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1. 3 2 Crystal Structures of GPCRS 3 3 Amino Acid Sequences and Sequence Alignment 3 3 1 Amino Acid Sequences Where to Get From 3 3 2 Ballesteros Nomenclature 3 3 3 Amino Acid Sequences Templates 3 3 4 Sequence Alignment 3 4 Homology Modelling 3 4 1 Modelling of the Transmembrane Domains 3 4 Modelling of Loops 3 4 3 Modelling of Internal 3 4 8 Modelling of the C Terminal Part of the Subunit or the Whole Go Subunit 222222 Refinement of the Receptor Model Construction of Ligands 5 1 Structure 46 5 2 Structure of the Phospholipid Bilayer 5 3 Lipid Bilayer Models Used in Molecular Modelling 5 4 Internet Sources for Lipid Bilayer Models 5 5 Embedding a GPCR into a Lipid Bilayer www allitebooks com viii Contents 6 Minimization and Molecular Dynamics 6 1 Generating a Complete Model of the Interesting GPCR 62 Embedding the GPCR in a Lipid Bilayer
2. 900945 Peart ing wp PRODRE vereion 804 942945 YRORR we ionan ias Daan van Malte peo Quart lonn conmanne 949955 790994 wring sir in cine 9929945 w Sckeertelhepf and P M F wan Aalen 2004 Y92994 TRONS veel det gh thm ppm cepere iegnepr IMS 909945 Dvaceing wp 720996 vsasuen 194 Your molecule added hydrogens WASHING 461 kyisegende ftem yous 7929945 inden 3 39 4 addu 922945 eleg change Nes charge em molecule 0 000 9909965 7 partial changes anbigueur obigen LD bend angler 59 obige 9505945 Y93994 qual ity em 8 19 mesie SENSUS Bove epencwace was wink Y94994 pacing Y92394 free CROMOS bend ivy egentem 8 908 Y92594 tose GROOT plane 31 93004 MOD taom bends m m ant Fig 4 3 First part of the results page of the PRODRG Server _ The PROCRG Server O 38 all H s pra
3. 6 3 Solvation of the Lipid GPCR Complex Achiving Electroneutrality of the Simulation Box and Minimization 64 Molecular Dynamic Simulation of your System 7 Calculation of Gibbs Energy of Solvation 7 Theory Link Between Microscopic and Macroscopic World 7 1 1 Statistical Mechanical Basics 7 1 2 From Potential Energy to the Chemical Potential 7 1 3 Concept of the Coupling Parameter Within MD Simulations ca qawas awa 72 Examples Conceptual and Practical Considerations 7 2 1 Example 1 Ethanol in Water Conceptual Considerations 7 2 22 Example 2 Ligand Receptor Complex and Affinity Conceptual Considerations 7 2 3 Example 1 Ethanol in Water Practical Considerations 7 2 4 Example 2 Gibbs Energy of Binding 8 Special Topics in GPCR Research 8 1 Interaction Between GPCR and the Go subunit 8 2 Process of Ligand Binding from the Extracellular Side into the Binding Pocket ofa 9 Force Fields waka d tg gatas 91 The Force Field Energy 9 1 1 The Stretching 9 1 2 Bending Energy
4. Status Mozilla Firefox Qut Bewbeten Cure He son eta x s zszz882e28s6805 058 K tata 2 receptor receptor orationi receptor OBI mos tw 222 raw Fig 3 1 GPCR tracking status Status November 2011 Source http gpcr scripps edu tracking_ status htm Fig 3 2 Crystal structure of the turkey B R 2 00 Warne et al 2011 16 3 Sequence Alignment and Homology Modelling covalent bond via a disulfide bridge Fig 3 3 Crystal structure of the human B R 3PDS Rosenbaum et al 2011 Fig 3 4 Crystal structure of the human CXCR4 3ODU Wu et al 2010 3 2 Crystal Structures of GPCRs Source http www pdb org 17 Fig 3 5 Crystal structure of the human CXCR4 30E0 Wu et al 2010 Fig 3 6 Crystal structure of the human 3EML Jaakola et al 2008 18 3 Sequence Alignment and Homology Modelling 3 3 Amino Acid Sequences and Sequence Alignment Before being able to start the homology modelling it has to be decided which amino acid of the template sequence corresponds to an amino acid in the target sequence Therefore a sequence alignment has to be performed manually or automatically Clustal http www clustal org for example is a software for multiple sequence alignment However before starting with sequence alignment the corresponding amino acid
5. o prot gro p S prot top ignh SARG SASP 610 SHIS LYS rm S prot pdb Converting pdb file for membrane ck ck ck ck ckokokok ck ck ck Ck ck Kk ck ck ck ck ck k ok ck ck ck ck k kc k k k k kk setenv LC NUMERIC Initializations map VMD atomic numbers to 54 55 156 157 58 59 160 61 162 163 164 165 atomic numbers index set map 31 43512 17 23 20 21 22 24 25 28 30 32 33 45 48 51 54 57 60 63 65 67 70 73 76 79 82 36 39 40 41 42 92 95 98 101 104 107 110 113 116 9 22 125 128 131 85 88 set 011 C23 035 C47 set n gro gro label C1 C2 C3 NA C5 C6 O7 58 09 O10 2 C13 O14 C15 O16 C17 C18 C19 C20 C21 C22 C24 C25 C26 C27 C28 C29 C30 C31 C32 O33 C34 C36 C37 C38 C39 C40 C41 C42 C43 C44 C45 C46 C48 C49 C50 1 CA2 number of sites per lipid molecule in gro notation set n_pdb 134 number of atoms per lipid molecule in VMD notation set gro file mem gro Caluclations and mapping 5 5 Embedding a GPCR into a Lipid Bilayer 51 181 182 166 167 168 169 170 171 1 72 173 174 175 176 177 178 179 180 183 184 185 186 187 188 189 190 191 192 193 194 195 196 units 1 mem pdb cut da fl n pdb number of lipid molecules 8 number of atoms units n gro echo Li
6. HQ T pVY gt exp A M Pr dpidr dv 7 23 kT and according to Eq 7 10 dG Q kT dQ a 0 20 7 24 0 00 where the term 42 2 259 represents mean value of XP and so we able to calculate as a function of by MD simulation numerical integra tion procedure will yield the desired term G 2 G 1 The concept of the coupling parameter could be thought as special case of the energy perturbation concept mentioned in the foregoing section In the next two sections we will apply the concept of the coupling parameter to the calculation of the Gibbs energy of solvation for the system ethanol water and subsequently to the estimation of the equilibrium constant for the ligand binding process 7 22 Examples Conceptual and Practical Considerations 7 2 1 Example 1 Ethanol in Water Conceptual Considerations From a thermodynamic point of view the desired solvation energy requires the calculation of the reference chemical potentials at the pressure of 1 bar and the temperature of 298 15 K when transferring one mole of ethanol from the ideal gas state into the solvent water forming an ideal solution of concentration 1 mol l Cai MEOH 7 25 Applying the coupling parameter concept we will start from a system state 1 which corresponds to the solution of ngog moles of ethanol and moles of water In the next step we will switch off all in
7. Vl Qu God qaa q yas Sas Mn MON AL GM MG Ned wil dis Sis e s Ck Gp a CH x CER E Fig 5 5 Starting page of lipidbook http lipidbook bioch ox ac uk Domanski et al 2010 OL TT uten UR lipidbook Hosted 40 now Wee Browser The Browser gives quick access to packages through the Filter packages function and presents a fist of the selected packages It is the man entry pont into the database The complete ist of al pid packages is also available but might take while to load Filter packages You can fiter ages by forcefield ipid abbreviation and smulabon code type Multiple entries can be selected by using the and or other special keys together with mouse cicks Database fields Forcefleld type and version cf the force field combined in a single identfier Cede smulaoon code determines the fie format of the parameter fles Lipid common abbrewabon of a lipid or other molecule The lone wildcard character selects all entries in the gr n category Forcefield Code Lipid ull scil AMBER GAFF Amber DMPC 1 2 demynistoy sn glycero 3 phosphocholine Bondini Chamm POPG 1 palmitoyt 2 oleoy sn glycero 3 phosphogtycerol 1 CHARMM22 Gromacs POPE 1 palmitoy 2 oleoy sn gyycero 3 phosphoethanolamine CHARMM27 Hippo DPPC 12 CHARMM38 NAMD POPC 1 palmitoyt 2 oleoy sn gtycero 3 phosphocholine a GROMOS4331 DO
8. 1st generation 2nd generation 1 Lig II Rec Lig 3rd generation I Lig Il Rec Lig 4th generation Lig IlII Rec Lig 5th generation I Lig HI Rec Lig n th generation until destination structure is reached Fig 8 9 Generation child scheme of the LigPath calculation Based on the starting structure new minimized child structures are generated by the LigPath algorithm The children are divided into three groups 7 and III Each group contains n children The best child of each generation is used as starting structure for the next generation The generation child cycle is continued until the destination structure is obtained Copyright by Springer with permission from Springer guided in direction of their destination position Again due to the combination with a Monte Carlo like procedure the guiding has a random character The division of each generation into three different child groups is very important in order to obtain a non restrained ligand binding and receptor activation pathway Out of each generation the best child is used as starting structure for the next generation The best child of each generation is selected by a combined criterion with regard to rmsd and potential energy On the one hand the potential energy of the best child should be as small as possible on the other hand
9. 3 4 2 0 100 15700000 0 0 100 15700000 0 H pairs 91 fu cl 1 4 1 4 H angles ai ak fu CO Cl 11 20 3 4 109 5 520 0 109 5 520 0 5 4 4 109 5 450 0 109 5 450 0 ci Hm dihedrals al fu 0 m 1 2 3 4 1 0 0 1 3 S 0 0 1 3 3 dth ca o Fig 4 6 GROMACS topology file of ethanol calculated by the PRODRG server www allitebooks com Construction of Ligands 35 Construct your ligand with an appropriate editor as 3D structure Check your molecule if e g the configuration of chiral atoms is correct Minimize your molecule if possible Save the minimized molecule as pdb file Start the PRODRG Server If you do not have a token to work with the PRODRG Server please fill In your E Mail in the corresponding field and used the Send button Be aware that it may take some time before you get your token via E Mail If you have the token please copy it from your E Mail into the appropriate field Now you can start working with PRODRG Open your pdb file in an appropriate editor Copy and paste the whole pdb file into the corresponding field of the PRODRG server Choose Yes or No in the field chirality depends on your molecule Always choose full charges in the field charges Choose Yes in the field EM energy minimization Now start your PRODRG Job Please be aware that the calculations may take a while a
10. and GBy complex In dependence of the subtype of the activated Ga the appropriate signal cascades are induced selectively Fig 2 8 Vauquelin and von Mentzer 2007 fan 1 V NU 0900009 00900000000 p ooo AJ Ay 2000 P Ms GTP GDP GDP GTP GTP GDP cAMP PIP IP DAG wA phosphorylation ER phosphorylation of target proteins of target proteins physiological physiological effect effect Fig 2 8 Signalling cascade induced by the binding of an agonist to a GPCR Three different signalling cascades with regard to G s Go and Gag are shown 2 4 Important Internet Sources with Regard to GPCRs A very important internet source is the GPCR network http cmpd scripps edu Fig 2 9 Here you can find important information concerning GPCRs The track ing status of solving the crystal structure of distinct GPCRs might be of special interest see Chap 3 Fig 3 1 2 4 Important Internet Sources with Regard to GPCRs 11 The GPCR sor Home Page gt t Alden e Understanding Human GPCR Biology 4 GPCR network GLUTAMATE 15 VE GPCR Structures esse Port to Flags to See rut March 21 2012 Pub
11. 7 48 7 2 Examples Conceptual and Practical Considerations 93 Table 7 2 Derivative of the Gibbs energy with respect to the coupling parameter for the transfer of ethanol from vacuum into water at 293 0 K 0 00 kJ mol 90 02 0 45 kJ mol 22 34 0 90 kJ mol 43 95 0 05 204 43 0 50 13 78 0 95 50 02 0 10 0 20 0 30 0 40 124 34 76 86 54 48 38 24 0 55 0 60 0 70 0 80 11 96 41 98 41 61 37 91 0 975 0 99 0 995 1 00 52 40 55 31 56 47 57 90 Therein xo corresponds to the lower bound of integration and x to the upper bound of integration Now let us apply this integration method to the example ethanol in water shown above in order to calculate the solvation energy The data presented in Fig 7 4 are given in Table 7 2 and represent the derivative of the Gibbs energy with respect to A as a function of A The integration can easily be performed using Eq 7 48 with the following gawk script named integrate usr bin gawk f BEGIN 5 0 n 0 n x n 1 s 0 5 x i 1 print dG_solv s OFS yin 2 END for i l i lt n i L x i vli 1 ylil kJ mol Now you can open an editor write the command sequences into the editor and save the file with the name integrate To test this script you should first change your file access rights using the following command chmod u x integra
12. Name Source and short description Gromacs http www gromacs org GROMACS is a versatile package to perform molecular dynamics i e simulate the Newtonian equations of motion for systems with hundreds to millions of particles www gromacs org Scott et al 1999 van der Spoel et al 2005 PRODRG http davapc 1 bioch dundee ac uk prodrg will take a description of a small molecule and from it generate a variety of topologies for use with GROMACS http davapc 1 bioch dundee ac uk prodrg Schuettelkopf and van Aalten 2004 NAMD http www ks uiuc edu Research namd A parallel MD code for high performance simulations of large systems TINKER http dasher wustl edu ffe Software tools for molecular design Clustal http www clustal org Software for multiple sequence alignment Whatif http swift cmbi ru nl whatif A versatile molecular modelling package Vriend 1990 PROCHECK J Hhttp www ebi ac uk thornton srv software PROCHECK Checks stereochemical quality of a protein PSIPRED http bioinf cs ucl ac uk psipred Protein structure prediction server I TASSER http zhanglab ccmb med umich edu I TASSER Protein structure and function predictions A Strasser H J Wittmann Modelling of GPCRs 161 DOI 10 1007 978 94 007 4596 4 Springer Science Business Media Dordrecht 2013 162 Appendix Software for Visualisation Name Source and short description Chimera http www cgl ucsf edu chimera A software fo
13. 9 1 3 The Torsional 9 1 4 The van der Waals 9 1 5 The Electrostatic Energy 9 2 All atom concept and Site concept 93 Force Field Parameters 10 Thermodynamics of Ligand Receptor Interaction Rr E RUSSIE E ER EAE RESI 10 2 Ligand Receptor 1 10 3 Thermodynamic Basics 10 4 Evaluating AH and AS 10 5 Special TOpICS u sa RE RU RE ERR www allitebooks com Contents ix 11 Important UNIX LINUX 139 11 11 Some Basic Aspects of the Operating System UNIX LINUX 139 11 2 The Use of Shell Operators and Meta Characters in Tcsh Bvitonmernts RE SEE XM 139 11 3 Shell Substitutions 140 11 3 1 File Name Substitution 141 11 3 2 Variable Substitution 141 11 3 3 Command Substitution 143 11 3 4 Protection Mechanism for Meta Characters of the TC Shell re ERR TER ET 143 11 4 Discussion of Selected LINUX Commands 144 11 5 Loops Statements of the Tesh Shel
14. coordinates MOL Moltile SYBYL 2 text drawing and from it generate variety of topologies for use with GROMACS WHAT IF Autodock HEX CNS REFMAC5 SHELX and other programs as well as energy minimized coordinates in a variety of formats Please note that thes Server 15 strictly for academic use max 5 submissions day only For more extensive or commercial use you can obtain your own copy of P A list of some frequently asked questions is available is available please have a look at t if you are having problems with PROORG s output f that does not help or you have other comments suggestions feel free to email Daan van Asten you use the data generated by this server in publicabon please cite W Sch ttelkopf and D van Aalen 2004 PRODRG a tool for high throughput crystaliography of protein igand complexes Acta Crystallogr D60 1355 1363 PMID 1 57 reprint avilable here Get started Fig 4 1 Homepage of the PRODRG server http davapc1 bioch dundee ac uk prodrg x Ardes 5 NE moos wa PRODRG Home Compound submission Betore you can subm molecules to the PROORG server you wil need to have a token Fil in your 00 4 below and nt SUDME and a token essentialy a short text string valid for three PROORG runs be emaded to you My emat adoress Suoma If you already have a token paste t here Then etner Drew the Molecule
15. After some minutes you obtain the results page At first you see some remarks of the server and additionally the molecule with added hydrogens is shown Fig 4 3 If your scroll down you see a summary of different output files Fig 4 4 Most important concerning GROMACS is the third item under Coordinates and the first item under Docking MD simulations Within the Coordinates section for GROMACS you find three different items namely a coordinate file with polar hydrogens with polar aromatic hydrogens and with all hydrogens If you look onto the number of coordinate lines you see differences in case of ethanol between polar hydrogens and all hydrogens Since the site concept is used in GROMACS the hydrogens of an alkyl moiety are integrated within the carbon This means for example that a methyl group CH3 does not consist of four sites one carbon and three hydrogens instead it is summarized in one site see Chap 9 This is a very important aspect with regard to simulation time Because of the combination of several atoms to one site the number of sites is reduced and this leads to an exponential decrease in simulation time If you compare with the contents of the topology file the coordinate file polar aromatic hydrogens is relevant Be aware that the number of coordinates in the gro file Fig 4 5 has 32 4 Construction of Ligands Tap vh
16. subunit can 8 1 Interaction Between a GPCR and the Go subunit 107 Fig 8 1 Starting structure for the surface scan between a GPCR and the subunit Copyright by Springer with permission from Springer be generated in a similar manner as described for the GPCRs For the systematic search a starting structure of the GPCR G protein complex is needed Optimally the starting structure should be modelled in the following way 1 The vertical axis of the receptor should be aligned in z direction of a coordinate system thus the interaction surface of the GPCR with the Go is found in a xy plain Fig 8 1 2 Now the Go has to be positioned in an optimal manner Put it in a distinct distance below the intracellular part of the receptor in such way that the C terminus of points into direction of the open pocket of the receptor in the intracellular Fig 8 1 There should be no contact between the sites of the receptor and the subunit There is no software for systematic scan of the potential energy surface available Thus the modeller has to establish the corresponding software by his own We recom 108 8 Special Topics in GPCR Research mend that the calculations are carried out on a computer with LINUX Furthermore we recommend using the programming language C in combination with C shell scripts For the energetic calculations every modelling software can be used in gen eral but GROMACS http www gromacs org is
17. 60 SGKSTIVKQM 120 QFRVDYILSV 180 IKQDDYVPSD 240 IFVVASSSYN 300 KSKIEDYFPE 360 CAVDTENIRR Literature rat guanine nucleotide binding protein G I G S G T subunit beta 1 P54311 340 amino acids 10 20 30 40 50 60 1 UniProtKB MSELDQLRQE 70 MHWGTDSRLL 130 CSIYNLKTRE 190 TGHTGDVMSL 250 FATGSDDATC 310 KADRAGVLAG AEQLKNQIRD 80 VSASQDGKLI 140 GNVRVSRELA 200 SLAPDTRLFV 260 RLFDLRADQE 320 HDNRVSCLGV ARKACADATL 90 IWDSYTTNKV 150 GHTGYLSCCR 210 SGACDASAKL 270 LMTYSHDNII 330 TDDGMAVATG SQITNNIDPV 100 HAIPLRSSWV 160 FLDDNQIVTS 220 WDVREGMCRQ 280 CGITSVSFSK 340 SWDSFLKIWN GRIQMRTRRT LRGHLAKIYA 110 120 MTCAYAPSGN YVACGGLDNI 170 180 SGDTTCALWD 230 240 TFTGHESDIN AICFFPNGNA 290 300 SGRLLLAGYD DFNCNVWDAL 207 Bovine guanine nucleotide binding protein G D G S G O subunit samma 2 GNG2 UniProtKB length 10 20 P63212 30 40 50 60 MASNNTASIA QARKLVEQLK MEANIDRIKV SKAAADLMAY CEAHAKEDPL LTPVPASENP 70 FREKKFFCAI L References Abraham MH 1984 Thermodynamics of solution of homologous series of solutes in water J Chem Soc Farad T 1 80 153 181 Alves ID Salamon Z Varga E Yamamura HI Tollin G Hruby VJ 2003 Direct observation of G protein binding to the human 6 opioid receptor using plasmon waveguide resonance spectroscopy J Biol Chem 278 48890 48897 Alves ID Sal
18. The second command inverts the search i e the output comprises of all lines not matching the regular expression Thethird instance of grep prints the number of matching lines for file The last command form prefixes each line on output with its corre sponding line number within the file followed by a colon example Given the file data created by the command cat in the appropriate section we want to extract all lines containing the pattern DRG using grep in its first form gt grep DRG data where the corresponding lines may contain the pattern DRG in any position to specify this position more exactly would lead to the following statement Find all lines where the string DRG is located after a line number followed by the character In this case the regular expression and the corresponding command would look like this gt 0 9 DRG data The character specifies the beginning of a line and the sequence 0 9 means a number of the set 0 9 a pair of square brackets denotes a set repeated one or more times indicated by the character where the plus sign must be preceded by a backslash to signalize the special meaning one or more All other characters stand for themselves To print out all lines of the file data not containing the string DRG use gt grep v DRG data To print only a count of all lines containing for examp
19. on detergents and sm ar molecules that are of interest when senang brologcal membranes LLIPI L Wink ore the community Anyone can browse and download parameters but deposibon Browse requires user registration For more detads and contact information see About Please report bugs and requests for morovements through our Issue Packing System Our Policy explains the terms under which the data are made avaiable THAT THE OPERATORS OF THIS WEBSITE DO GUARANTEE THAT THE CONTENT MADE AVAILABLE VIA LIPID OOK I CORRECT OR FOR ANY PURPOSE IT 1 74 UMP E RELPONSIBILITY TO VERIFY THAT THE PARAMETERS ARE PRODUCING yours Browse Parameters are bundied n packages start by browsing the database Search The full text search indexes parts of this site and a number of other ses with related content If you know exactly what you for then t s probably quaker to use the Browser instead of search md Reference Lipidbook described in 2 Domats A Stansfeld MEA Tansom and tez Lieidbesh A Public Repormery for Force Field Parameters Used in Membrane Simulations J Mamivase Biel 216 2010 253238 do 10 1007 100232 010 929 8 VURLihtp voidtoch bed ov oe ub Reperts can be cbtaned from the authors Issue Wacker Wiki Quesbons Answers Contact
20. g shortlog wait endif z i set i l 7 2 Examples Conceptual and Practical Considerations 89 41 while i lt 18 42 tail n 100001 lambda i dgdl xvg gt lambda i dgdl dat 43 echo i average gibbs lambda i dgdl dat gt gt lambda gibbs dat 44 Q i 45 end Before the script gibbs_energy can be started the execute permission for the user has to be set using the following command chmod u x gibbs energy Following an exemplary mdp file named md first mdp for calculation in aqueous phase is given We like to suggest explicitly that the simulation parameters may be adopted by the user as appropriate for the simulation problem In the mdp file shown below the parameter init lambda is set to zero for the first calculation with full interactions The file md mdp is identical with the file first mdp only the parameter unconstrained start is set to yes and gen vel is set to no In the script gibbs energy see above line 24 and 25 the last line of the file md mdp is adopted with regard to the actual value of in the parameter init lambda line 66 in md mdp For cal culation in gaseous phase the mdp files have to be adopted in an appropriate manner 102 first mdp 2 MD 3 4 Imput file 52 6 title Ethanol in water 7 cpp lib cpp 8 define DPOSRES 9 constraints all bonds 10 constraint_algorithm lincs 11 unconstrained
21. well equilibration protocoll kJ mol nm 00 25 50 7 5 100 125 150 17 5 20 0 t ns Of course you can subsequently start each cycle of the equilibration protocol manually However it is more comfortable to establish a script equilibrate system which will be presented later on in this chapter First one needs an appropriate position restraint file which has the file name extension itp in general Therefore one has to decide which sites should be administered with position restraints In the following you see a part of gro file containing the coordinates of a protein in the ffG53a6 force field notation In the following example the sites 0 N and H should be administered with position restraints 105SER N 987 4 491 3 927 4 520 105SER H 988 4 569 3 864 4 530 105SER CA 989 4 495 4 049 4 604 105SER CB 990 4 616 4 061 4 697 105SER OG 991 4 739 4 063 4 624 105SER HG 992 4 800 3 994 4 664 105SER C 993 4 477 4 182 4 529 105SER O 994 4 381 4 254 4 558 106MET N 995 4 551 4 202 4 420 106MET H 996 4 634 4 147 4 405 106MET CA 997 4 533 4 321 4 333 106MET CB 998 4 652 4 341 4 238 106MET CG 999 4 788 4 340 4 309 106MET SD 1000 4 803 4 453 4 452 106MET CE 1001 4 950 4 385 4 525 64 6 Minimization and Molecular Dynamics 106MET C 1002 4 399 4 329 4 255 106MET O 1003 4 341 4 437 4 244 107ASP N 1004 4 344 4 213 4 214 107ASP H 1005 4 396 4 128 4 216 107ASP CA 1006 4 210 4 204 4 149
22. 106 1002 4 399 4 329 4 255 107ASP 1011 4 095 4 247 4 244 Note that only lines with blank before and after the C are printed because the pat tern for search is C However you do not see this output on your screen because the results are connected via the pipe to the command cut Why is the command cut used One needs not the complete line but only the number of the site If you have a closer look into protein gro you see that the site numbers are written in the columns 17 20 if the protein contains not more than 9999 sites The option 16 21 cuts the columns 16 21 including a blank before and after the site number and redirects the results in to file site dat If you would use only gt www allitebooks com 6 4 Molecular Dynamic Simulation of your System 65 the file site dat is created and the data are written into the new file But be aware if a file site dat is already here in the current working directory its data will be deleted If the operator gt gt is used all new data are appended to site dat Now site dat should contain the following information 993 1002 1011 After repeating the analogue commands with regard to O N and H the file site dat should contain the following data 993 1002 1011 994 1003 1012 987 995 1004 998 996 1005 Because the numbers are not sorted numerically use the following command to ensure a correct order gt sort n site dat s
23. 15 potential energy surface representing the smallest rmsd with regard to the crystal structure Copyright by Springer with permission from Springer 30 15 30 a a a a 8 Special Topics in GPCR Research rmsd a 2 Pr Pr a BE a Pr a Pr Pr 8 1 Interaction Between a GPCR and the Go subunit 111 A local minimum on the potential energy surface model Ia with an rmsd between model and crystal structure of about 3 3 was identified Fig 8 4 An alignment of the predicted models I and Ia with the crystal structure is shown in Fig 8 5 Rotation of Ga rmsd 8 4 rmsd 3 3 Fig 8 5 Alignment of model I left orange or model Ia right orange with the corresponding parts of the crystal structure 3SN6 green Copyright by Springer with permission from Springer Taking into account that the crystal structure is artificial due to the cocrystallization of the Gs binding nanobody Nb35 and the T4 lysozyme Fig 2 7 the predicted model I is in very good accordance to the experimental structure As already stated all experimental results concerning GPCR G protein interaction including muta genesis and pharmacological studies cannot be explained by only one interaction model Oldham and Hamm 2008 Therefore the hypothesis of sequential binding is discussed in literature Herrman
24. 2006 like the NK1 receptor Evers et al 2004 P2Yg receptor Costanzi et al 2005 the CB2 receptor Pei et al 2008 the NKB and NK receptor Ganjiwale et al 2011 the cholecystokinin 1 receptor Henin et al 2006 histamine receptors Jongejan et al 2005 Preuss et al 2007 Jongejan et al 2008 Lim et al 2008 Igel et al 2009 Strasser and Wittmann 2010a Brunskole et al 2011 and besides addresses GPCR oligomerization Simpson et al 2010 3 1 Selection of a Template To be able to start homology modelling one has to search for an appropriate template structure A large number of such templates are available at the Protein Data Bank PDB http www pdb org Until end of 2011 a large number of crystal structures were available Table 3 1 As illustrated by Table 3 1 most crystal structures con cern the and B adrenergic receptor These crystal structures are of great interest since different types of ligands like inverse agonists antagonists or partial agonists are bound Thus these crystal structures reveal important information with regard A Strasser H J Wittmann Modelling of GPCRs 13 DOI 10 1007 978 94 007 4596 4_3 Springer Science Business Media Dordrecht 2013 14 3 Sequence Alignment and Homology Modelling Table 3 1 pdb codes of most important crystal structures related to opsin or GPCRs GPCR Related pdb codes Bovin rhod opsin 1F88 1GZM 3DQB 3PQR 3PXO Human
25. 2008 Exploiting QSAR models in lead optimization Curr Opin Drug Discov Devel 11 569 575 Gether U Kobilka BK 1998 G protein coupled receptors II Mechanism of agonist activation J Biol Chem 273 17979 17982 Goetz A Lanig H Gmeiner P Clark T 2011 Molecular dynamics simulations of the effect of the G protein and diffusible ligands on the B adrenergic receptor J Mol Biol 414 611 623 Greasley PJ Fanelli F Scheer A Abuin L Nenniger Tosato M de Benedetti PG Cotecchia S 2001 Mutational and computational analysis of the b adrenergic receptor involvement of basic and hydrophobic residues in receptor activation and G protein coupling J Biol Chem 276 46485 46494 Grishina Bertlot CH 2000 A surface exposed region of in which substitutions decrease receptor mediated activation and increase receptor affinity Mol Pharmacol 57 1081 1092 van Gunsteren WF Berendsen HJC 1987 Thermodynamic cycle integration by computer simula tion as a tool for obtaining free energy differences in molecular chemistry J Comput Aided Mol Des 1 171 176 van Gunsteren WF Berendsen HJC 1990 Computer simulation of molecular dynamics methology applications and perspectives in chemistry Angew Chem Int Ed Engl 29 992 1023 van Gunsteren WF Billeter SR Eising AA H nenberger PH Kr ger P Mark AE Scott WRP Tironi IG 1996 Biomolecular simulation the GROMOS96 manual an user guide Hochschulverlag AG an der ETH Z rich Halgren TA 1996
26. 6 86 7 Calculation of Gibbs Energy of Solvation Calculate 7677 for gas phase via MD simulation for example via the shell script g bbs energy see below Center your solute obtained by item 4 in the simulation box Solvate your solute with the desired solvens using the GROMACS command genbox Adopt your mdp file for minimization if necessary Minimize your simulation box solute in solvens Adopt your mdp file for molecular dynamic simulation if necessary Calculate 452 for ethanol in water via MD simulation for example via the shell script g bbs energy see below Fig 7 1 Thermodynamic cycle for ethanol in water coloured ligand full AG interactions grey ligand Coulomb and van der Waals gt interactions Each of the mentioned items will be explained now step by step First generate an appropriate gro and top file for ethanol as described in detail in Chap 4 Save the files shown explicitly in Chap 4 as ethanol gro and ethanol itp In the next step one has to modify the topology file ethanol itp In the section atoms only the atom types charges and masses for the state 1 are defined To calculate the Gibbs energy of solvation according to the thermodynamic cycle Fig 7 1 Villa and Mark 2002 the solute has to be transferred into an ideal gas state by switching of all the Coulomb and van der Waals interactions
27. D 18 I ipt 0 500 1000 1500 2000 0 500 1000 1500 2000 generation generation Phe 44 Phe 44 3 EDS ca E 590 NAJ aasawa E 5 12048 OR 0 500 4000 1500 2000 0 500 1000 1500 2000 generation generation Fig 8 12 Changes in dihedral angles of distinct amino acid side chains during binding of a partial agonist Copyright by Springer with permission from Springer 118 8 Special Topics in GPCR Research surface The inactive receptor R is separated from the active receptor R by a high potential energy barrier This is also true for the inactive LR and active ligand receptor complex LR However the high energy barrier shows a small pass which can be passed during the binding process of the ligand Furthermore this modelling data suggest that the ligand binding accompanied by receptor activation is at least for this example the energetically preferred pathway Thus during the binding process of a partial agonist the receptor gets more and more activated As described above the LigPath calculations allow getting insight onto poten tial energy surface but also detailed insights onto processes on structural level can be obtained Largest changes for example were described for Phe and 6 48 Fig 8 12 The conformational changes of the dihedral angles x1 and x2 of the aromatic amino acid side chains 655 Phe gt and Tyr 9 establish an aromatic channel for the phen
28. lt N lt L1 Y H NAN 12 Fig 7 11 Structures of selected compounds Table 7 10 Calculated Gibbs energies of solvation for selected compounds Fig 7 11 in water in the binding pocket of hH R and for the transfer of aqueous phase into the binding pocket of hH at a temperature of 298 15 K Wagner et al 2011 copyright by Springer with permission from Springer AG L wat L hHiR L wat hHi R kJ mol kJ mol kJ mol L1 171 2 446 21 275 23 L2 145 3 436 16 291 19 L3 R 248 4 515 18 267 22 L3 S 243 3 507 16 264 19 Table 7 10 are in very good accordance to the trend of the experimental data Ob viously it would be a much simpler task only to compute the transfer of the ligand from the gaseous state into the binding pocket of the receptor AG L hH R Table 7 10 Wagner et al 2011 But these data do not reveal the mentioned trend of affinities Omitting the desolvation process for the ligand would pretend a higher affinity for L3 R S than for L2 Chapter 8 Special Topics in GPCR Research 8 1 Interaction Between a GPCR and the Go subunit It is well known that GPCRs couple in the intracellular part with G proteins which consist of a Ga GB and Gy subunit Induced by activation of the GPCR by an agonist the G proteins act as intracellular switches on molecular level turning on intracellular signal cascades What is kno
29. receptor X ray based structures are the best choice up to now to get structures of the interesting biochemical system which would then be utilized to calculate and AS or rate constants for comparison with the experimentally determined values and to validate a particular model Making use of statistical mechanical concepts see Chap 7 1 the central quantity is the potential energy of the system from which we are able to calculate the phase integral and thereafter the chemical potential which governs the chemical behaviour of an arbitrary species These concepts are adopted in the framework of the quantum mechanical concept by calculating the so called partition sum see Chap 7 1 Here we also have to define the potential energy of the system of interest and then we have to solve the corresponding Schr dinger equation to get the allowed energy levels But up to now it is impossible for such large systems comprised of ligand receptor membrane water and ions to do such ab initio calculations in an acceptable time To simplify the calculation procedure a stable state is defined as a energy minimum of the so called potential energy surface represented by the potential energy as a function of all coordinates of the particles present in the system Starting from a first guess of a structure minimizing the poten tial energy with respect to the coordinates will lead to a final structure from which we are able to derive a set of proper
30. three conserved internal water molecules between TM II TM Asn7 45 TM Vil III and TM VII in the intracellular part of the TM Il transmembrane helix bundles of the gpH R Copyright by view from the side Springer with permission from Springer Asn 4 9 inactive active view from the extracellular part Asp250 Ser inactive active 120 8 Special Topics in GPCR Research In general the LigPath algorithm allows studying structural and energetical changes during ligand binding and receptor activation on molecular level in de tail Thus it is really worth to implement such an algorithm However one should taken into account that therefore it is necessary to master a programming language like C Additionally one should be able to perform some geometrical calculations like rotation around axis rotation around a bond translation and similar Chapter 9 Force Fields Taking into account the computational difficulties as mentioned in the introductionary part when calculating the potential energy of a system the use of the so called force fields enables us to get relevant structural and energetic information In this chapter the most important facts concerning force fields will be presented For more detailed information the reader is referred to appropriate literature Halgren et al 1996 Jorgensen et al 1996 MacKerell et al 1998 Jensen 1999 Duan et al 2003 Mackerell 2004 Oostenbrink et al 2004
31. 11100 03 0 12100 03 0 11100 03 0 11100 03 0 11100 03 0 11100 03 0 11100 03 0 11100 03 0 46020 03 0 46020 03 0 39750 03 0 39750 03 0 39750 03 0 39750 03 0 39750 03 0 58580 03 0 39750 03 0 39750 03 0 46020 03 0 46020 03 0 46020 03 0 41840 03 0 46020 03 0 46020 03 0 50210 03 0 50210E 03 0 46020E 03 0 50210E 03 0 46020E 03 0 46020E 03 0 46020E 03 0 46020E 03 0 46020E 03 0 46020E 03 173 174 Appendix 23 24 25 1 120 000 502 080 cis thingies 24 25 26 1 120 000 502 080 cis thingies 25 26 27 1 0 11100 03 0 46020E 03 26 27 28 1 0 11100 03 0 46020 03 27 28 29 1 0 11100 03 0 46020 03 28 29 30 1 0 11100 03 0 46020E 03 29 30 31 1 0 11100 03 0 46020 03 30 31 51 1 0 11100 03 0 46020 03 31 51 52 1 0 11100 03 0 46020 03 32 33 34 1 0 12000 03 0 41840E 03 33 34 35 1 0 12400 03 0 50210 03 33 34 36 1 0 11500 03 0 50210E 03 34 36 37 1 0 11100 03 0 46020 03 35 34 36 1 0 12100 03 0 50210 03 36 37 38 1 0 11100 03 0 46020 03 37 38 39 1 0 11100 03 0 46020 03 38 39 40 1 0 11100 03 0 46020 03 39 40 41 1 0 11100 03 0 46020 03 40 41 42 1 0 11100 03 0 46020 03 41 42 43 1 0 11100 03 0 46020 03 42 43 44 1 0 11100 03 0 46020 03 43 44 45 1 0 11100 03 0 46020E 03 44 45 46 1 0 11100 03 0 46020 03 45 46 47 1 0 11100 03 0 46020 03 46 47 48 1 0 11100 03 0 46020 03 47 48 49 1 0 11100 03 0 46020 03 48 49 50 1 0 1
32. 2 8 9 105 113 114 117 118 131 132 Alignment 22 23 45 58 111 156 All atom concept 124 Antagonist 2 7 13 113 131 132 Aqueous 87 89 91 99 101 114 129 B Ballesteros nomenclature 20 Bending energy 122 127 Binding pocket 24 99 101 103 112 113 118 131 134 138 Boundary conditions 83 Bovine rhodopsin 20 22 C C terminus 5 7 9 22 25 105 107 cat 144 148 Chemical potential 2 77 80 83 132 Chemical thermodynamics 132 Chemokine receptor 14 Cholesterol 39 Classical statistical mechanics 76 Conserved amino acids 20 21 23 Coulomb interaction 83 86 87 Counter ions 85 134 Coupling parameter 79 80 83 85 Crystal structure 1 9 10 13 14 20 22 24 39 105 106 112 cut 153 Cut off 82 83 A Strasser H J Wittmann Modelling of GPCRs D Disulfide bridge 5 7 23 24 Dopamine receptor 14 Dummy 86 87 E E2 loop 5 7 23 24 Efficacy 2 122 Electrochemical potential 132 134 Electrostatic energy 124 Energy minimization 26 28 31 Enthalpy 2 95 135 136 Entropy 2 3 95 135 Equilibration 55 62 66 73 100 Equilibration protocol 55 63 Equilibrium constant 75 77 78 83 135 136 138 Extracellular loops 5 6 23 24 F Family A 5 Family B 6 Family C 7 Fatty acid 38 55 Force field 2 3 29 40 98 121 125 Force field parameters 125 G G protein 9 105 106 subunit 105 108 subu
33. 24 where in the case of dilute solutions A H approximately does not depend on the concentration of any reactant Substituting from Eq 10 23 into 10 24 denotes the quantity Ah as function of the total ligand concentration c7 caused by adding successive amounts of the stock solution containing the ligand species 1 Ah ames 10 25 By applying a nonlinear least square fit method we determine the unknown param eters AH and K Knowing about K we are able to calculate AG according to Eq 10 18 and with the help of Eq 10 19 we get A 5 Another method uses the temperature dependence of the equilibrium constant and the related quantity AG to determine A H and A 5 Starting with Eqs 10 18 and 10 19 we can write AH TAS RT ln K 10 26 10 4 Evaluating AH and AS 137 The measurement of K at the temperature of interest leads to an equation containing two unknowns A H and AS for that temperature To solve this problem we could assume temperature independent quantities A H and A 5 so the determination of K at a series of temperatures would lead to a linear relationship between T and the right hand side of Eq 10 26 with slope 5 and intersection A H But extensive investigations of the association constant at different temperatures reveal a distinctive dependence of AH and AS on temperature Thus the above mentioned linear relationship between and will no longer hold
34. 250 260 270 280 290 300 LFALCWLPLH IINCFTFFCP DCSHAPLWLM YLAIVLSHTN SVVNPFIYAY RIREFRQTFR 310 320 330 340 350 360 KIIRSHVLRQ QEPFKAAGTS ARVLAAHGSD GEQVSLRLNG HPPGVWANGS APHPERRPNG 370 380 390 400 410 YALGLVSGGS AQESQGNTGL PDVELLSHEL KGVCPEPPGL DDPLAQDGAG VS Appendix 205 Lysozyme LYS_BPT4 164 amino acids UniProtKB organism 70 enterobacteria phage T4 bacteriophage T4 10 20 30 40 50 60 MNIFEMLRID EGLRLKIYKD TEGYYTIGIG HLLTKSPSLN AAKSELDKAI GRNCNGVITK 80 90 100 110 120 DEAEKLFNQD VDAAVRGILR NAKLKPVYDS LDAVRRCALI NMVFQMGETG VAGFTNSLRM 130 140 150 160 LQQKRWDEAA VNLAKSRWYN QTPNRAKRVI TTFRTGTWDA YKNL bovine guanine nucleotide binding protein G t subunit alpha 1 GNATI UniProtKB MGAGASAEEK 70 ECLEFIAIIY 130 DIIQRLWKDS 190 IETOFSFKDL 250 ESLHLFNSIC 310 VOFLELNMRR HSRELEKKLK 80 GNTLOSILAI 140 GIQACFDRAS 200 NFRMFDVGGQ 260 NHRYFATTSI 320 DVKEIYSHMT P04695 350 amino acids 10 20 30 40 50 60 EDAEKDARTV 90 VRAMTTLNIQ 150 EYOLNDSAGY 210 RSERKKWIHC 270 VLFLNKKDVF 330 CATDTONVKF KLLLLGAGES 100 YGDSARQDDA 160 YLSDLERLVT 220 FEGVTCIIFI 280 SEKIKKAHLS 340 VFDAVTDIII GKSTIVKOMK IIHQDGYSLE 110 120 RKLMHMADTI EEGTMPKEMS 170 180 PGYVPTEQDV LRSRVKTTGI 230 240 AALSAYDMVL VEDDEVNRMH 290 300 ICFPDYNGPN TYEDAGNYIK 350 KENLKDCGLF 206 Appendix bovine guanine nucleotide binding protein G s s
35. 5 shown above The 5 after the search string induces that grep only searches the string at the end of a line In order to avoid that the is misinterpreted as variable substitution the single quotes have to be used instead of double quotes For the position restraints only the number of the corresponding sites is of interest thus the long command line above has to be combined at last with the cut command in the following manner gt head n 467 protein3 top tail n 461 tr s cut d f2 6 grep C cut d f1 The further steps in handling the file site dat are the same as already mentioned above 6 4 Molecular Dynamic Simulation of your System 71 Supposing the existence of the constraint files created above the following shell script equilibrate system can be used for equilibration of the simulation box Be aware that the files system top system gro minimized simulation box see Sect 6 3 md first mdp mdp file for the first equilibration cycle md mdp mdp file for all following cycles and the i tp files reside in the same directory as the shell script 1 bin tcsh f 2 3 set fconst 1000 800 600 400 200 100 4 5 set nr of fconst fconst 6 7 1 8 9 while i nr of fconst 10 mkdir posre_ i 11 cd 6451 12 cp system top 13 cp posre bb S fconst i itp posre itp 14 15 if i 1 then 16 Cp system gro 17 cp md f
36. 53977 0 52977 0 52977 8 Fig 4 5 Three different GROMOS87 GROMACS coordinate files as output of the PRODRUG run to be the same as in the topology file Thus copy all lines within the box titled polar aromatic hydrogens and save them in a file named ethanol gro Now scroll down to the section The GROMACS topology Fig 4 6 copy the contents and save in a file named ethanol itp Now you have all data for performing simulations including ethanol with GROMACS In the following box a summary of all steps for generating a GROMACS coordinate and topology file is given 34 4 Construction of Ligands The GROMACS topology This file vas generated by PRODRG version AA081006 0504 PRODRG vritten copyrighted by Daan van Aaiten and Alexander Schuette kopf Questions comments to davafBdavapcl bioch dundee ac uk Vhen using this software publication cite A V Sechuwettelkopf and D M F van Aalten 2004 PRODRG a tool for high throughput crystallography of protein ligand complexes Acta Crystallogr D60 1355 1363 lt w w w w w w w w w w w w w w moleculetype Name nrexcl LIG 3 atoms 4 nr type resnr resid atom cgnr charge mans 1 cm 1 Lio 1 0 074 15 0350 2 1 6 i 1 0 091 14 0270 3 OA 1 LIG o2 1 0 202 15 9994 4 H 1 LIG g2 1 0 037 1 0080 bonds ai a fu ee 2 1 2 0 153 7150000 0 0 153 7150000 0 ci 2 97 2 0 143 8180000 0 0 143 8180000 0
37. After completion of the genbox command you should visualize your solvated system here rec lipid sol gro with an appropriate software like vmd http www ks uiuc edu Research vmd If your system looks like the example Fig 6 1 step 3 all is ok and you can go on with neutralizing your system If your ligand or protein is outward of the water shell you have to center the actual system in the simulation box using the editconf command before performing the solvation process using the file rec 1ipid gro containing the lipid GPCR complex gt editconf f rec lipid gro c o out gro l Rename the file out gro to rec lipid gro with the help of the mv command gt out gro rec lipid gro J Now you may again perform the genbox command as mentioned above If the resulting simulation box looks like the one in Fig 5 13 everything worked well but if it looks like Fig 5 14 the reader is referred to Sect 5 6 After solvation it is recommended to minimize the system using the commands grompp and mdrun grompp f mini c rec lipid sol p system mdrun v s An example parameter file mini mdp read by grompp is presented below i mini mdp Cpp lib cpp define DPOSRES constraints none integrator steep nsteps 1000 Energy minimizing emtol 1000 emstep 0 01 pbc xyz nstcomm 1 62 6 Minimization and Molecular Dynamics nstlist 5 rlist sul nstype grid coulombty
38. Considerations 95 0 99 55 31 0 995 56 47 1 00 57 90 In this case you cannot use the command shown above Here you have two alter natives First you delete all lines except the data lines Or secondly and more elegant gt grep v ethanol sol xvglintegrate What does this command do If you take a closer look onto the file ethanol Sol xvg shown above you see that additionally to the data lines there are lines starting with the symbol or These lines have to be deleted which can be done with the command gt grep v 40 ethanol sol xvg The option v inverts grep s search all lines not containing one of the characters or in the specified pattern at the beginning of the line indicated by will be printed and may be used as input to the command integrate see Chap 11 Additionally calculations of Gibbs energy of solvation can be performed at dif ferent temperatures This allows to calculate enthalpy and entropy of solvation You can do so for example with ethanol in water In Table 7 3 the predicted temperature dependence of the Gibbs energy of solvation of ethanol in water is shown Table 7 3 Predicted values KJ mol for the Gibbs energy of T F solvation AG at different 283 21 140 3 temperatures for ethanol in 288 21 0 0 4 water 293 20 7 0 2 298 20 5 0 4 303 20 5 0 3 For calculation of enthalpy and entropy of solvation the f
39. E2 and this is not the case with regard to the intracellular loop I3 Since the E2 loop is in contact with the binding pocket the E2 loop has to be modelled completely If you look onto different crystal structures with complete E2 loop you can see different conformations Fig 3 11 Thus you have to decide carefully which template is to be used for modelling of the E2 loop A large number of crystal structures are obtainable for the human adrenergic hB receptor But the hB R is a special case There are two disulfide bridges in the E2 loop Fig 3 12 whereas in most others GPCRs there is only one disulfide bridge in the E2 loop connecting the E2 loop with the upper part of the TM A part of the E2 loop of the hB R exhibits a helical structure but this is not the case for all other GPCRs Thus you have to decide carefully if it would be appropriate to use two different template structures for homology modelling one for the E2 loop and one for the remaining parts of the receptor However the E2 loops are widely different in their length thus in most cases the E2 loop cannot be modelled by changing an amino acid side chain of the template into the side chain of the destination Thus you have to use also techniques like loop search For only one loop search the number of amino acids is too long and you would get bad results Thus it is better to use at least one fixed point This is the highly conserved cysteine connecting t
40. F Seeber M de Benedetti PG Fanelli F 2008 Mechanisms ofthe inter and intramolecular communication in GPCRs and G proteins J Am Chem Soc 130 4310 4325 Rasmussen SGF Choi HJ Rosenbaum DM Kobilka TS Thian FS Edwards PC Burghammer M Ratnala VRP Sanishvili R Fischetti RF Schertler GFX Weis WI Kobilka BK 2007 Crystal structure of the human B adrenergic G protein coupled receptor Nature 450 383 387 Rasmussen SG Choi HJ Fung JJ Pardon E Casarosa P Chae PS DeVree BT Rosenbaum DM Thian FS Kobilka TS Schnapp A Konetzi J Sunahara RK Gellman SH Pautsch A Steyaert J Weis WI Kobilka BK 2011 Structure of a nanobody stabilized active state of the B adrenoceptor Nature 469 175 180 214 References Rasmussen SGF DeVree BT Zou Y Kruse AC Chung K Y Kobilka TS Thian FS Chae PS Pardon E Calinski D Mathiesen JM Shah STA Lyons JA Caffrey M Gellman SH Steyaert J Skiniotis G Weis WI Sunahara RK Kobilka BK 2011 Crystal structure of the B adrenergic receptor Gs protein complex Nature 477 549 555 Rosenbaum DM Zhang C Lyons JA Holl R Arago D Arlow DH Rasmussen SGF Choi HJ DevVree BT Sunahara RK Chae PS Gellman SH Dror RO Shaw DE Weis WI Caffrey M Gmeiner P Kobilka BK 2011 Structure and function of an irreversible agonist B adrenoceptor complex Nature 459 236 240 Scheerer P Park JH Hildebrand PW Kim YJ Krau8 N Choe HW Hofmann KP Ernst OP 2008 Crystal structure of opsin in its G
41. GPCRs were mod elled in the gas phase This was a very rigorous approximation because the amino acid side chains pointing outwards of the receptor were not in contact with the na tive surrounding This could lead to incorrect amino acid side chain conformations or to artificial interactions between polar or charged amino acids Additionally if molecular dynamic simulations were performed of a GPCR in the gas phase the secondary and tertiary structure of the receptor was not stable In order to achieve stability constraints had to be put onto the backbone of the protein Thus confor mational changes with regard to the whole receptor could not be observed But with the development of more efficient computers it was possible to simulate GPCRs in their natural surrounding like lipid bilayer including intra and extracellular water Meanwhile it is widespread established to model a GPCR in its natural surrounding 5 1 Structure of Lipids Lipids can be divided into several groups the phosphoglycerides sterols sphin golipids triglycerides and glycolipids Membrane bilayers are mainly constituted by phosphoglycerides A schematic representation of phophoglycerides is given in Fig 5 1 A Strasser H J Wittmann Modelling of GPCRs 37 DOI 10 1007 978 94 007 4596 4 5 Springer Science Business Media Dordrecht 2013 38 5 Lipids Fig 5 1 Structure of phosphoglycerides The phosphoglycerides are established by one glycerol Two
42. In contrast the binding site of peptide and glycoprotein hormone receptors is located between the N terminus the extracellular loops and the upper part of the transmembrane domains Family GPCRs for peptides like calcitonin secretin or parathyroide belong to family B IUPHAR 2000 Harmar 2001 Jacoby et al 2006 see appendix GPCR Families Source http www gpcr org 7tm A characteristic of the family B GPCRs is the long N terminus Fig 2 4 The N terminus of family B GPCRs contains three conserved disulfide bridges Fig 2 4 Besides that the extracellular loop E2 and the upper part of transmembrane domain III are connected by a disulfide bridge Fig 2 4 Typically in family B GPCRs ligands bind between the long N terminus and the extracellular loops Experimental data suggest that family B GPCRs prefer to couple to Ga Hoare SRJ et al 2005 2 3 Activation of GPCRs and Their Interaction with G Proteins 7 Fig 2 3 Schematic N representation of a family A GPCR Fig 2 4 Schematic representation of a family B GPCR T 12 13 Family C Metabotropic glutamate receptors mGluR y aminobutyric acid type B GABAg and calcium sensing receptors CaR for example belong to GPCRs of family C IUPHAR 2000 Jacoby et al 2006 Br uner Osborne et al 2007 For most of the family C GPCRs along N terminus and C terminus is typical as well as a disulfide bridge connecting the extracellular loop E2 with the upper part of TM II
43. MEM mem 48 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 5 Lipids e s PROT prot e s OUT Sout gt S out tcl if status then echo Error creating Tcl script file S out tcl Terminating exit 1 endif Starting Tcl script from working directory chmod u x S out tcl vmd e out tcl dispdev text if status then echo out tcl failed Terminating calculations exit 1 endif echo Output files out pdb and out psf successfully created echo Going to convert pdb format to gro format Removing obsolete files pdb and psf files of membrane and protein tcl script file output psf file rm S mem pdb psf prot pdb psf S out tcl S out psf Extracting protein and membrane structures from out pdb file deleting all water molecules grep POPC out pdb mem pdb grep v TIP POPC S out pdb grep ATOM sed e s HSD HIS gt S prot pdb rm out pdb Converting pdb file for protein and possibly change protonation state 5 5 Embedding a GPCR into a Lipid Bilayer 49 94 95 96 echo WA Ac k k Ck ck K k k Ck k k k k kk k kk ck k ko ck ck ko k Ck ko k Ck ko ck ko ko K ko lt kx X ck k k k ck k ck ko k k ck ck k k ko ck lt x k ck k k Ck ko lt Ck ck ck ck k k Ck ko lt k ko k ko
44. Merck molecular force field I Basis form scope parameterization and performance of MMFF94 J Comput Chem 17 490 519 Hanson MA Cherezov V Griffith MT Roth CB Jaakola VP Chien YET Velasquez J Kuhn P Stevens RC 2008 A specific cholesterol binding site is established by the 2 8 structure of the human B adrenergic receptor Structure 16 897 905 Harmar AJ 2001 Family B G protein coupled receptors Genome Biology 2 REVIEWS2012 Henin J Maigret B Tarek M Escrieut C Fourmy D Chipot C 2006 Probing a model of a GPCR ligand complex in an explicit membrane environment the human cholecystokinin 1 receptor Biophys J 90 1232 1240 Herrmann R Heck M Henklein P Henklein P Kleuss C Hofmann KP Ernst OP 2004 Sequence of interactions in receptor G protein coupling J Biol Chem 279 24283 24290 Herrmann R Heck M Henklein P Hofmann KP Ernst OP 2006 Signal transfer from GPCRs to G proteins role of the Ga N terminal region in rhodopsin transducin coupling J Biol Chem 281 30234 30241 Hoare SRJ 2005 Mechanisms of peptide and nonpeptide ligand binding to class B G protein coupled receptors Drug Discov Today 10 417 427 Igel P Geyer R Strasser A Dove S Seifert R Buschauer A 2009 Synthesis and structure activity relationships of cyanoguanidine type and structurally related histamine H4 receptor agonists J Med Chem 52 6297 6313 Isralewitz B Izrailev S Schulten K 1997 Binding pathway of retinal to bacterio opsin a pr
45. Theoretical study on receptor G protein recognition new insights into the mechanism of the 1 b adrenergic receptor activation Int J Quant Chem 73 71 83 Filizola M Wang SX Weinstein H 2006 Dynamic models of G protein coupled receptor dimmers indications of asymmetry in the rhodopsin dimer from molecular dynamics simulations in a POPC bilayer J Comput Aided Mol Des 20 405 416 Fleishmann SJ Ben Tal N 2006 Progress in structure prediction of a helical membrane proteins Curr Opin Struct Biol 16 496 504 Fredriksson R Lagerstr m MC Lundin LG Schi th HB 2003 The G protein coupled receptors in the human genome form five main families Phylogenetic analysis paralogon groups and fingerprints Mol Pharmacol 63 1256 1272 Frenkel D Smit B 2002 Understanding molecular simulation from algorithms to applications Academic Press San Diego References 211 Gales C van Durm JJJ Schaak S Pontier S Percheranchier Y Audet M Paris H Bouvier M 2006 Probing the activation promoted structural rearrangements in preassembled receptor G protein complexes Nat Struct Mol Biol 13 778 786 Ganjiwale AD Rao GS Cowsik SM 2011 Molecular modeling of neurokinin B and tachykinin NK3 receptor complex J Chem Inf Model 51 2932 2938 Gascon JA Leung SSF Batista ER Batista VS 2006 A self consistent space domain decompo sition method for QM MM computations of protein electrostatic potentials J Chem Theory Comput 2 175 186 Gedeck P Lewis RA
46. and may take some time If the www allitebooks com 5 5 Embedding a GPCR into a Lipid Bilayer 45 alignment procedure is finished the protein with the new coordinates has to be saved as pdb and psf file in the following manner Use the menu but tons Extensions Modelling Automatic PSF Builder and a new window opens Step 1 In the field Output basename we write protein autopsf for example and click onto the button Load input files Step 2 Choose Everything and click onto Guess and split chains using current selections Step 3 Click onto Create chains Step 4 Click onto Apply patches and finish PSF PDB An additional window opens there click OK and finish by clicking onto the button Reset Autopsf If you look into the directory where vmd is started from three new files protein autopsf log protein autopsf pdb and protein autopsf psf generated by the procedure mentioned above Now vmd can be closed and the shell script vmd2gro can be startet gt vmd2gro Subsequently you have to define some basenames of files gt Basename of membrane file membrane gt Basename of aligned protein file protein_autopsf gt Basename of output file protein membrane temp The first two basenames have to be the same as used in the alignment procedure mentioned above The third can have any basename since these will be temporary files which will be deleted automatically Aft
47. at protein data bank http www pdb o mutation no information at protein data bank http www pdb org Ligand UniProtKB 02699 literature Choe et al 2011 Appendix 179 human B adrenergic receptor method X ray diffraction 240 p adrenergic receptor T4 lysozyme chimera no information at protein data bank http www pdb org mutation NIS7E 54 C97A TA H ligand HN Oy P N Y P07550 Cherezov et al 2007 method X ray diffraction 340 molecule p adrenergic receptor no information at protein data bank http www pdb org mutation no information at protein data bank http www pdb org without ligand UniProtKB P07550 literature Rasmussen et al 2007 180 Appendix method X ray diffraction molecule p adrenergic receptor fragment no information at protein data bank http www pdb org no information at protein data bank http www pdb org mutation eraen Rea I I O PTZ p adrenergic receptor T4 lysozyme chimera no information at protein data bank http www pdb org mutation E122W NI87E 1054 C1097A ligand HO UniProtKB P07550 P00720 literature Hanson et al 2008 Appendix pdb code UniProtKB pdb code resolution molecule UniProtKB 181 3NYA X ray diffraction 3 16 p adrenergic receptor lysozyme chimeric protein of B adrenocepto
48. can be calculated by appropriate MD simulations as shown later Subsequently the Gibbs energy of solvation of ethanol in water AG EtOH can be estimated via AG EtOH AG AG 7 45 sol In the following the atoms section of ethanol itp with the additional column is presented atoms nr type resnr resid atom cgnr charge mass 1 CH3 1 DRG CAA 1 0 000 15 0350 DUM 0 0 15 0350 2 CH2 1 DRG 1 0 266 14 0270 DUM 0 0 14 0270 3 OA il DRG OAB 1 0 674 15 9994 DUM 0 0 15 9994 4 HO T DRG HAA 1 0 408 1 0080 DUM 0 0 1 0080 Save this file as ethanol itp Minimize the ethanol and save the resulting file as ethanol gas gro Solvate the minimized ethanol with an appropriate number of water molecules using the GROMACS commands edi tconf to center the solvent in the simulation box and genbox for solvation Minimize the box and save the file as ethanol sol gro Now can start the simulation to calculate the Gibbs en ergy of solvation Therefore you would have to start a distinct number of subsequent molecular dynamic simulations for discrete values of Thereby it should be taken into account to perform the calculations at least at eighteen values for for example 0 0 0 05 0 1 0 2 0 3 0 4 0 45 0 5 0 55 0 6 0 7 0 8 0 9 0 95 0 975 0 99 0 995 and 1 0 In general a AX of 0 1 can be used But to avoid singularities around 0 0 5 and 1 at these regions smaller AA are recommended as shown above It
49. comprehensively obtained from genome sequences Pharmaceutical 4 652 664 Taylor MS Fung HK Rajgaria R Filizola M Weinstein H Floudas CA 2008 Mutations affecting the oligomerization interface of G protein couple receptors revealed by a novel de novo protein design framework Biophys J 94 2470 2481 References 215 Teller DC Okada T Behnke CA Palczewski K Stenkamp R 2001 Advance in determination of a high resolution three dimensional structure of rhodopsin a model of G protein coupled receptors GPCRs Biochemistry 40 7761 7772 Theodoropoulou M Bagos PG Spyropoulos IC Hamodrakas SJ 2008 gpDB a database of GPCRs G proteins effectors and their interactions Bioinformatics 24 1471 1472 Tolkovsky AM Levitzki A 1978 Mode of coupling between the b adrenergic receptor and adenylate cyclase in turkey erythrocytes Biochemistry 17 3795 3810 Torres FE Recht MI Coyle JE Bruce RH Williams G 2010 Higher throughput calorimetry opportunities approaches and challenges Curr Opin Struct Biol 20 598 605 Van Der Spoel D Lindahl E Hess B van Buuren AR Apol E Meulenhoff PJ Tieleman DP Sijbers ALTM Feenstra KA van Drunen R Berendsen HJC 2005 Gromacs User Manual version 4 0 http www gromacs org Vauquelin G von Mentzer B 2007 G Protein coupled receptors Wiley Blackwell Wiley Villa A Mark AE 2002 Calculation of the free energy of solvation for neutral analogs of amino acid side chains J Comput Chem 23 548 553 Vr
50. coupled receptor oligomerization knowledge base BMC Bioinformatics 8 177 Stewart JJP 1989 Optimization of parameters for semiempirical methods II Applications J Comput Chem 10 221 264 Stewart JJP 2004 Optimization of parameters for semiempirical methods IV extension of MNDO AMI and PM3 to more main group elements J Mol Model 10 155 164 Strasser A Wittmann HJ 20074 LigPath a module for predictive calculation of a ligands pathway into a receptor application to the gpH receptor J Mol Model 13 209 218 Strasser A Wittmann HJ 2007b Analysis of the activation mechanism of the guinea pig histamine H receptor J Comput Aided Mol Des 21 499 509 Strasser A Wittmann HJ 2010 In silico analysis of the histaprodifen induced pathway of the guinea pig histamine receptor J Comput Aided Mol Des 24 759 769 Strasser A Wittmann HJ 20104 3D QSAR CoMFA study to predict orientation of suprahistaprod ifens and phenoprodifens in the binding pocket of four histamine H receptor species Mol Inf 29 333 341 Strasser Wittmann HJ 20100 Distinct interactions between the human adrenergic B receptor and an in silico study J Mol Model 16 1307 1318 Strasser A Wittmann HJ in press hB R Go complex prediction versus crystal structure how valuable are predictions based on molecular modelling studies J Mol Model in press Suwa M Sugiharar M Ono Y 2011 Functional and structural overview of G protein coupled receptors
51. half of the cubic box length To get insight into the consequences for different values of the cut off distance we will analyze the total kinetic and potential energy of a system containing molecule of ethanol and 3 000 molecules of water at 1 bar and 298 15 K For this we do three independent runs of a 1 000 ps MD simulation and calculate the mean of these energies over a time interval from 500 ps to 1 000 ps with the help of the GROMACS command energy The result may look like given in Table 7 1 We see that the results corresponding to the first cut off value differ considerably from that of run 2 and 3 which exhibit nearly the same results with respect to the computational error A 1 000 ps MD simulation with 3 000 water molecules and one molecule of ethanol using a twin range cut off between 0 8 and 1 4 nm Villa and Mark 2002 exhibits a kinetic energy of 33 975 kJ mol and a potential energy of 130 183 kJ mol Both values are different to the values given in Table 7 1 and reflect the importance of the simulation conditions 7 2 2 Example 2 Ligand Receptor Complex and Affinity Conceptual Considerations Now let us apply the concept discussed so far to evaluate the equilibrium constant according to Eq 7 3 To do so we must have knowledge about the reference chemical potentials according to Eq 7 11 To elucidate the application of coupling parameters let us have a look on the system state 1 consisting of nz moles of ligand molec
52. information about the type Thus the command gt head n 467 protein3 top tail n 461 tr s cut d 2 6 70 6 Minimization and Molecular Dynamics would lead to the following output only the first seven lines are shown N CA CB C N CA Fa Now we have to look for all lines containing the sites which should be administered with position restraints In our case this is C O N and H This can be achieved by combining the command explained above with a corresponding grep command as shown below gt head n 467 protein3 top tail n 461 tr s cut d f2 6 grep This command leads to the following output only the first ten lines are shown 7 C Please compare the option of grep with the options which were used when dealing the same problem with the gro file In the gro file the search string could be defined as C This means that grep searched all lines containing a C with a blank before and after the C But in the actual case one has to be aware that there is a blank before the C but there is no blank after the C because the line ends with a new line Thus if one searches for all lines with C but also with CA and CB for example were found In order to avoid this a new search criterion has to be found This might be Look for all lines containing a C at the end of a line and with a blank before the C The be achieved by grep
53. long chain fatty acids are esterified to the carbons C1 and C2 of the glycerol The fatty acids are carboxylic acids with about 12 20 carbon atoms A phosphoric acid is esterified to C3 of the glycerol and an alcohol to the phosphate Due to their chemical structure phosphoglycerides are amphiphilic The head groups are hydrophilic whereas the long fatty acids show hydrophobic properties In biological systems a large variety of phosphoglycerids is found since there is a high variability with regard to the alcoholic group and the fatty acids The name of the phosphoglycerides is based on the alcoholic head groups Phosphatidic acid PA no head group i e POPA Phosphatidylcholine PC i e POPC Phosphatidylethanolamine PE i e POPE Phosphatidylglycerol PG i e POPG Phosphatidylinositol PI Phosphatidylserine PS i e POPS The PO in the lipids mentioned above is the abbreviation for 1 palmitoyl 2 oleol For MD simulations GPCRs are mainly embedded into POPC lipid bilayers Ivanov et al 2005 Filizola et al 2006 Henin et al 2006 Strasser et al 2007 The structure 5 2 Structure of the Phospholipid Bilayer 39 of POPC is presented in Fig 5 2 However other lipid models like DOPC dioleoylphosphatidylcholine are used Goetz et al 2011 Fig 5 2 Structure of POPC 1 palmitoyl 2 oleoylphosphatidylcholine Sterols are another important class of membrane lipids One of the most prominent 15 the choleste
54. name begins with a period or contains a slash the meta character does not affect them In this example we used the special character to efficiently address the contents of the current working directory 1s al The behaviour of the shell is as follows The character is substituted by all entries of the working directory and afterwards the shell executes the command Now lets have a look on the directory data located in usr project with a couple of files dati data old data save datl new dat2 new dat3 new dat3 old geo new Assume a user might want to move the files named data old and data save to a directory usr new project Making use of the meta character the command would look like this gt mv usr project data data usr project new Thus the character substitutes an arbitrary string including the null string Another special character matches exactly one character so the command gt mv usr project data dat new usr project would move the files dat1 new dat2 new and dat3 new to the directory usr project The notation gt mv usr project data dat 13 usr project moves the files 1 dat3 new and dat3 old to the directory usr project Thus an enumeration of characters enclosed in square brack ets will match a single character out of this enumeration An extension of the meta character is given by the pattern The meta notation dat1 geo ne
55. particular UNIX command possibly completed by options which control its execution or output The item objects indicate files A Strasser H J Wittmann Modelling of GPCRs 139 DOI 10 1007 978 94 007 4596 4_11 Springer Science Business Media Dordrecht 2013 140 11 Important UNIX LINUX Commands and or directories Note that all parts of the command line must be separated by at least one white space character e g a blank In the following sections each command line is introduced by the so called shell prompt indicated by the character gt The ENTER key specifying the end of the command is given by the symbol To find out the contents of a directory named dir located in the working directory one would us the command 1s 515 dir 24 which generally brings up a very poor listing whereas the command gt 1s al dir prints out an extensive list of objects including a lot of its properties caused by the option 1 which is indicated by a hyphen Shell commands may be combined with the symbol to form a pipleline for instance gt echo abc tr a z A Z J will translate all lower case characters of the string abc into upper case characters will say the output of the command on the left hand side of the pipe symbol is used as input for the command on the right hand side for a description of tx refer to the following section An arbitrary number of commands may be comb
56. protein aligned pdb coordpdb PROT pdb can delete some protein segments list them in brackets on next line set pseg2del foreach seg pseg2del delatom seg write temporary structure set temp temp writepsf temp psf writepdb temp pdb reload full structure do NOT resetpsf mol load psf temp psf pdb Stemp pdb select and delete lipids that overlap protein any atom to any atom distance under 0 8A alternative heavy atom to heavy atom distance under 1 3A set sellip atomselect top resname POPC set lseglist lsort unique sellip get segid foreach lseg 1seglist find lipid backbone atoms set selover atomselect top segid 1seg and within 0 8 of protein delete these residues set resover lsort unique selover get resid foreach res resover 243 delatom 1seg res 5 5 Embedding a GPCR into a Lipid Bilayer 53 244 245 246 247 248 249 j j delete lipids that stick into gaps in protein foreach res 1 delatom LIP1 res foreach res delatom S LIP2 res 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 24 1 272 273 274 275 276 delete lipids that fall out of the PBC box the following numbers are for example only yours are different set xmin 55 set xmax 41 set ymin 51 set ymax 34 foreach lseg LIP1 LIP2 find lipi
57. protein interacting conformation Nature 455 497 502 Schuettelkopf AW van Aalten DMF 2004 PRODRG a tool for high throughput crystallography of protein ligand complexes Acta Crystallogr D60 1355 1363 Scior T Medina Franco JL Do QT Martinez Mayorga K Yunes Rojas JA Bernard P 2009 How to recognize and workaround pitfalls in QSAR studies a critical review Curr Med Chem 16 4297 4313 Scott WRP Huenenberger PH Tironi IG Mark SR Fennen 1 Torda AE Huber Krueger P van Gunsteren WF 1999 The GROMOS biomolecular simulation program package J Phys Chem A 103 3596 3607 Shimamura T Shiroishi M Weyand S Tsuhimoto H Winter G Katritch V Abagyan R Cherezov V Liu W Han GW Kobayashi T Stevens RC Iwata S 2011 Structure of the human histamine Hi receptor complex with doxepin Nature 475 65 70 Silberg RJ Alberty RA Bawendi MG 2005 Physical chemistry 4th edn Wiley New York Silva ME Heim R Strasser A Elz S Dove S 2011 Theoretical studies on the interaction of partial agonists with the 5 HT2A receptor J Comput Aided Mol Des 25 51 66 Simpson LM Taddese B Wall ID Reynolds CA 2010 Bioinformatics and molecular modelling approaches to GPCR oligomerization Curr Opin Pharmacol 10 30 37 Skrabanek L Murcia M Bouvier M Devi L George SR Lohse MJ Milligan G Neubig R Palczewski K Parmentier M Pin JP Vriend G Javitch JA Campagne F Filizol M 2007 Requirements and ontology for a G protein
58. proteins BOSS Taste receptors T1R Class D fungal pheromone Fungal pheromone A factor like STE2 STE3 Fungal pheromone B like BAR BBR RCB PRA Fungal pheromone M and P factor Class E cAMP receptors Listing of Biogenic Amine Receptors Muscarinic acetylcholine Adrenoceptors Alpha adrenoceptors Ola Od Beta adrenoceptors Appendix 169 Serotonin receptors 5 HT 5 HTp SAE 5 HT 1 5 HTie 5 HTif 5 HT gt 5 5 HT gt 5 HTy 5 HT5a 5 HTs 5 HTs 5 Parameters Source http moose bio ucalgary ca index php page Structures and Topologies The file popc itp available at the internet source mentioned above is shown below Please note that the identifier for the residue POPC is changed to POP in the related example of Chap 5 The types of the sites within this file are defined in lipid itp also available at the same internet source 170 moleculetype Name nrexcl POPC 3 atoms nr type resnr mass 1 LC3 1 15 0350 qtot 0 36 2 LC3 1 15 0350 qtot 0 72 3 LC3 1 15 0350 qtot 1 08 4 LNL 1 14 0067 qtot 0 76 5 LH2 1 14 0270 qtot 1 0 6 LC2 1 14 0270 qtot 1 0 7 LOS 1 15 9994 qtot 0 54 8 LP 1 30 9738 qtot 2 3 9 LOM 1 15 9994 qtot 1 5 10 LOM 1 15 9994 qtot 0 7 11 LOS 1 15 9994 qtot 0 12 LC2 1 14 0270 qtot 0 08
59. receptor whereas partial agonists stabilize the active conformation of a receptor Thus it can be suggested that during the binding process of the partial agonist the receptor has to change its conformation In general for the binding process of a partial agonist several pathways as illustrated in Fig 8 7 have to be taken into account Fig 8 7 Scheme for different L R LR ligand binding and 1a receptor activation pathways Copyright by Springer with permission from Springer 3 2a 1b L R 2b LR The binding of an antagonist or inverse agonist L to the receptor is illustrated by pathway 14 of Fig 8 7 After binding the inactive ligand receptor complex LR is established For binding of a partial agonist three different pathways have to be taken into account e Pathway la amp 1b The partial agonist L binds to the inactive state of the receptor R and establishes the inactive ligand receptor complex LR Subsequently the in active ligand receptor complex LR changes its conformation into the active ligand receptor complex LR Pathway 2a amp 2b The inactive receptor R changes its conformation into the active state R without binding of a ligand This phenomena is called constitutive activity Subsequently the partial agonist L binds to the already activated receptor R and the active ligand receptor complex LR is established Pathways 3 The partial agonis
60. sequences have to be obtained 3 3 1 Amino Acid Sequences Where to Get From There are several sources for amino acid sequences present in the internet One prominent is for example the Expasy Proteomics Server http expasy org Fig 3 7 Exercise Start your internet browser and open the site http expasy org Now choose UniProtKB under the section query Then you can type your search string into the field on the right Now we want to search for the human adrenergic B receptor There different possibilities for the search string For example type adrenergic and click the Search button Now more than 900 results related to adrenergic are presented Scroll until the receptor of your choice is listed In our case it is the human adrenergic receptor with the accession code 07550 If you want to reduce the number of hits the search string has to be defined more exactly Please try beta adrenergic receptor beta 2 adrenergic receptor and beta 2 adrenergic receptor human By defining the search string more exactly the number of hits can be significantly reduced and it is easier for you to find the hit you are searching for Now click onto the corresponding entry with the accession code 07550 and you get a lot of very useful information about this receptor including the amino acid sequence In the section Regions the amino acids related with the N terminus C term
61. simple model the behaviour of an antagonist will be de scribed successfully But in the case of an agonist the receptor is expected to be activated for inducing further intracellular signalling processes So the presented model summarizes the formation of a ligand receptor complex and the effect of the receptor activation resulting in the question whether the denoted complex formation will be described by one chemical equilibrium or it might be necessary to formulate a consecutive two step mechanism like R R 10 2 A Strasser H J Wittmann Modelling of GPCRs 131 DOI 10 1007 978 94 007 4596 4_10 Springer Science Business Media Dordrecht 2013 132 10 Thermodynamics of Ligand Receptor Interaction L R LR 10 3 where R denotes the activated receptor Because it is an experimentally difficult task to distinguish between reaction 10 1 on the one hand and the reaction system 10 2 and 10 3 on the other hand we will make the assumption that the Eq 10 1 is also valid in the case of an agonist where the process reads L R LR 10 4 implying the receptor activation during the formation of the ligand receptor complex 10 3 Thermodynamic Basics To understand the behaviour of antagonists and with respect to the activation process agonists it is necessary to discuss the formation of the ligand receptor complex on a quantitative level According to the first and second law of thermodynamics the chemical behaviour of
62. solvation process the water molecules are put somehow of course in the correct density around the lipid GPCR complex But again the interactions between the water molecules on the one hand and more importantly between the water molecules and the GPCR are not established This means for example no hydrogen bonds are established If you start a molecular dynamic simulation without equilibration the GPCR may be destroyed i e for example the helical conformation of the GPCR 6 4 Molecular Dynamic Simulation of your System 63 is not stable In this case your simulation results are wrong In the equilibration phase the surrounding of the GPCR the lipid bilayer and the water should be equilibrated around the GPCR without modifying the structure of the GPCR This can be done by putting position constraints onto the GPCR Position restraints were already introduced in context with the minimization of the system But it has to be taken into account that in context with molecular dynamics distinct equilibration protocols should be used in order to perform a successful and well equilibration At the beginning of the equilibration phase a rather high force constant k is to be used but during equilibration the force constant should be decreased gradually until a force constant of 0 is attained Fig 6 2 Fig 6 2 Two different 1 equilibration protocols for disadvantageous MD simulation equilibration protocol
63. van der Spoel et al 2005 Kukol 2010 9 1 The Force Field Energy The potential energy of a system also called force field energy is given in Eq 9 1 Err Ebona F Eangle Ee F 9 1 Therein Ebona describes the energy function for stretching a bond between to atoms is the energy function describing the bending of an angle between three atoms The torsional energy is given by and describes the energy for rotation around a bond and represent the non bonded van der Waals and electrostatic interactions The coupling between the stretching bending and torsional energy is described by the cross term 9 1 1 The Stretching Energy The stretching energy represents the energy function for stretching a bond between two atoms Fig 9 1 This energy can be described by Eq 9 2 Epona KAB r 9 2 A Strasser H J Wittmann Modelling of GPCRs 121 DOI 10 1007 978 94 007 4596 4_9 Springer Science Business Media Dordrecht 2013 122 9 Force Fields Fig 9 1 Definition of a bond Fig 9 2 Definition of the angle yan reference distance between both atoms A and B r actual distance between the atoms A and B k P force constant for the bond between A and B Besides this simple equation some other equations to describe the stretching energy are used in literature Because of computational efficacy in the GROMOS 96 force field van Gunsteren et a
64. will be calculated with the help of MD coupling parameter concept and so requires to set up an appropriate system In the framework of GROMACS MD simulations the quantity mole may be replaced by particle numbers Thus one mole of some species means one particle of the species in the simulation To set up the system one would choose one molecule of ethanol firstly to fulfil the requirement of neglecting the formerly discussed interactions and secondly to have the desired term 47 95 Ugoy isolated on the right hand side of Eq 7 28 The next problem is the choice of the quantity ng o Of course one could try to use a number of water molecules in such a way that the two concentration terms on the right hand side of Eq 7 28 would cancel RT n Z npon PO pug 1 29 Co 1 mol nmo The calculated difference G 1 G 2 equals the Gibbs energy of solvation in this case The concentration term cg og may be written approximately as 2 ru 7 30 a where the symbols and denote the molar masses of the solute and the solvent means the density of water and will be substituted in the case of dilute solution by 1 kg l Taking into account 1 mol we get an equation for estimating nmo Which after solving numerically exhibits the result of 18 water molecules However for a simulation with periodic boundary conditions the system comprised of 19 molecules
65. will be too small So the question arises how many water molecules to use and how to treat the concentration terms in Eq 7 28 To set 82 7 Calculation of Gibbs Energy of Solvation up a system large enough for an exact simulation the box size should be as large as possible i e is much larger than ngon Will be approximately one and the term In xg o will reach zero But if we choose ngog 1 mol and calculate the term 7g o RT In xg o for several numbers of water molecules we would conjecture the limiting value RT So what is the correct result As we demand a large number of solvent particles we already see that the logarithm of the mole fraction of the solvent reaches the value zero but this term is multiplied by the itself On the one hand we have a term approaching zero but on the other hand we have a term getting larger and larger To achieve the correct result of this product we have to use the so called rule of Hospital which tells us that the limiting value of the expression will be RT If we choose Nmo 512 we get xmo 0 998051 and nmo RT 2 476 kJ per mol ethanol For Nz o 3 000 xmo 0 999667 and nj o0 RT In xmo 2 477 kJ per mole ethanol which is close to the limiting value RT 2 479 kJ per mole ethanol at a temperature of 298 15 K So a choice of the number of solvent molecules between 512 and 3 000 or higher will lead to a constant term of approximately RT i
66. you can start to calculate the Gibbs energy of solvation of a ligand in the binding pocket of a GPCR you have to dock the interesting ligand into the binding pocket and perform molecular dynamic simulations as described in the corresponding Chap 6 in order to obtain a stable ligand receptor complex During the thermodynamic cycle the interaction between the ligand and the surrounding is switched off In case of a homogeneous surrounding like water or another solvens 100 7 Calculation of Gibbs Energy of Solvation Fig 7 8 Thermodyamic AG cycle for ligand receptor d interaction with mutation of aq R LR the ligand Henin et al 2006 A Gi AG Rmt LRmut aq this does not matter But in case of a specific location of the ligand in the binding mode this might lead to problems Due to the decreasing interaction between ligand and receptor the ligand may be able to wander around somewhere in the simulation box Consequently the wrong surrounding will be included into the calculation Thus it will be very useful in a lot of cases to put slight position constraints onto the ligand after equilibration in the binding pocket via MD simulation with full interaction Example 2 1 Within a study addressing the human cholecystokinin 1 receptor free energy calculations were used to compare predicted changes in Gibbs energy of binding with respect to mutation of the ligand Henin et al 2006 For this purpose the au
67. 1 Fig 7 10 Correlation 25 between the predicted changes in Gibbs energy of 27 solvation for the transfer of phenylhistamine derivatives from the aqueous phase into the binding pocket of hH4R Wittmann et al 2011 copyright by Springer with permission from Springer kJ mol e 37 40 4 5 5 0 5 5 6 0 6 5 7 0 pK Table 7 9 Affinities pK pK values of three selected p S v n T O compounds at hHiR at room LI 6 77 0 05 temperature Wagner L2 8 15 0 10 et al 2011 L3 R S 6 67 0 09 to use the A AG value for transfer of ligand from aqueous phase into the binding pocket because this is exactly the process which is experimentally determined Furthermore one should take into account that there might be systems where only using will lead to a well correlation Example 2 3 A procedure analogue to example 2 2 just above was performed within another study addressing the histamine H receptor Wagner et al 2011 Within this study the affinities of selected ligands Fig 7 11 to human histamine Hi receptor were determined Table 7 9 Having a look onto the Table 7 9 the affinity of ligand L2 compared to those of ligand L1 and L3 is significantly higher The corresponding values of the Gibbs energy for the ligand receptor binding process AAG L wat hH R from 7 2 Examples Conceptual and Practical Considerations 103 bi H4CO A UU N bs N P TX
68. 10 27 and 10 28 yields AH T AH T AC T 10 30 AS T AS T In 10 31 Substituting these results into Eq 10 18 we arrive at AH T ACT T T AC ln z RT InK 10 32 Having determined the association constant K at various temperatures T a linear least square fit algorithm enables us to calculate A H 45 and AC at the temperature which is commonly defined as 298 15 K 138 10 Thermodynamics of Ligand Receptor Interaction 10 5 Special Topics Within this section we will discuss the possibility that a ligand is able to bind in more distinct orientations inside the receptor Strasser et al 20104 For the sake of simplicity we will restrict our considerations on the case of two different orientations and consequently have to define two association processes L R LRI 10 33 and L R LR2 10 34 where L and R on the left hand sides of the Eqs 10 33 and 10 34 correspond to exactly the same compounds whereas LR1 and LR2 denote two distinct ligand receptor com plexes Making use of the assumptions within this chapter the equilibrium constants for these reactions are given in accordance to Eq 10 16 by CLR1Co kec 10 35 CLRI CLR2 and CLR2C K i zpen 10 36 Cr Cg CLR1 CLR2 Appropriate experimental techniques enable us to determine the concentration of exactly one complex LR But the same methods applied onto the case of t
69. 107ASP CB 1007 4 189 4 061 4 099 107ASP CG 1008 4 087 4 049 3 985 107ASP OD1 1009 3 966 4 060 4 014 107ASP OD2 1010 4 129 4 009 3 874 107ASP C 1011 4 095 4 247 4 244 107ASP O 1012 4 024 4 344 4 216 A GROMACS position restraint file starts with the keyword position restraints followed by several lines Each line corresponds to one site and contains five columns First column Number of the site numbering according to the topology file Second column function type Third column force constant on the x coordinate kJ mol nm Fourth column force constant on the y coordinate kJ mol nm Fifth column force constant on the z coordinate kJ mol Thus at first the number of the sites which should be administered with position constraints has to be determined The gro file which should be analyzed is named protein gro forexample The numbers of the sites administering with position restraints should be written into the file site dat gt C protein gro cut c 16 21 site dat gt O protein gro cut c 16 21 gt gt site dat gt N protein gro cut c 16 21 gt gt site dat grep protein gro cut c 16 21 gt gt site dat What does this sequence do The command grep C protein gro for example looks for all lines in the file protein gro which contain the string C like shown below 105SER 993 4 477 4 182 4 529
70. 1100 03 0 46020 03 1 4 2 1 0 10950 03 0 33470 03 2 4 3 1 0 10950 03 0 33470 03 3 4 1 1 0 10950E 03 0 33470E 03 1 4 5 1 0 10950E 03 0 37660E 03 2 4 5 1 0 10950E 03 0 37660E 03 3 4 5 1 0 10950E 03 0 37660E 03 dihedrals ai aj ak al funct phi0 cp mult 1 4 5 6 1 0 0 3 76 3 4 5 6 7 1 0 0 5 85 3 5 6 7 8 1 0 0 3 76 3 6 7 8 11 T 0 0 1 05 3 6 7 8 11 1 0 0 3 14 2 9 8 11 12 1 0 0 1 05 3 7 8 11 12 1 0 0 3 14 2 8 11 12 13 1 0 0 3 76 3 11 12 13 14 1 0 0 2 09 2 11 42 13 32 1 0 0 5 85 3 11 12 13 32 1 0 0 0 42 2 12 13 32 33 1 0 0 5 85 3 12 13 32 33 1 0 0 0 42 2 12 13 14 15 1 0 0 SOT 3 13 32 33 34 1 0 0 3 76 3 I3 14 15 17 1 180 0 16 74 2 14 13 32 33 1 0 0 2 09 2 14 15 17 18 1 0 0 0 42 6 15 17 18 19 1 0 0 5 86 3 17 18 19 20 3 18 19 20 21 3 19 20 21 22 3 20 21 22 23 3 21 22 23 24 3 22 23 24 25 10 000 5 858 3 dihedrals 81 ifdef POSRES_LIPID aj ak 14 14 33 24 O Q Q QQ QQ QQ Q Q Q Q Q QQ F2 P P Q QQ C QQ QQ C P ES include lipid posre itp endif 0 000 12 16 35 26 115 5 858 3 3 76 16 74 2 0 42 6 5 86 3 2 35 264 0 33470 03 2 0 00000 00 0 16740 03 2 0 00000 00 0 16740 03 2 0 000 167 360 176 Appendix Important Crystal Structures of GPCRs Source http www pdb org bovine rhodopsin fragment no information at protein data bank http www pdb org no information at protein data bank http www pdb org fragment no infor
71. 13 1 13 0190 qtot 0 52 14 105 1 15 9994 qtot 0 14 15 LC 1 12 0110 qtot 0 56 16 LO 1 15 9994 qtot 0 0 17 LP2 1 14 0270 qtot 18 LP2 1 14 0270 qtot 19 LP2 3 14 0270 qtot 20 LP2 1 14 0270 qtot 21 LP2 1 14 0270 qtot 22 LP2 1 14 0270 qtot 23 LP2 1 14 0270 qtot 24 LH1 1 13 0190 qtot 25 1 residu POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC atom C1 C2 03 N4 cs c6 07 P8 09 010 011 C12 C13 014 C15 016 C17 C18 C19 C20 C21 C22 C23 C24 C25 cgnr 0 0 10 11 charge 0 4000 0 4000 0 4000 0 5000 0 3000 0 4000 0 800 1 700 0 800 0 800 0 700 0 400 0 300 0 700 0 7000 0 700 0 0 Appendix Appendix 13 0190 15 0350 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LC2 qtot LOS qtot LC qtot LO qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 qtot LP2 atot LP2 qtot LP2 qtot LP3 qtot LP2 tail2 LP3 tail2 POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC P
72. 160 170 180 YSSVLILAFI SLDRYLAIVH ATNSQRPRKL LAEKVVYVGV WIPALLLTIP DFIFANVSEA 190 200 210 220 230 240 DDRYICDRFY PNDLWVVVFQ FQHIMVGLIL PGIVILSCYC IIISKLSHSK GHQKRKALKT 250 260 270 280 290 300 TVILILAFFA CWLPYYIGIS IDSFILLEII KQGCEFENTV HKWISITEAL AFFHCCLNPI 310 320 330 340 350 LYAFLGAKFK TSAQHALTSV SRGSSLKILS KGKRGGHSSV STESESSSFH SS sequence Isoform 2 P61073 2 length 356 amino acids 10 20 30 40 50 60 MSIPLPLLOI YTSDNYTEEM GSGDYDSMKE PCFREENANF NKIFLPTIYS IIFLTGIVGN 70 80 90 100 110 120 GLVILVMGYQ KKLRSMTDKY RLHLSVADLL FVITLPFWAV DAVANWYFGN FLCKAVHVIY 130 140 150 160 170 180 TVNLYSSVLI LAFISLDRYL AIVHATNSOR PRKLLAEKVV YVGVWIPALL LTIPDFIFAN 190 200 210 220 230 240 VSEADDRYIC DRFYPNDLWV VVFQFQHIMV GLILPGIVIL SCYCIIISKL 5 5 250 260 270 280 290 300 ALKTTVILIL AFFACWLPYY IGISIDSFIL ENTVHKWISI TEALAFFHCC 310 320 330 340 350 LNPILYAFLG AKFKTSAQHA LTSVSRGSSL KILSKGKRGG HSSVSTESES SSFHSS 204 Appendix 412 amino acids N terminus 144 173 TMI 174 198 C1 loop 33 42 199 234 101 120 291 412 10 20 30 40 50 60 MPIMGSSVYI TVELAIAVLA ILGNVLVCWA VWLNSNLQNV TNYFVVSLAA ADIAVGVLAI I 1552 N N 70 80 90 100 110 120 PFAITISTGF CAACHGCLFI ACFVLVLTQS SIFSLLAIAI DRYIAIRIPL RYNGLVTGTR 130 140 150 160 170 180 AKGIIAICWV LSFAIGLTPM LGWNNCGQPK EGKNHSQGCG EGQVACLFED VVPMNYMVYF 190 200 210 220 230 240 NFFACVLVPL LLMLGVYLRI FLAARRQLKQ MESQPLPGER ARSTLQKEVH AAKSLAIIVG
73. 258 kJ mol nm is mentioned for the C and a value of 5 6782 1076 kJ mol nm for the C 12 parameter The Lennard Jones interaction between the CH3 and OA site in dependence of distance r is presented in Fig 9 9 Chapter 10 Thermodynamics of Ligand Receptor Interaction 10 1 Motivation The development of a new drug nowadays spents a lot of time and money starting with the synthesis of the molecule and ending up in the testing process Very often promising compounds built up by for example screening methods fail to exhibit the desirable properties A better understanding of the interaction process for the ligand receptor system may circumvent these problems and may allow to design drug purposeful in future An extensive discussion of thermodynamical concepts presented in this chapter is given in literature Kondepudie et al 1998 Silberg et al 2005 Klotz et al 2008 10 2 Ligand Receptor Model A lot of work has done during the last decades to investigate the interaction between a ligand and its receptor resulting in the proposal of forming a ligand receptor complex as a fundamental step determining the effect of a drug Kenakin 1997 In its simplest form this process will be described as an equilibrium between the ligand located in the extracellular solution the receptor embedded in the cell membrane and the complex where the ligand occupies a binding pocket inside the receptor L R LR 10 1 In the framework of this
74. 29 2 H 1 ALA H1 0 248 1 008 qtot 0 377 3 H 1 ALA H2 1 0 248 1 008 2 qtot 0 625 4 H 1 ALA H3 1 0 248 1 008 0 873 5 CH1 1 ALA CA 2 0 127 13 019 qtot 1 6 CH3 1 ALA CB 2 0 15 035 qtot 1 7 c 1 ALA c 3 0 45 12 011 qtot 1 45 8 1 ALA o 3 0 45 15 9994 qtot 1 9 N 2 PRO N 4 0 14 0067 qtot 1 10 CH1 2 PRO CA 5 0 13 019 qtot 1 11 CH2R 2 PRO CB 5 0 14 027 qtot 1 12 CH2R 2 PRO 6 0 14 027 qtot 1 13 CH2R 2 PRO CD 6 0 14 027 qtot 1 14 c 2 PRO c 7 0 45 12 011 qtot 1 45 15 2 PRO 7 0 45 15 9994 7 qtot 1 16 N 3 GLY N 8 0 31 14 0067 z qtot 0 69 17 H 3 GLY H 8 0 31 1 008 qtot 1 18 CH2 3 GLY CA 9 0 14 027 qtot 1 19 c 3 GLY c 10 0 45 12 011 qtot 1 45 20 3 GLY 10 0 45 15 9994 qtot 1 21 N 4 CYSH N 11 0 31 14 0067 qtot 0 69 22 H 4 CYSH H 11 0 31 1 008 qtot 1 23 CH1 4 CYSH CA 12 0 13 019 qtot 1 24 CH2 4 CYSH CB 13 0 15 14 027 atot 1 15 25 s 4 CYSH 56 13 0 37 32 06 qtot 0 78 26 H 4 CYSH HG 13 0 22 1 008 qtot 1 27 c 4 CYSH c 14 0 45 12 011 qtot 1 45 28 4 CYSH 14 0 45 15 9994 qtot 1 29 N 5 GLY N 15 0 31 14 0067 qtot 0 69 30 H 5 GLY H 15 0 31 1 008 qtot 1 31 CH2 5 GLY 16 0 14 027 qtot 1 32 5 GLY 17 0 45 12 011 qtot 1 45 33 5 GLY 17 0 45 15 9994 qtot 1 34 N 6 ALA N 18 0 31 14 0067 qtot 0 69 35 H 6 ALA H 18 0 31 1 008 qtot 1 36 CH1 6 ALA CA 19 0 13 019 qtot 1 439 52 LEU 193 0 45 12 011 qtot 6 45 440 52 LEU 193 0 45 15 9994 q
75. 3 will yield the following equation G 1 G 4 G 3 nr uir ni RTIn E ngRTIn xs 7 44 C because the terms containing cancel The first expression within parenthesis on the right hand side of Eq 7 44 equals the desired quantity AG in the case of n 1 mol The second and third term represent the corrections analogous to the solvation problem discussed in this chapter Applying the concept of the coupling parameter within the framework of MD simulations we are able to evaluate the equilibrium constant for the association process Eq 7 1 according to Eq 7 24 7 2 3 Example 1 Ethanol in Water Practical Considerations After discussing the theoretical concept in the field of thermodynamics in combina tion with thermodynamic integration method coupling parameter method we will present the calculation of the Gibbs energy of solvation using the software package GROMACS Let us exemplary calculate the Gibbs energy of solvation for ethanol in water Therefore the following steps have to be performed Construct the molecule for which the Gibbs energy of solvation should be calculated and save the coordinates as pdb file Contact the PRODRG Server in order to obtain the GROMACS coordinates as a gro file and the GROMACS topology as a top file see Chap 4 Change the size of the simulation box in an appropriate manner Minimize your molecule in gas phase see Chap
76. 4 residues 230 319 mutation L125W C1054T C1097T fragment ligand UniProtKB P61073 P00720 literature Wu et al 2010 pdb code 3OE6 X ray diffraction molecule C X C chemokine receptor type 4 lysozyme chimera CXCR4 residues 2 228 lysozyme residues 1002 1161 CXCR4 residues 231 325 mutation L125W C1054T C1097T fragment UniProtKB P61073 P00720 literature Wu etal 2010 192 Appendix X ray diffraction molecule C X C chemokine receptor type 4 lysozyme chimera CXCRA residues 2 229 lysozyme residues 1002 1161 CXCR4 residues 231 319 mutation L125W CI054T C1097T fragment ligand UniProtKB P61073 P00720 Wu et al 2010 method X ray X ray diffraction ssi molecule C X C chemokine receptor type 4 lysozyme chimera CXCR4 residues 2 228 lysozyme residues 1002 1161 CXCR4 residues 231 319 fragment UniProtKB P61073 P00720 literature Wu et al 2010 Appendix 193 m method X ray diffraction C X C chemokine receptor type 4 lysozyme chimera CXCR4 residues 2 228 Lysozyme residues 1002 1161 CXCR4 e residues 231 319 L125W T240P C1054T C1097T mutation CrlepepdeCVxis UniProtKB UniProtKB P61073 P00720 Wu et al 2010 194 Appendix human Adenosine A gt receptor pdb code 3EML X ray diffraction resolution 260A molecule human adenosine A gt receptor 4 lysozyme chimera fra
77. 7660E 06 0 33470E 06 0 25100E 06 0 25100E 06 0 37660E 06 0 37660E 06 0 25100E 06 0 25100E 06 0 33470E 06 0 25100E 06 0 33470E 06 0 37660E 06 0 50210E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 41840E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 25100E 06 0 37660E 06 0 50210E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 33470E 06 0 37450E 06 0 37450E 06 0 37450 06 Appendix Appendix pairs OX pair around double bond pair around double bond aj funct 6 i 6 1 6 T 7 1 8 1 9 1 10 11 1 12 1 13 1 12 1 12 1 14 1 32 1 15 1 33 1 16 1 17 1 34 1 18 1 33 1 19 1 32 1 18 1 25 1 27 3 35 36 1 27 1 38 37 1 aj ak funct 5 6 6 7 7 8 8 9 8 10 8 11 11 12 8 10 8 11 8 11 12 13 13 14 13 32 14 15 32 33 13 32 15 16 15 17 17 18 15 17 18 19 19 20 20 21 21 22 22 23 23 24 Hip HH p p pm PpIHBpP HB H dH HB p p mp BP BE Pee Pe ee 0 10950 03 0 10950 03 0 12000 03 0 10960 03 0 10960 03 0 10300 03 0 12000 03 0 12000 03 0 10960 03 0 10960 03 0 11100 03 0 10950 03 0 10950 03 0 12000 03 0 11100 03 0 10950 03 0 12400 03 0 11500 03 0
78. 7700 literature Warne et al 2011 Es adrenergic receptor 188 pdb code ligand UniProtKB pdb code Appendix 2Y01 X ray diffraction 2 60 p adrenergic receptor residues 33 368 yes P07700 Warne et al 2011 2Y02 X ray diffraction 2 60 p adrenergic receptor residues 33 368 yes H OH UniProtKB P07700 literature Warne et al 2011 Appendix 189 pdb code 2Y03 X ray diffraction mt s p adrener residues 33 receptor rgic 5 3 ligand P07700 Warne et al 2011 2Y04 method X ray diffraction 3 05 p adrenergic receptor residues 33 368 mutation yes P07700 CES Warne et al 2011 190 pdb code molecule UniProtKB resolution molecule fragment pdb code UniProtKB Appendix human D receptor 3PBL X ray diffraction 2 89 D dopamine receptor lysozyme chimera no information at protein data bank http www pdb org L119W C1054T C1097A P00720 P35462 Chien et al 2010 human H receptor 3RZE X ray diffraction 3 10 histamine H receptor lysozyme chimera no information at protein data bank http www pdb org no information at protein data bank http www pdb org O P35367 P00720 Shimamura et al 2011 Appendix 191 human CXCR receptor pdb code 3ODU at X ray diffraction molecule C X C chemokine receptor type 4 lysozyme chimera CXCR4 residues 2 229 lysozyme residues 1002 1161 CXCR
79. AFAVSCPLLF GFNTTGDPTV 190 200 210 220 230 240 CSISNPDFVI YSSVVSFYLP FGVTVLVYAR IYVVLKORRR KRILTRQNSQ CNSVRPGFPQ 250 260 270 280 290 300 QTLSPDPAHL ELKRYYSICQ DTALGGPGFQ ERGGELKREE KTRNSLMPLR EKKATOMVAI 310 320 330 340 350 360 VLGAFIVCWL PFFLTHVLNT HCQTCHVSPE LYSATTWLGY VNSALNPVIY TTFNIEFRKA FLKILSC 202 Appendix 10 20 30 40 50 60 MSLPNSSCLL EDKMCEGNKT TMASPQLMPL VVVLSTICLV TVGLNLLVLY AVRSERKLHT 70 80 90 100 110 120 VGNLYIVSLS VADLIVGAVV MPMNILYLLM SKWSLGRPLC LFWLSMDYVA STASIFSVFI 130 140 150 160 170 180 LCIDRYRSVQ QPLRYLKYRT KTRASATILG AWFLSFLWVI PILGWNHFMQ QTSVRREDKC 190 200 210 220 230 240 ETDFYDVTWF KVMTAIINFY LPTLLMLWFY AKIYKAVROH COHRELINRS LPSFSEIKLR 250 260 270 280 290 300 PENPKGDAKK PGKESPWEVL KRKPKDAGGG SVLKSPSQTP KEMKSPVVFS QEDDREVDKL 310 320 330 340 350 360 YCFPLDIVHM QAAAEGSSRD YVAVNRSHGQ LKTDEQGLNT HGASEISEDQ MLGDSQSFSR 370 380 390 400 410 420 TDSDTTTETA PGKGKLRSGS NTGLDYIKFT WKRLRSHSRQ YVSGLHMNRE RKAAKOLGFI 430 440 450 460 470 480 MAAFILCWIP YFIFFMVIAF CKNCCNEHLH MFTIWLGYIN STLNPLIYPL CNENFKKTFK RILHIRS Appendix 203 human CXCR4 receptor UniProtKB P61073 352 amino acids N terminus 1 38 E2 loop 175 195 TM II 78 99 42 261 3 2 2 MV 8 Em Dues exem 10 20 30 40 50 60 MEGISIYTSD NYTEEMGSGD YDSMKEPCFR EENANFNKIF LPTIYSIIFL TGIVGNGLVI 6 8 0 6 3 3 03 3 70 80 90 100 110 120 LVMGYQKKLR SMTDKYRLHL SVADLLFVIT LPFWAVDAVA NWYFGNFLCK AVHVIYTVNL 130 140 150
80. B adrenergic receptor 2RH1 2R4R 2R4S 3D4S 3NYA 3NY8 3NY9 3KJ6 3P0G 3PDS 3SN6 Turkey B adrenergic receptor 2VT4 2YCW 2YCX 2YCY 2YCZ 2Y00 2Y01 2Y02 2Y03 2Y04 Human dopamine D receptor 3PBL Human histamine H receptor 3RZE Human chemokine CXCR receptor 30DU 3OE6 30E8 30E9 30E0 Human adenosine receptor 3EML 2YDO 2YDV 3QAK 3PWH 3REY 3RFM to different conformations of the receptors Recently the crystal structure of a lig and bound covalently to the hB R was published 3PDS Rosenbaum et al 2011 Besides the crystal structures of adrenergic receptors 2010 the crystal structure of the human dopamine D receptor 3PBL Chien et al 2010 and 2011 the crystal strucuture of the human histamine receptor 3RZE Shimamura et al 2011 was published In addition to the mentioned crystal structures of biogenic amine recep tors crystal structures of the human chemokine CXCR4 receptor Wu et al 2010 and the human adenosine receptor Jaakola et al 2008 Lebon et al 2011 Xu et al 2011 Dore et al 2011 are known Table 3 1 Thus if a GPCR has to be modelled an appropriate template has to be chosen If one likes to model a biogenic amine receptor by homology modelling the crystal structure of a biogenic amine receptor is suggested to be used as template to solve this task For modelling of inverse agonists or neutral antagonist in the receptor bound state a template representing the inactive
81. Cut off 0 4 4 EnerPres 0 12 0 0 0 4 1 5 yes 6 4 Molecular Dynamic Simulation of your System 73 45 Temperature coupling 46 tcoupl berendsen 47 tc grps system 48 tau_t 0 1 49 ref t 298 50 Energy monitoring 51 energygrps System 52 Pressure coupling is not on 53 Pcoupl berendsen 54 pcoupltype isotropic 55 tau p 20 5 0 5 0 5 0 0 0 0 0 0 56 compressibility 4 5e 5 4 5e 5 4 5e 5 0 0 0 0 0 0 57 ref p 1 0 58 Generate velocites is on at 298 K 59 gen vel yes 60 gen temp 298 61 gen seed 173529 In the file md mdp the parameters unconstrained start and gen vel should be set no Afterwards the productive simulation phase without position restraints can be started If the binding mode of a ligand receptor complex should be analyzed via MD simulations analogous steps as shown above have to be performed Often it is very useful to administer the ligand with an equilibration protocol similar to that describe above for the receptor For analysis of the MD simulation several GROMACS commands like energy hbond rms and g_traj example can be used It has to be taken into account that water molecules can penetrate into the binding pocket and mediate interactions between the ligand and receptor as illustrated in Fig 6 3 Fig 6 3 Internal water lt molecules mediate the interaction between ligand and receptor Chapter 7 Calculat
82. E 1 palmitoyl 2 oleoylphosphatidylethanolamine PLPC Palmitoyllinoleylphosphatidylcholine 5 4 Internet Sources for Lipid Bilayer Models In the internet there are some sources which give a more detailed information with regard to lipid bilayers including simulation parameters for GROMACS At some sites in internet equilibrated lipid bilayer models can be obtained via free download A summary of the most important internet resources with regard to lipids is given in Table 5 2 Table 5 2 Most important URL internet resources with regard to lipds http lipidbook bioch ox ac uk http moose bio ucalgary ca index php page Structures Topologies http www lrz muenchen de heller membrane membrane html http www scmbb ulb ac be Users lensink lipid A very comfortable site is lipidbook http lipidbook bioch ox ac uk Domanski etal 2010 The aim of the lipidbook is a public repository for force field parameters with special emphasis on lipids http lipidbook bioch ox ac uk Fig 5 5 Here you individually select the force field the parameter notation for distinct software and the kind of lipid Fig 5 6 5 4 Internet Sources for Lipid Bilayer Models 41 Que Qewbeten Quonk women t e Ubidbock A pubic repository for ipad force ia 45 6 enters ic utes lipidbook em is a public for fM parematacs wih spaces
83. G 2 G 1 due to a change in the potential energy between the states 1 and 2 So we are able to use the MD simulation method to calculate a difference of the Gibbs energy for two distinct states of our system with the help of the so called thermodynamic perturbation formula 7 1 3 The Concept of the Coupling Parameter Within MD Simulations The mentioned procedure for calculating the mean according to Eq 7 18 sometimes leads to convergence problems in MD simulations especially if state 2 energeti cally is far from state 1 As a workaround to get the term G 2 G 1 a stepwise integration based on small differences of the Hamiltonian energies between neigh bouring states could be performed Returning to Eq 7 10 we introduce a so called coupling parameter which described the state of the system Therefore a variation of indicates a change of the system state and we can write GQ kT In 0 Q 7 20 where Q A reads f SOT 7 21 Within the framework of the coupling parameter concept the Coulomb potential for instance between two sites i and j separated by the distance for example is defined by the following equation 1 Ea 4T orij 7 22 Therein the superscripts 1 2 refer to the state 1 and 2 respectively 80 7 Calculation of Gibbs Energy of Solvation A differential small change in d will lead to the following expression for
84. I Fig 2 5 The ligand binding site is established by a so called venus flytrap module VFTM which is connected by a cysteine rich domain CRD to the transmembrane domain I 2 3 Activation of GPCRs and Their Interaction with G Proteins Based on several experimental data it was shown that GPCRs can undergo confor mational changes in simplest case between an inactive and an active conformation Kobilka and Deupi 2007 The binding of antagonists or inverse agonists stabilize 8 2 GProtein Coupled Receptors Fig 2 5 Schematic representation of a family C GPCR the inactive conformation whereas the binding of partial agonists induce a con formational change of the receptor Gether et al 1998 Pierce et al 2002 In the intracellular part GPCRs activated by the binding of an agonist are able to inter act with heterotrimeric G proteins consisting of a B and y subunit Fig 2 6 Kristiansen et al 2004 Oldham et al 2006 Fig 2 6 Schematic presentation of a GPCR activated by an agonist and interacting with a heterotrimeric G protein extracellular part il intracellular part 2 3 Activation of GPCRs and Their Interaction with G Proteins 9 There is only small knowledge about the interaction between GPCR and G pro tein on molecular level available Crystal structures of GPCRs see Chap 3 and appendix Important Crystal Structures of GPCRs Source http www pdb org on the one hand and G p
85. KKLRT PLNYILLNLA VADLFMVFGG FTTTLYTSLH GYFVFGPTGC NLEGFFATLG 130 140 150 160 170 180 GEIALWSLVV LAIERYVVVC KPMSNFRFGE NHAIMGVAFT WVMALACAAP PLVGWSRYIP 190 200 210 220 230 240 EGMQCSCGID YYTPHEETNN ESFVIYMFVV HFIIPLIVIF FCYGQLVFTV KEAAAQQOES 250 260 270 280 290 300 ATTOKAEKEV TRMVIIMVIA FLICWLPYAG VAFYIFTHQG SDFGPIFMTI PAFFAKTSAV 310 320 330 340 YNPVIYIMMN KOFRNCMVTT LCCGKNPLGD DEASTTVSKT ETSQVAPA Appendix 199 human adrenergic receptor e pue m me TMI 35 58 197 220 mer pes nes p mw mm _ 10 20 30 40 50 60 MGQPGNGSAF LLAPNGSHAP DHDVTQERDE VWVVGMGIVM SLIVLAIVFG NVLVITAIAK 70 80 90 100 110 120 FERLQTVTNY FITSLACADL VMGLAVVPFG AAHILMKMWT FGNFWCEFWT SIDVLCVTAS 130 140 150 160 170 180 IETLCVIAVD RYFAITSPFK YOSLLTKNKA RVIILMVWIV SGLTSFLPIQ MHWYRATHQE 190 200 210 220 230 240 AINCYANETC CDFFTNQAYA IASSIVSFYV PLVIMVFVYS RVFQEAKROL QKIDKSEGRF 250 260 270 280 290 300 HVQNLSQVEQ DGRTGHGLRR SSKFCLKEHK ALKTLGIIMG TFTLCWLPFF IVNIVHVIQD 310 320 330 340 350 360 NLIRKEVYIL LNWIGYVNSG FNPLIYCRSP DFRIAFQELL CLRRSSLKAY GNGYSSNGNT 370 380 390 400 410 GEQSGYHVEQ EKENKLLCED LPGTEDFVGH QGTVPSDNID SQGRNCSTND SLL 200 Appendix ma ps EE E3 dee 6 320 NAE 138 155 44 483 MGDGWLPPDC GPHNRSGGGG ATAAPTGSRQ VSAELLSQQW EAGMSLLMAL VVLLIVAGNV 70 80 90 100 110 120 LVIAAIGRTQ RLOTLTNLFI TSLACADLVM GLLVVPFGAT LVVRGTWLWG SFLCECWTSL 130 140 150 160 170 180 DVLCVTASIE TLC
86. Modelling of GPCRs www allitebooks com Andrea Strasser Hans Joachim Wittmann Modelling of GPCRs A Practical Handbook 2 Springer www allitebooks com Andrea Strasser Hans Joachim Wittmann University of Regensburg University of Regensburg Institute of Pharmacy Faculty of Chemistry and Pharmacy Dept of Pharm Med Chemistry Regensburg Regensburg Germany Germany ISBN 978 94 007 4595 7 ISBN 978 94 007 4596 4 eBook DOI 10 1007 978 94 007 4596 4 Springer Dordrecht Heidelberg London New York Library of Congress Control Number 2012938366 Springer Science Business Media Dordrecht 2013 No part of this work may be reproduced stored in a retrieval system or transmitted in any form or by any means electronic mechanical photocopying microfilming recording or otherwise without written permission from the Publisher with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system for exclusive use by the purchaser of the work Printed on acid free paper Springer is part of Springer Science Business Media www springer com www allitebooks com Preface Biological cells function as elementary building blocks for living individuals All compounds essential for establishing and maintaining life processes are to be pro duced inside the cells This makes it necessary for molecules and ions to pass the cell membrane in order to take part or to support the a
87. OMACS http www gromacs org software package But there is also a more flexible alternative in using LINUX commands as shown later on in Sect 6 4 6 2 Embedding the GPCR in a Lipid Bilayer The embedding of the GPCR into a lipid bilayer Fig 6 1 step 2 is an important step which has carried out very carefully For a more detailed information see also Chap 5 6 3 Solvation of the Lipid GPCR Complex Achiving Electroneutrality of the Simulation Box and Minimization In the next step the lipid GPCR complex should be solvated Fig 6 1 step 3 Some hints and pitfalls with regard to solvation of the lipid GPCR complex are mentioned in Chap 5 Most modelling software allows an automatic solvation of your system The solvation is very easy within GROMACS http www gromacs org Here you can use the command genbox If you have constructed a lipid GPCR complex in the file rec_lipid gro with the corresponding topology file system top you may perform the genbox command for example like this gt genbox cp rec lipid cs o rec lipid sol p system 6 3 Solvation of the Lipid GPCR Complex Achiving Electroneutrality 61 The option cp is used to define the file containing the structure that should be solvated The option cs has to be used to define the solvent With the option o you define the name of your output file Furthermore we recommend to use the option p and give the name of the topology file you are already using
88. OPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC POPC C26 C27 C28 29 30 C31 C32 033 C34 035 C36 C37 C38 C39 c40 C41 C42 C43 C44 C45 C46 C47 C48 C49 050 CA1 CA2 12 13 14 15 16 17 18 18 18 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 0 800 0 60 171 172 ia 0 14700 00 0 15300 00 0 14300 00 0 16100E 00 14800 00 14800 00 16100 00 14300 00 15300 00 14350 00 15300 00 13600 00 12300 00 15300 00 15300E 00 15300 00 15300 00 15300 00 15300 00 15300 00 15300 00 13900 00 15300 00 15300 00 15300 00 15300 00 15300 00 15300 00 15300 00 15300 00 14300 00 13600 00 12300 00 15300E 00 15300 00 15300 00 15300 00 15300 00 15300 00 15300 00 15300 00 15300 00 0 15300 00 0 15300 00 0 15300 00 0 15300 00 0 15300 00 0 15300 00 0 14700 00 0 14700 00 0 14700 00 CO OO O O O O O O O O O O O O O O O O O O O OO O OO OOO O O Op O O O O OoOo 0 3
89. PC 1 2 Goleo i sr glycecro 3 phosphochoine GROMOSS336 PG GROMOS87 1 Martini 21 DPhyPC 1 2 diphytanoy sn gycero 3 phosphochoine il 47 Utephy Issue Wacker Wiki Questions amp Answers Contact Static site content is Copyright 2009 2010 Jan Demariski and Oliver Beckstein and made avalatie under a CC by Scence v3 0 See Loensing Database for detais of conditions cf use Funded by the Wellcome Trust the EDICT project and BBSRC Fig 5 6 Browser in lipidbook http lipidbook bioch ox ac uk Domanski et al 2010 42 5 Lipids 5 5 Embedding a GPCR into a Lipid Bilayer For embedding a GPCR into a lipid bilayer different strategies are available The most time consuming would be to simulate the whole system de novo by putting an appropriate number of lipid and water molecules randomly around the GPCR and start a molecular dynamics simulation Since this procedure is really time consuming alternative methods are suggested One approach could be to set an appropriate num ber of lipid molecules in appropriate orientation around the protein Woolf and Roux 1996 Belohorcova et al 1997 However for this strategy you must have access to an appropriate software or you have to establish the software by yourself Alternatively for setting up your simulation box you can start with already prepared lipid bilayers Therefore you can look at the mentioned internet resources Table 5 2 download an equilibrated lipid bi
90. R Cornell et al 1995 Duan et al 2003 OPLS Jorgensen et al 1996 CHARMM MackKerell et al 1998 and GROMOS Oostenbrink et al 2004 Some force fields were developed for specific classes of molecules For example the EAS force field was developed for alkanes whereas other force fields like MM2 can be used in general Other force fields were especially developed for proteins nucleic acids and carbohydrates For performing any force field based calculations like minimization or molec ular dynamic simulations one needs the corresponding force field parameters GROMACS for example contains the command pdb2gmx This command allows if a correct pdb file of a protein is available to generate the so called topology file which contains all information about the force field parameters necessary for sim ulation Unfortunately pdb2gmx can be used only for proteins To obtain topology files for small compounds the PRODRG server http davapc 1 bioch dundee ac uk prodrg as described in Chap 4 can be used 2 This file was generated by PRODRG version AA081006 0504 126 9 Force Fields PRODRG written copyrighted by Daan van Aalten and Alexander Schuettelkopf E Questions comments to dava davapcl bioch dundee 7 ac uk A When using this software in a publication cite 5 A W Schuettelkopf van Aalten 2004 2004 PRODRG atoolforhigh throughput crystallography of protein ligand complexe
91. SSYFFLNLAIS FFVGV 66 TMIII jussus ricum TMIV hH1R 79 VVMPMNILYLLMSKWSLGRPLELFWLSMDYVASTASIFSVFILCI RSVQOPLRYLKYRTK TRASATILGAMFLSFLWVIPI 162 hH4R 67 ISIPLYIPHTLFE WDFGKEICVFWLTTDYLLCTASVYNIVLISY LSVSNAVSYRTQHTGVLKIVTLMVA LAFLVNGPM 150 TMV hH1R 163 LGW NHFMQOQTSVRREDKOCETDFYDVTWFKVMTAIINFY LLMLWFYAKIYKAVRQHCQ QYVSGLHMNRERKAAKQL 417 hH4R 151 ILV SESWKDEG SE PGFFSEWYILAITSFLEFVI ILVAYFNMNIYWSLWKRDH HQREHVELLRARRLAKSL 305 TMVI TMVII hH1R 418 GFIMAAFILCWIMYFIFFMVIAFCKNC CNEHLHMFTIWLGYINST IYPLCNENFKKTFKRILHIRS 487 hH4R 306 AILLGVFAVCW SLFTIVLSFYSSATGPKSVWYRIAFWLQWFNS LY PLCHKRFOKAFLKIFCIKKQPLPSQHSRSVSS 390 Fig 3 10 Manual alignment of the hH4R to the hH R green termini and loops grey transmem brane domains red boxes highly conserved amino acids Ballesteros et al 2001 yellow highly conserved cysteine establishing a disulfide bridge to the upper part of TM III missing amino acids the amino acids of the I3 loop are not shown completely which is indicated by dots Therefore some amino acids of the beginning and end of the I3 loop are modelled correctly and the gap is closed by an alanine chain The E2 loop has to be aligned very carefully It has to be taken into account that there is a highly conserved disulfide bridge between the E2 loop and the upper part of TM III Thus the corresponding cysteine has to be positioned correctly An example for an alignment o
92. Source http www gpcr org 7tm FamilyA Thefamily A GPCRs represents the largest GPCR family IUPHAR 2000 Ballesteros et al 2001 Chalmers et al 2002 Jacoby et al 2006 Mustafi et al 2009 and is the one which is mostly studied The family A GPCRs like biogenic amine re ceptors or rhod opsin see appendix GPCR Families Source http www gpcr org 7tm are the most studied so far A disulfide bridge between the E2 loop and the upper part of TM is typical for most of the family A GPCRs Fig 2 3 Additionally most A Strasser H J Wittmann Modelling of GPCRs 5 DOI 10 1007 978 94 007 4596 4_2 Springer Science Business Media Dordrecht 2013 6 2 GProtein Coupled Receptors 732 other targets D El GPCRs as target Fig 2 2 Schematic representation if of a G extracellular part protein coupled receptor embedded in a lipid bilayer Fig 2 1 Percentage of drugs addressing GPCRs intracellular part Table 2 1 Three GPCR main Family A class I Rhodopsin like families A B and C Family B class II Secretin like Familiy C class Metabotropic glutamate like of the family A GPCRs have a palmitoylated cysteine in the C terminus In general the homology of the family A GPCRs is small However a small number of highly conserved key residues like the DRY motif could be identified Typically small ligands of biogenic amine receptors for example bind between the transmembrane domains of the receptor
93. TheAll atom concept and Site concept In general there are two opposite concepts with regard to force field parameteriza tion On the one hand there is the so called all atom model e g ethanol Fig 9 4 As already indicated by the name all atoms of the molecule are included into the calculation and therefore parameterized On the other hand there is the so called site model Fig 9 4 Therein a small group of atoms in general connected via bonds are summarized within one group the so called site It is very important that the combination of several atoms into one site is ingenious Thus in general methyl moieties methylene moieties and aromatic and aliphatic CH 9 3 The Force Field Parameters 125 all atom model site model Fig 9 4 All atom model versus site model moieties are summarized to one site However in some force fields aromatic CH moieties are not handled as one site Due to the dipole character it would not be very useful to combine the hydrogen and oxygen of a hydroxy moiety OH to one site A combination into one site would not allow describing intermolecular interaction like hydrogen bonds 9 3 The Force Field Parameters In literature a number of force fields which differ in the values for the non variable parameters of the potential energy terms mentioned in the foregoing section are described The most prominent for example are the following TRIPOS Clark et al 1989 AMBE
94. To overcome this difficulty we make use of the fundamental thermodynamic relations in the case of constant pressure PANT AC 10 27 oT 77 57 ACS 10 28 aT T where the quantity AC denotes the change in the heat capacity for the reference state during the reaction and reads AC 10 29 PLR C pL and Cj denote the heat capacity of the complex the ligand and the receptor within the solution in its particular reference state These terms are indepen dent of concentration but are generally functions of the temperature and the pressure If we are interested in the values of A and AS at a given temperature we can determine the association constants K at a series of temperatures enclosing by evaluating the particular concentration of the ligand receptor complex at given ck and c with the help of radioligand competition binding assays Weiland et al 1979 Wittmann et al 2009 Here we also assume that c is much larger than c and so we are able to calculate AG for each temperature according to Eq 10 18 To combine A H and AS with AG at different temperatures Eq 10 19 we integrate Eqs 10 27 and 10 28 in the range from to any temperature of the series If the temperature interval of the measurement is small for example 25 K it is a good first approximation to think of as a constant for a given reaction according to Eq 10 1 and the integration of Eqs
95. VIAIDRY LAITSPFRYO SLMTRARAKV IICTVWAISA LVSFLPIMMH 190 200 210 220 230 240 WWRDEDPQAL KCYODPGCCD FVTNRAYAIA SSIISFYIPL LIMIFVYLRV YREAKEQIRK 250 260 270 280 290 300 IDRCEGRFYG SQEQPOPPPL PQHQPILGNG RASKRKTSRV MAMREHKALK TLGIIMGVFT 310 320 330 340 350 360 LCWLPFFLVN IVNVFNRDLV PDWLFVFFNW LGYANSAFNP IIYCRSPDFR KAFKRLLCFP 370 380 390 400 410 420 RKADRRLHAG GQPAPLPGGF ISTLGSPEHS PGGTWSDCNG GTRGGSESSL EERHSKTSRS 430 440 450 460 470 480 ESKMEREKNI LATTRFYCTF LGNGDKAVFC TVLRIVKLFE DATCTCPHTH KLKMKWRFKQ HOA Appendix 201 human D receptor 10 20 30 40 50 60 MASLSQLSSH LNYTCGAENS TGASQARPHA YYALSYCALI LAIVFGNGLV CMAVLKERAL 70 80 90 100 110 120 QTTTNYLVVS LAVADLLVAT LVMPWVVYLE VTGGVWNFSR ICCDVFVTLD VMMCTASILN 130 140 150 160 170 180 LCAISIDRYT AVVMPVHYQH GTGQSSCRRV ALMITAVWVL AFAVSCPLLF GFNTTGDPTV 190 200 210 220 230 240 CSISNPDFVI YSSVVSFYLP FGVTVLVYAR IYVVLKQRRR KRILTRQNSQ CNSVRPGFPQ 250 260 270 280 290 300 QTLSPDPAHL ELKRYYSICQ DTALGGPGFQ ERGGELKREE KTRNSLSPTI APKLSLEVRK 310 320 330 340 350 360 LSNGRLSTSL KLGPLQPRGV PLREKKATQM VAIVLGAFIV CWLPFFLTHV LNTHCQTCHV 370 380 390 400 SPELYSATTW LGYVNSALNP VIYTTFNIEF RKAFLKILSC sequence Isoform 3 P35462 3 length 367 amino acids 10 20 30 40 50 60 MASLSQLSSH LNYTCGAENS TGASQARPHA YYALSYCALI LAIVFGNGLV CMAVLKERAL 70 80 90 100 110 120 QTTTNYLVVS LAVADLLVAT LVMPWVVYLE VTGGVWNFSR ICCDVFVTLD VMMCTASILN 130 140 150 160 170 180 LCAISIDRYT AVVMPVHYOH GTGQSSCRRV ALMITAVWVL
96. YFITSLACABLVMGLAVVPFGAAHILMKMWTFGNFWCEFWTSI 112 12 loo 113 DVLCVTASIETLCVIAVDYFAITSPFKYOSLLTKNKARVIILMVIVSGLTSFLP 168 E2 loo 16 9 IOMHWYRATHQEA INCYANETCCDFFTNQAYAIASSIVSFYVBLVIMVFVYSRVFQ 224 13 loo 225 EAKROLOKIDKSEGRFHVONLSQVEQDGRTGHGLRRSSKFCLKEHKALKTLGIIMG 280 TM VI 281 TFTLCWLBFFIVNIVHVIQDNLIRKEVYILLNWIGYVNSGFNBLIYCRSPDFRIAF 336 C terminus 337 QELLCLRRSSLKAYGNGYSSNGNTGEQSGYHVEQEKENKLLCEDLPGTEDFVGHQG 3 92 393 TVPSDNIDSPGRNCSTNDSLL 413 Fig 3 8 Amino acid sequence of the human adrenergic B receptor The transmembrane domain are presented as defined at http expasy org accession code P07550 The highly conserved amino acids defined by Ballesteros Ballesteros et al 2001 are marked by red boxes a Glu 107 b 79092 o Glu 29 98 MWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDBYFAITSPFK 140 1 2100 val 129 98 MWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDYFAITSPFK 140 Val 48 325 332 3 50 Fig 3 9 Helical structure of a transmembrane domain a Definition of the TM domain III of the human adrenergic B receptor at expasy http www expasy org b TM of the human adrenergic receptor of a crystal structure c Amino acid sequence of TM domain III based on the crystal structure 22 3 Sequence Alignment and Homology Modelling homology modelling In general the crystal structure with highest sequence homol ogy to the receptor which is intended be mode
97. _start yes 12 integrator md 13 tinit 0 14 dt 0 001 ps 15 nsteps 100000 16 nstcomm 1 17 Output control 18 nstxout 5000 19 nstvout 5000 20 nstfout 21 nstlog 5000 22 nstenergy 100 90 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 55 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 7 Calculation of Gibbs Energy of Solvation Neighbor searching nstlist 10 ns_type grid pbc xyz rlist 1 4 Electrostatics coulombtype PME rcoulomb switch 0 rcoulomb 1 4 epsilon_r 1 20 epsilon rf 7 0 vdwtype Cut off rvdw switch 0 rvdw l 4 DispCorr EnerPres fourierspacing 20 12 fourier nx 0 fourier ny 0 fourier nz 0 pme order 4 ewald rtol 1 5 optimize fft yes Temperature coupling tcoupl berendsen tc grps LIG SOL tau_t 0 1 0 1 ref t 298 298 Energy monitoring energygrps LIG SOL Pressure coupling is not on Pcoupl berendsen pcoupltype isotropic tau_p 5 0 5 05 0 0 0 0 0 0 compressibility 4 5e 5 4 5e 5 4 5e 5 0 0 0 0 0 0 ref p 1 0 Generate velocites is at 298 K gen vel yes gen_temp 298 gen_seed 173529 Free Energy Calculation free_energy yes sc alpha u sc power 2 init lambda 20 0 7 2 Examples Conceptual and Practical Considerations 91 The files 4941 dat created by gib
98. a system For calculating thermodynamical quantities the reader is referred to Chaps 7 and 10 Up to now processes with time constants in the range of some are subject to MD simulations so processes taking place with time constants in the range of ms or larger like diffusion processes in solutions cannot be captured by this method Furthermore force field methods are unable to handle processes www allitebooks com 4 1 Introduction accompanied by bond forming or bond breaking Thus the calculation of the Gibbs energy see Chap 7 is limited to reactions leaving the molecule intact e g solvation processes completely different concept known as quantitative structure activity relationship does not deal with theoretically founded energy terms Most often the quantitative structure activity relationship QSAR is used to predict for example structures and association constants for biochemical systems Strasser et al 2010a Silva et al 2011 Following this concept a correlation is established between the desired property of a system and leading variables for the training systems Kubinyi 2011 Calculating the value of the leading variables for the system of interest pro vides the desired property with the help of the former correlation However it must be emphasized that the better the system of interest corresponds to the data material representing the training set the better the prediction of binding properties will
99. ago GFJ Salamon Z Brown MF Tollin G Hruby VJ 2005 Phosphatidylethanolamine enhances rhodopsin photoactivation and transducin binding in a solid supported lipid bilayer as determined using plasmon waveguide resonance spectroscopy Biophys J 88 198 210 Bae H Cabrera Vera TM Depree KM Graber SG Hamm HE 1999 Two amino acids within the o4 helix of Gil mediate coupling with 5 hydroxytryptaminelB receptors J Biol Chem 274 14963 14971 Ballesteros JA Shi L Javitch JA 2001 Structural mimicry protein coupled receptors impli cations of the high resolution crystal structure of rhodopsin for structure function analysis of rhodopsin like receptors Mol Pharmacol 60 1 19 Barth P Wallner B Baker D 2009 Prediction of membrane protein structures with complex topologies using limited constraints PNAS 106 1409 1414 Belohorcova K Davis JH Woolf TB Roux B 1997 Structure and dynamics of an amphiphilic peptide in a lipid bilayer a molecular dynamics study Biophys J 73 3039 3055 Bokoch MP Zou Y Rasmussen SGF Liu CW Nygaard R Rosenbaum DM Fund JJ Choi HJ Thian FS Kobilka TS Puglisi JD Weis WI Pardo L Prosser RS Mueller L Kobilka BK 2010 Ligand specific regulation of the extracellular surface of a G protein coupled receptor Nature 463 108 112 Bouzida D Kumar S Swendsen RH 1992 Efficient Monte Carlo methods for the computer simulation of biological molecules Phys Rev A 45 8894 8901 Br uner Osborne H Wellendorp
100. al in solution and exhibit a kind of dynamical behaviour This is taken into account by molecular dynamic simulations of a protein in its natural surrounding Additionally with several distinct molecular modelling techniques ligand receptor interactions for example can be simulated in a reasonable time and insights onto interactions on molecular level can be obtained Furthermore some techniques like 3D QSAR Brown et al 2006 Dudek AZ et al 2006 Gedeck et al 2008 Scior T et al 2009 allows predicting affinities also in context with GPCRs Strasser et al 2010a Silva et al 2011 However molecular modelling results should be when ever possible compared with experimental data in order to judge predictive quality To combine the experimental results with computational methods in order to under stand and moreover to predict the behaviour of systems involving chemical reactions it is necessary to establish a link between macroscopic quantities like equilibrium and rate constants thermodynamic quantities like AH and AS which are available from experimental methods Leavitt S et al 2001 Wittmann et al 2009 Torres et al 2010 and microscopic properties like energy levels which result from the interac tions of the nuclei and electrons comprising the distinct particles of the system of interest This task is not a simple one especially when certain properties for exam ple of a ligand interacting with the receptor are to be depicted as
101. all to gawk s built in function match which takes a string here the entire line 0 of the base sequence read from the file 11 7 A More Extensive Example 157 base dat and searches for the beginning of the regular expression enclosed in slashes represented by the second argument of the function match The notation means one or more occurrences of lower case characters The second assignment defines the variable seq which holds the substring of the entire line 0 starting at RSTART and spawning RLENGTH characters In this case we make use of two built in variables of gawk RSTART and RLENGTH which are set by the function match The pattern action statement denoted by END prints out the interesting sequence of bases the starting position of the substring and its number of characters Now we will combine both gawk commands to construct the associative array AS and to extract the appropriate base sequence The latter task will be done in the action part of the pattern BEGIN whereas the array AS is to be constructed in the action part applied to each input line of code dat The command will now look like this gawk BEGIN getline base base dat match base a z seq substr base RSTART RLENGTH AS 1 2 print AS 1 END print seq code dat Because we have two input files base dat and code dat the BEGIN action part uses the get Line statement to store the content
102. amp means the locial AND operator Gawk reads one line after the other from the input file data and prints out the field numbers 6 8 and 10 only from the lines in the range between 2500 and 3456 inclusive Assume there is an output file out from a simulation run which contains a line holding the heat of formation in the form HEAT OF FORMATION 1345 774 kJ mol To get the value 1345 774 in Joule per mole the appropriate line indicated by the term HEAT OF has to be located and the value of field number 5 multiplied by thousand has to be printed out Take into consideration that any number of repeated blanks and or tabs count as a single delimiter where leading delimiters will be ignored Thus the command will read gt gawk HEAT OF print 5 1 0e3 out In this case the pattern consists of a regular expression HEAT OF en closed in slashes indicating the line of the file out which will be processed by gawk grep syntax grep regular expression file grep v regular expression file grep c regular expression file grep n regular expression file explanation The four command lines given above will lead to the following results 148 11 Important UNIX LINUX Commands grep searches the named file for lines containing a mach to the specified regular expression and writes them to standard output For a complete description of regular expression used by grep see the appropriate manual page
103. any species i is governed by its electrochemical potential Z the chemical energy per mole which mainly comprises in our framework of three energetic parts First there is the contribution of the atomic nuclei of all the atoms present in a molecule of species i its kinetic energy and the potential energy resulting from the chemical bonds between the atoms of the molecule In a simple view these contributions may be described as the chemical nature of the species i As the reaction takes place in a solution phase a further energetic contribution resulting from the independent interaction of each molecule of species i with the surrounding solvent has to be taken into account All these energy terms are summarized in the quantity H5 the so called reference chemical potential per mole of species i Cellular systems often exhibit compartiments by means of membranes which are not permeable for all species particularly ions As a consequence parts of the whole system show an electrostatic potential apart from zero which leads to a second molar potential energy contribution for a charged particle of species i characterized by its valency Zi given by zi F 10 5 where F denotes the Faraday constant i e the charge of one mole of an arbitrary ion with valency 1 The last contribution to the electrochemical potential has its origin in the second law of thermodynamics The species i will be more stable if a given number of moles will be d
104. ar Dynamics A receptor model which was energetically minimized represents only one local minimum on the potential energy surface Additionally those minimized receptor models are based on homology models with more than 50 difference in amino acid sequence compared to the template in most cases Thus receptor models should be refined by molecular dynamics MD Besides that GPCRs embedded in their natural surrounding are not rigid in contrast they show a distinct flexibility Thus it 15 state of the art to analyze proteins by MD simulations Carloni et al 2002 Christen et al 2008 In the early beginning of performing MD simulations of GPCRs the calculations were performed in gas phase without including the natural surrounding of the receptor To avoid the destroy of the secondary and tertiary structure of the GPCR position restraints were set onto the backbone of the transmembrane domains However this lead to wrong conformations of the amino acid sidechains located at the surface of the receptor To avoid such artefacts the surrounding of the GPCR has to be included into the calculations On the one hand the surrounding stabilizes the conformation of the receptor On the other hand the correct surrounding allows the amino acid side chains on the receptor surface to achieve a correct conformation Forenabling an adequate simulation box with the GPCR in its natural surrounding at least four main steps illustrated also in Fig 6 1 ha
105. ation around z axis is given in Fig 8 3 Fig 8 3 Section of the 0 potential surface describing 92 the interaction between 0 receptor the Go subunit 02 with regard to translation on inactive E 0 z axis and rotation around GPCR z axis Copyright by 0 Springer with permission 1 from Springer modified 5 0 0 2 0 02 active E o GPCR 0 4 1 2 1 SHS PPPS SPSS Yr Based on the potential energy surface shown in Fig 8 3 a model for a hD R Go complex was suggested Strasser and Wittmann 2010b Because the crystal structure of a hB R GaBy complex was published recently Rasmussen et al 2011 the pre diction was compared with the experimentally determined structure Strasser and Wittmann in press The comparison between predicted model I and experimental results revealed an rmsd of about 8 4 Therefore the potential energy surface scan was extended in order to find a structure with smallest rmsd compared to the crystal structure Fig 8 4 110 Fig 8 4 Potential energy Epot and rmsd surfaces for the systematic search in the Yr range 60 to 60 and y 30 to 30 arrow model I representing a gobal minimum on the potential energy surface as predicted Strasser and Wittmann 2010b arrow b minimum rmsd between the calculated model I and the corresponding parts of the crystal structure arrow c local minimum on the
106. be Chapter 2 G Protein Coupled Receptors The G protein coupled receptors GPCRs represent one of the largest families of proteins within the human genome and mediate several physiological and patho physiological effects Jacoby et al 2006 GPCRs are of general interest with regard to therapy of several diseases since about 27 96 of all drugs available on market are addressing GPCRs Fig 2 1 Wise et al 2002 Overington et al 2006 Since alot of literature is available with regard to GPCRs only a short introduction is given in this chapter 2 Structure of GPCRs GPCRs are transmembrane receptors Thus they are located in the lipid bilayer The GPCRs consist of seven transmembrane o helixes spanning through the membrane from the extracellular to the intracellular part The transmembrane domains are con nected by intra and extracellular loops The N terminus amino terminus is located on the extracellular part whereas the C terminus carboxy terminus is located on the intracellular part Because of the structure GPCRs are sometimes called seven transmembrane receptors 7 TM receptors Fig 2 2 22 Different GPCR Families GPCRs were divided into several families A F classes and are described system atically IUPHAR 2000 Fredriksson et al 2003 Suwa et al 2011 http www gpcr org However there are three main families A B and C Table 2 1 A more detailed listing is given in the appendix GPCR Families
107. ble to extract the substring consisting of lower case characters and evaluate its length with the help of the following pipeline gt echo n base tr d A Z wc m A where the echo command is used with the option n to suppress the trailing newline character which erroneously would be counted by wc see command section The tr command deletes all upper case characters of the string Enclosing the command line above in back quotes as the first argument the command expr outputs the desired result gt expr echo n base tr d A Z wc m 3 J Note the use of a variable substitution as part of a command substitution 11 3 4 Protection Mechanism for Meta Characters of the TC Shell Sometimes it is necessary to suppress part of the shell substitution or to have meta characters as valid characters not modifying the original command line For this purpose tcsh provides the backslash or single quotes and double quotes A charac ter preceded by a backslash for example N will not be expanded Note that the backslash is needed to prevent the shell from a special treatment of the symbol To protect more than one meta character from shell substitution within a string single quotes might be used Suppose we have defined the variable x with value 123 via gt set x 123 J 144 11 Important UNIX LINUX Commands then the commands gt echo abc x and gt echo abc x will both write the string abc x to t
108. bove E J kJ mol Here the torsional energy between site 1 C4 CH3 site 2 C1 CH2 site 3 O2 OA and site 4 H2 H of ethanol is described For the presented example o is 0 the force constant k is 1 3 kJ mol and the multiplicity n is 3 The corresponding course of the torsional energy is shown in Fig 9 7 9 3 The Force Field Parameters 129 There is no separate section with regard to partial charges of the sites The partial charges in the topology files of GROMACS are found in the section atoms in the 7th column Let us look for example onto the partial charge of the CH3 and OA site For the CH3 site the partial charge is 0 074 eo eo denotes the elementary charge whereas the partial charge for the OA site is 0 202 eo as suggested in the corresponding topology file see above The electrostatic interaction between the CH3 and OA site in dependence of distance r for vacuum e 1 and aqueous phase 78 is presented in Fig 9 8 The Lennard Jones or van der Waals parameter are not found within the topology file generated by the PRODRG server Instead the are found in the corresponding parameter file For the f G53a6 force field Oostenbrink et al 2004 for example the Lennard Jones parameters are found in the file G53a6nb itp which may be located in the directory gromacs share gromacs top in your GROMACS installation directory For the interaction between a CH3 and OA site a value of 0 004663
109. bs energy contain two columns The first column represents the time and the second one the values 40 To calculate the mean of at one the gawk script average gibbs presented below can be used usr bin gawk f UJ s 0 n 0 s s 2 E ND print s n Before the script average gibbs can be started the execute permission for the user has to be set using the following command chmod u x average gibbs Additionally average gibbs must reside in the same directory as gibbs energy because average gibbs is started in line 43 of gibbs energy Thus after gibbs_energy has completed a file named 1ambda gibbs dat is created containing in the first column and the mean of 46 the second column With the help of the script integrate shown later on the integration can be performed The calculation for ethanol in water ethanol in vaccuo and ethanol for the transfer from vaccuo into aqueous phase may lead to 4 as function of at a temperature of 293 0 K as shown in Figs 7 2 7 3 and 7 4 To be able to calculate the Gibbs energy of solvation the integral for the corre sponding curve has to be determined For integration you can use distinct software products like xmgrace http plasma gate weizmann ac il Grace However after long simulations the data sets might be too large and it might be very time consum ing to perform the integration with such software In t
110. btain an equilibration of the lipids in the xy plain slight position constraints might be put onto the z coordinates of the lipids In general the modeller is encouraged to perform some different equilibration protocols in order to obtain an optimal structure After this equilibration step the lipid bilayer is fitted well to the GPCR and the gap between the GPCR and the lipid bilayer is removed Now the system can be solvated in the next step An optimally solvated box should look as shown in Fig 5 13 5 Lipids 56 PU ra n UNT msg SA the and lipid bilayer and extra intracellular water u Equilibration of the lipid bilayer around the GPCR Fig 5 13 Step 5 well prepared simulation box containing the GPCR Fig 5 12 Step 4 5 5 Embedding a GPCR into a Lipid Bilayer 57 avoid a water layer at the ends of the lipid bilayer artificial water channel through the lipid bilayer at the edges of the simulation box 5 s Z St q dublicate of your dublicate of your simulation box due simulation box due to periodic boundary to periodic boundary conditions conditions your simulation box Fig 5 14 Artificial water channels through the lipid bilayer at the edges of the simulation box as consequence of wrong system setup 58 5 Lipids With regard to solvation you have to look carefully onto the size of your simulation box If the defined box size is a little bit larger than t
111. ccording to Ballesteros Ballesteros et al 2001 of each transmembrane domain of rhodopsin like GPCRs TMI TM II TM III IV TMV TM VI TM VII Asn N Asp D Arg R Trp W Pro P Pro P Pro P 3 3 2 Ballesteros Nomenclature A careful analysis of the known amino acid sequences of known rhodopsin like GPCRs by Ballesteros Ballesteros et al 2001 exhibited the most conserved amino acid within each of the seven transmembrane domains which is used as a reference for all other amino acids within the same helix Within this nomenclature the term X YY is used Therein X represents the number of the transmembrane domain and YY the position of the residue within the transmembrane domain The most conserved amino acid within one helix gets the number 50 All other amino acids within the same helix are numbered relative to that highly conserved position 50 The highly conserved amino acids of each transmembrane domain of a GPCR according to the Ballesteros nomenclature Ballesteros et al 2001 are given in Table 3 2 In Fig 3 8 the complete amino acid sequence with the conserved amino acids according to Ballesteros Ballesteros et al 2001 of the human adrenergic B receptor is presented One should pay attention onto the transmembrane regions as pointed out in Fig 3 8 As already mentioned the amino acids related to the transmembrane regions are given at http expasy org under the corresponding accession code comparison to the correspond
112. chanics To take advantage of this method we have first to define the boundary between the quantum mechanical region and classical region and secondly we have to establish a con nection between the two regions which is done by introducing so called link atoms A further improvement of the hybrid methods is developed in the framework of the moving domain quantum mechanics molecular mechanics MoD QMMM gain deeper insight into the basics of the hybrid methods the reader is referred to the liter ature Gascon et al 2006 Menikarachchi et al 2008 Searching the potential energy surface for minima any of the mentioned methods will find only local minima To identify the most stable configuration of the system of interest the global minimum of the potential energy surface should be detected but up to now no reliable algo rithm solving this problem is available Thus to get enough information about the system of interest multiple scans have to be done from distinct starting structures But in this context the question arises whether these different configurations have to be linked by equilibrium processes or not Doing so we will get a very large set of structures from which we have to explain the interaction between the ligand and the receptor A further crucial problem appears when the entropic contributions are to be evaluated Molecular mechanics methods totally lack the calculation of such terms whereas quantum mechanical bas
113. conformation should be chosen whereas a template representing the active conformation should be used in case of partial ag onists Furthermore the homology between the receptor to be modelled and the tem plate should be as high as possible Based on these suggestions itis the responsibility of the modeller to choose an appropriate template for homology modelling Sometimes a look onto the homepage of GPCR network http cmpd scripps edu is very useful There you get information about the tracking status of GPCRs which will be crystallized in future Fig 3 1 3 2 Crystal Structures of GPCRs Source http www pdb org In the appendix the most important information with regard to all crystal structures of rhod opsin or GPCRs is summarized tabular These tables should give you a fast overview onto available crystal structures resolution structure of a cocrystallized ligand related UniProtKB entries and corresponding literature Have a careful look onto the section mutation Often not the wild type receptor is crystallized instead point mutations were introduced Thus if you want to model the receptor which is crystallized you may change the amino acids mutated in the crystal structure into the corresponding amino acid of the wild type receptor An overview of the differences in crystal structures is given by the Figs 3 2 3 6 www allitebooks com 3 2 Crystal Structures of GPCRs Source http www pdb org 15
114. cs by isothermal titration calorimetry Curr Opin Struct Biol 11 560 566 Lebon G Warne T Edwards PC Bennett K Langmead CJ Leslie AGW Tate CG 2011 Agonist bound adenosine 2 receptor structures reveal common features of GPCR activation Nature 474 521 525 Li J Edwards PC Burghammer M Villa C Schertler GFX 2004 Structure of bovine rhodopsin in a trigonal crystal form J Mol Biol 343 1409 1438 Lim HD Jongejan A Bakker RA Haaksma E de Esch IJP Leurs R 2008 Phenylalanine 169 in the second extracellular loop of the human histamine H4 receptor is responsible for the difference in agonist binding between human and mouse H receptors J Pharmacol Exp Ther 327 88 96 Lipkowitz KB Boyd DB 2007 Semiempirical molecular orbital methods Reviews Comp Chem 1 45 81 McKerell AD Bashford D Bellott M Dunbrack RL Evanseck JD Field MJ Fischer S Gao J Guo H Ha S McCarthy JD Kuchnir L Kuczera K Lau FTK Mattos C Michnick S Ngo T Nguyen DT Prodhom B Reiher WE Roux B Schlenkrich M Smith JC Stote R Straub J Watanabe M Wiorkiewicz Kuczera K Yin D Karplus M 1998 All atom empirical potential for molecular modeling and dynamics studies of proteins J Phys Chem 102 3586 3616 References 213 Mackerell AD 2004 Empirical force fields for biological macromolecules overview and issues J Comput Chem 25 1584 1604 Mehler EL Hassan SA Kortagere S Weinstein H 2006 Ab initio computational modeling of loops in G prot
115. ction and the related signal cascades Working on the field of GPCRs theoretical concepts have to be developed and a large number of related pro grams have to be designed and it turns out that the operation system UNIX LINUX is the best solution to do all this work in a highly efficient manner Thus we got the idea to present not only a review of methods and results concerning the modelling of GPCRs but to establish a practical guide for researchers interested in this field Real izing the great importance of the work in computing we included a chapter designed as an overview of the most important UNIX LINUX commands and present a lot of solutions concerning computational problems We hope researchers will compre hend the benefit of the operating system All commands and scripts presented in this book were developed very carefully Nevertheless we do not give any warranty for correctness www allitebooks com Contents 3 4 5 5 Lipids 1 Introduction 2 G Protein Coupled 2 1 Structure 2 2 Different GPCR Families 2 3 Activation of GPCRs and Their Interaction with G Proteins 2 4 Important Internet Sources with Regard to GPCRs 3 Sequence Alignment and Homology Modelling 3 1 Selection ofa 1
116. d Glycine 163 164 H O N Histidine OH 4 Isoleucine At NH OH OH OH Yon NH3 OH NH2 O OH NH O pn Phenylalanine S H Serine v 2 1 n 8 Appendix Threonine Tryptophane Tyrosine Valine GPCR Families Source http www gpcr org 7tm Class A rhodopsin like Amine Muscarinic acetylcholine Adrenoceptors Dopamine Histamine Serotonin Octopamine Trace amine Peptide Angiotensin Bombesin Bradykinin C5a anaphylatoxin Fmet leu phe APJ like 165 UGG 166 Appendix Interleukin 8 Chemokine Cholecystokinin Endothelin Melanocortin Duffy antigen Prolactin releasing peptide GPR10 Neuropeptide Y Neurotensin Opioid Somatostatin Tachykinin Vasopressin like Galanin like Proteinase activated like Orexin amp neuropeptides FF QRFP Urotensin II Adrenomedullin G10D GPR37 endothelin B like Chemokine receptor like Neuromedin U like Somatostatin and angiogenin like peptide Allatostatin C drostatin C Melanin concentrating hormone receptors Prokineticin receptors Sulfakinin CCKLR Other peptide receptors Hormone protein Follicle stimulating hormone Lutropin choriogonadotropic hormone Thyrotropin Gonadotropin Rhod opsin Olfactory Prostanoid Prostaglandin Prostacyclin Thromboxane Nucleotide like Adenosin
117. d backbone atoms set selover atomselect top segid 1seg and x xmin or x xmax or y ymin or y ymax delete these residues set resover lsort unique selover get resid foreach res resover delatom 1seg res write full structure writepsf OUT psf writepdb OUT pdb clean up file delete Stemp psf file delete Stemp pdb non interactive script quit In Fig 5 9 the membrane with a hole created as described above is shown The file membrane gro should look similar if loaded into vmd After establishing an appropriate hole in the lipid bilayer and putting the GPCR into the hole you should receive a system as shown in Fig 5 10 The file protein lip gro created above should look similar As you can see in the figure there is a significant gap between the lipid bilayer and the GPCR Now the system consists of the lipid bilayer and the GPCR Using the GROMACS commands grompp and mdrun the system can be minimized see Chap 6 Thus 5 Lipids 54 Fig 5 9 Step 2 Generate a hole of appropriate size for o gt s i 4 s o o Fig 5 10 Step 3 Placement of the GPCR or GPCR G protein complex in the lipid bilayer www allitebooks com 5 5 Embedding a GPCR into a Lipid Bilayer 55 Fig 5 11 An artificial water avoid a water shell shell between the GPCR and the lipid bilayer as between the receptor consequence of
118. directory where vmd is started from two files named membrane pdb and membrane psf are gen erated The extension psf means protein structure file In the next step the file protein pdb has to be loaded via File New Molecule To simplify the alignment of the protein in the lipid bilayer use the menu Graphics Representations Coloring Method Color yellow and Drawing Method New Cartoon Now the coordinates of the pro tein have to be changed via Mouse Move Molecule Be careful and move ONLY the protein and NOT the membrane Moving the membrane in the move mode would result in a failure of the alignment In the move mode use the left mouse button for translation the shift button and the left mouse button for rotation around the z axis and the shift button in combination with the middle mouse button to rotate around the axis vertical to the screen Therefore click directly onto the protein with the mouse cursor To leave the move mode type r or use the menu button Mouse gt Rotate In rotate mode you can rotate the whole system membrane and protein as appropriate without changing any coordinates In the next step you have to use the move and rotate mode alternately to align the protein into the lipid bilayer This procedure should be performed very carefully with regard to the placement of the GPCR in the membrane Addi tionally this procedure needs some practice
119. e ar Your molecule added hydrogens H Fig 4 8 Output of the PRODRG Server with regard to dobutamine The action that molecules with a basic or acid moiety are calculated in its charged form is based on the behaviour of carboxylic acid or amines in water at pH values about 7 Under these conditions carboxylic moieties for example are deprotonated and amino moieties are protonated Chapter 5 Lipids Lipid membranes separate two compartimentes from each other they separate a cell from the surrounding or they separate the cytoplasm of cells into organelles These membranes consist of two layers of lipid the so called lipid bilayer The lipid bilayer is a planar two dimensional fluid A large number of proteins belong to the class of membrane proteins Membrane proteins can be divided into two groups First peripheral membrane proteins which are located on the surface of the lipid bilayer and second the integral membrane proteins Itis typical for integral membrane proteins that they are embedded into the phospholipid bilayer GPCRs belong to the membrane proteins and are also called TTM receptors since they consist of 7 transmembrane domains which cross the lipid bilayer These transmembrane domains are connected by sections with some few up to some hundreds of amino acids which are located in the aequeous extra and intracellular sides of the lipid bilayer Within the first molecular modelling studies of GPCRs the
120. e Purinoceptors Appendix 167 Cannabinoid Platelet activating factor Gonadotropin releasing hormone Gonadotropin releasing hormone Adipokinetic hormone like Corazonin Gonadotropin releasing hormone other Thyrotropin releasing hormone amp Secretagogue Thyrotropin releasing hormone Growth hormone secretagogue Growth hormone secretagogue like Ecdysis triggering hormone ETHR Melatonin Viral Lysosphingolipid amp LPA EDG Leukotriene B4 receptor Orphan Other Putative neurotransmitters SREB Mas proto oncogene amp Mas related MRGs RDCI EBV induced ORPH LGR like hormone receptors GPR GPR45 ike Cysteinyl leukotriene G protein coupled bile acid receptor Free fatty acid receptor GP40 GP41 GP43 Class B secretin like Calcitonin Corticotropin releasing factor Gastric inhibitory peptide Glucagon Growth hormone releasing hormone Parathyroid hormone PACAP Secretin Vasoactive intestinal polypeptide Diuretic hormone EMRI 168 Appendix Latrophilin Brain specific angiogenesis inhibitor BAD Methuselah like proteins MTH Cadherin EGF LAG CELSR Very large G protein coupled receptor Class C metabotropic glutamate pheromone Metabotropic glutamate Calcium sensing like Putative pheromone receptors GABA B Orphan GPCR5 Orphan GPCR6 Bridge of sevenless
121. e sequence of upper case characters in the second field in all the lines of the file data using the pattern range 7 gt cat data tr d A Z d As a consequence of removing the characters in each data line the 22 output exhibits two adjactent characters which are to replaced by a 32 single character with the help of a further instance of the tr command gt cat data tr d A Z tr s J wc syntax wc 1 file wc m file explanation In its first form the command wc writes out the number of lines of file The second form of the wc command counts the characters within file example Count the lines of the file data gt wc 1 data An example of wc using the option m for counting characters is already presented in the section Command Substitution above 152 11 Important UNIX LINUX Commands 11 5 Loops Statements of the Tcsh Shell Loops are very helpful in solving problems by combining arbitrary commands and executing them repeatedly Two loop constructs are available in the tcsh shell First we mention the foreach loop foreach loop syntax foreach variable valuel value2 command1 command2 end explanation and examples The command sequence is executed for each of the values valuel value2 Afterwards the loop exits Suppose we got a lot of data files Each of them is named with the starting character x To save these files we will renam
122. e them enclosing their names in Note that a command like mv x x will not work because the shell will not distinguish between source and destination files Thus we will make use of the foreach loop gt foreach i x gt mv i Si gt end The foreach statement defines a variable i and substitutes for x all file names beginning with x in the current working directory The loop statement say the mv command now moves one file after the other with the help of a variable substitution Finally the loop statements are finished by the end statement A second possibility to form a loop is realized by the while loop while loop syntax while expression command1 command2 end 11 6 Working with Shell Scripts 153 explanation and examples The while expression is evaluated and has value 1 if it is of arithmetic type with value not equal to zero or if it is an expression which evaluates to true whereas in all other cases expression has a value zero Now the command sequence is executed as long as the while expression has the value 1 The user has to provide a command altering the value of this expression in order to leave the loop after a certain number of runs Given the following sequence of DNA bases which is stored in a variable named base gt set base atgtctttcctcccaggaatgacc a After testing that the remainder of the number of characters in base indicated by the character divided by t
123. ed methods allow for estimating the entropy term of a system in principle which is given mainly by the vibration modes So if we deal with a system comprised of N sites we have to determine 3 N 6 vibration modes i e for N 10 000 there are nearly 30 000 vibrational terms to be computed Further on there is another problem arising from the modes belonging to transition states Since we are interested in equilibrium states and get a lot of transition modes we have to change the geometry of our system in a way that only real vibrational modes appear which is a very tedious task Many of the vibrational modes describe inter nal rotations around bonds characterized by low frequencies and therefore make an unacceptable large contribution to the overall vibration energy An exact treatment of this motion is not available up to now The prediction of the entropy term A S in this context is a very difficult matter and consequently the results are not reliable Because of this difficulties in almost all studies based on the mentioned methods also called single point calculations only the potential energy terms or the allowed energy levels of the system are used for a qualitative discussion of its behaviour To overcome the problems caused by single point calculations molecular dynamic studies MD on biological systems have to be carried out These methods make use of the equation of motion introduced by Newton to compute the time evolution of
124. ediction by molecular dynamics simulation Biophys J 73 2972 2979 IUPHAR 2000 Committee on receptor nomenclature and drug classification The IUPHAR compendium of receptor characterization and classification 2nd edn IUPHAR Media London 212 References Ivanov AA Baskin II Palyulin VA Piccagli L Baraldi PG Zefirov NS 2005 Molecular modelling and molecular dynamics simulation of the human A gt B adenosine receptor The study of the possible binding modes of the 2 receptor antagonists J Med Chem 48 6813 6820 Jaakola VP Griffith MT Hanson MA Cherezov V Chien YET Lane JR Ijzerman AP Stevens RC 2008 The 2 6 angstrom crystal structure of a human adenosine receptor bound to an antagonist Science 322 1211 1217 Jacoby E Bouhelal R Gerspacher M Seuwen K 2006 The 7TM G protein coupled receptor target family ChemMedChem 1 760 782 Jensen F 1999 Introduction to computational chemistry Wiley Chichester Jongejan A Bruysters M Ballesteros JA Haaksma E Bakker RA Pardo L Leurs R 2005 Linking agonist binding to histamine receptor activation Nat Chem Biol 1 98 103 Jongejan A Lim HD Smits RA de Esch IJP Haaksma E Leurs R 2008 Delineation of agonist binding to the human histamine H4 receptor using mutational analysis homology modeling and ab initio calculations J Chem Inf Model 48 1455 1463 Jorgensen WL Maxwell DS Tirado Rives J 1996 Development and testing of the OPLS all atom force field on conf
125. ein coupled receptors lessons from the crystal structure of rhodopsin Prot Struct Funct Bioinfor 64 673 690 Menikarachchi LC Gascon JA 2008 Optimization of cutting schemes for the evaluation of molecular electrostatic potentials in proteins via Moving Domain QM MM J Mol Model 14 1 9 Metropolis N 1987 The beginning of the Monte Carlo method Los Alamos Sci 12 125 130 Monard G Merz KM 1999 Combined quantum mechanical molecular mechanical methodologies applied to biomolecular systems Acc Chem Res 32 904 911 Moukhametzianov R Warne T Edwards PC Serrano Vega MJ Leslie AGW Tate CG Schertler GFX 2011 Two distinct conformations of helix 6 observed in antagonist bound structures of B adrenergic receptor Proc Natl Acad Sci USA 108 8228 8232 Mustafi D Palczewski K 2009 Topology of class A G protein coupled receptors insights gained from crystal structures of rhodopsins adrenergic and adenosine receptors Mol Pharmacol 75 1 12 Oldham WM Hamm HE 2006 Structural basis of function in heterotrimeric G proteins Q Rev Biophys 39 117 166 Oldham WM Hamm 2008 Heterotrimeric G protein activation by G protein coupled receptors Nat Rev Mol Cell Biol 9 60 71 Oliveira L Paiva PB Paiva ACM Vriend G 2003 Sequence analysis reveals how G protein coupled receptors transduce the signal to the G protein Proteins 52 553 560 Oostenbrink C Villa A Mark AE van Gunsteren WF 2004 A biomolecular force field based on the
126. ence concentration of 1 mol l which results from theoretical considerations Summarizing all the energy terms leads to T zi F RT n 10 9 It should be noted that the quantities Z u and c are dependent on the system variables pressure and temperature Generally we are interested in ligand receptor interactions taking place at constant pressure and temperature so we will not use the explicit functional notation of T M p T and c p T Moreover the quantity u does not depend on the concentration of any solute present in the solution After discussing the fundamental thermodynamic function 10 9 we have to deal with the question of applying this concept to the ligand receptor interaction resulting in the chemical equilibrium according to Eq 10 1 On the one hand we have a solution possibly provided with an electrostatic potential containing the ligand L and a ligand free receptor R embedded in its membrane and both L and R are generally charged The electrochemical potentials read as follows A C u 10 10 x C RT In za F 10 11 134 10 Thermodynamics of Ligand Receptor Interaction where is the reference potential of the ligand with respect to the solvent 1 6 water and is the reference potential of the receptor embedded in the membrane but in contact with the solvent just as the ligand L Because of the
127. equals the equilibrium constant K of the process Eq 10 1 uta ut 10 15 CLR Co Je U E cr co CR co The left hand side of Eq 10 15 is defined as the reference Gibbs energy A G of the reaction in the case of constant pressure and constant temperature 10 16 AG UR 10 17 10 3 Thermodynamic Basics 135 Thus we have the fundamental equation valid for all types of reaction taking place at constant pressure and temperature AG RTIn 10 18 Note that in the framework of an exact thermodynamic treatment of chemical re actions the equilibrium constant K does not exhibit any unit Nevertheless nearly all papers dealing with the determination of equilibrium constants of the ligand binding process provide units like nM or uM for example in connection with an thermodynamic equilibrium constant This mistake results from omitting the refer ence concentration and exhibits serious difficulties when calculating the energy quantity Getting the Gibbs energy of reaction 10 1 the Eq 10 18 is to be used but the evaluation of the logarithm of a quantity taking a unit does not make any sense So how can we get the desired result in this case in an exact manner Because co is defined as 1 mol l the given equilibrium constants have to be converted into a molar quantity and only the number is to be used in all subsequent calculations If for example the di
128. er that the script performs some calculations and then it stops in order to ask you if protonation states of amino acids should be changed Here answer no by typing a Subsequently the command pdb2gmx is called within vnd2gro and you are asked to choose an appropriate force field For example type 4 Now vmd2gro performs some time consuming calculations like generation of a topology file After some minutes vmd2gro should have finished Now you should have some new files in your current working directory membrane gro protein autopsf gro protein autopsf gro protein autopsf topandposre itp Thefilesmembrane groandprotein autopsf gro contain the coordinates relevant for the further steps In membrane gro the POPC lipid bilayer with a hole and in an appropriate site notation is given Be aware that the POPC in this notation can only be used with the parameters available in internet http moose bio ucalgary ca index php page Structures Topologies and shown explicitly in the appendix POPC Pa rameters The file protein autopsf gro contains the coordinates of the aligned protein and the file protein autopsf top is the corresponding topology file The coordinates of both gro files membrane gro and protein_ autopsf gro can be combined within one gro file containing now the protein and lipids To do so one can use the following LINUX command sequence 46 5 Lipids gt set nr prot l protein autopsf
129. eriodicity the term n 2 describes a rotation with 180 periodicity and the term n 3 describes a rotation with 120 periodicity In GROMACS the proper dihedral angles are defined according to the IU PAC IUB convention van der Spoel et al 2005 Therein is the angle between the plane ABC and the plane BCD Zero corresponds to the cis configuration this means A and D are on the same side van der Spoel et al 2005 In GROMACS the following Eq 9 7 is used k 1 cos no o 9 7 124 9 Force Fields 9 1 4 The van der Waals Energy The interaction between atoms which are not connected by bonds is described by the van der Waals energy The van der Waals energy is often described by the Lennard Jones potential Er Eq 9 8 4 __ CAB AB Ege 9 8 parameters for the interaction between two atoms and B r actual distance between two atoms A and B Instead of the above equation often a more prominent Eq 9 9 is used pussa E amp Ap parameter for interaction between two atoms B oag parameter for interaction between two atoms A and B 9 1 5 The Electrostatic Energy The electrostatic interaction between two atoms which are not bonded is represented by the following Eq 9 10 1 a 9 10 4 r 444 partial charges on the atoms A and B r distance between the atoms A and B vacuum permittivity dielectric constant of a medium 9 2
130. ers The value of each field is referenced by the notation 4 where denotes the field number starting at 1 The special notation 50 refers to the entire line of an input file Actions without any patterns will be performed for each input line As special cases the patterns and END mark actions which will be performed before reading the first line of input and after the last input line has been processed Because of the versatility of this command the reader is strongly recommended to contact the manual page for a complete description of gawk so the next section will contain 11 4 Discussion of Selected LINUX Commands 147 only some simple applications Extensive examples making use of gawk may be found in Chap 7 and Sect 11 7 example Given the file data containing information about a very large molecule one line per atom we want to print the x y and z coordinates of some atoms located in columns 6 8 and 10 beginning at line 2500 and ending at line 3456 The appropriate values will be stored in a file named outdat command would look like this gt gawk NR 2500 6 NR lt 3456 print 6 8 10 data gt outdat The pattern NR gt 2500 amp amp NR lt 3456 uses the built in variable NR which holds the actual line number The notations gt and lt represent the relational operators greater than and less than whereas the symbol amp
131. f the human histamine H4 receptor to the human histamine H receptor is shown in Fig 3 10 3 4 Homology Modelling 3 4 1 Modelling of the Transmembrane Domains The helical transmembrane domains can be easily modelled straight forward There fore only the amino acid side chains have to be changed into the side chain of the destination with appropriate modelling software 3 4 2 Modelling of Loops In general the transmembrane domains of different GPCRs consist of the same num ber of amino acids Thus the homology modelling of transmembrane domains is quite easy and can be performed straight forward In case of intra or extracellu lar loops which are connecting the transmembrane domains differences in number of amino acids of a loop between different GPCRs can occur This is the case for the E2 E3 loop between hH R and hH4R Fig 3 10 Small gaps can be closed with loop search modules by using appropriate software For some biogenic amine 24 3 Sequence Alignment and Homology Modelling E2 loop Fig 3 11 Different conformations of the E2 loop based on crystal structures receptors an influence of extracellular loops especially the E2 loop onto the bind ing of ligands to the receptor was shown Lim et al 2008 Brunskole et al 2011 Thus a correct modelling of the loops is very important Most of the loops are re solved by crystal structures However this is often not the case with regard to the extracellular loop
132. fact that both the ligand and the receptor are located in the same environment the electrostatic potential acting on each other is the same Therefore we use the same quantity in Eqs 10 10 and 10 11 On the other hand we have the complex LR containing the ligand in the binding pocket of the receptor situated in the same solvent system as the ligand and the empty receptor and therefore subjected to the same electrostatic potential So its electrochemical potential reads CLR Ug RT n p 10 12 Co In case of a chemical equilibrium at constant pressure and constant temperature the second law of thermodynamics states that the sum of the electrochemical potentials of the products right hand side of Eq 10 1 equals the sum of the electrochemical potentials of the educts left hand side of Eq 10 1 o CLR Lip RT In zrRF CL CR Because the ligand the receptor and the ligand receptor complex are charged gen erally appropriate counter ions have to be present in an electrically neutral solution For the discussion of the thermodynamics of the association process we presuppose that these counter ions do not influence the formation of the ligand receptor complex Due to the following equation ZLR ZL ZR 40 14 the terms containing the electrical potential cancel and after rearrangement we arrive at CLR Co n 1 where the argument of the logarithmic term
133. file out tcl will be created on the fly echo n Basename of membrane file set mem 5 lt echo Missing pdb file mem pdb exit 1 else if e mem psf then echo Missing psf file mem psf exit 1 PPRPPRPRRRRR FR 1 2 3 4 5 if e mem pdb then 6 7 8 9 0 5 5 21 22 23 Embedding a GPCR into a Lipid Bilayer 47 endif echo n Basename of aligned protein file 24 set prot 5 lt 25 26 if e prot pdb then 27 echo Missing pdb file prot pdb 28 exit 1 29 else if e prot psf then 30 echo Missing psf file prot psf 31 exit 1 32 endif 33 34 echo n Basename of output file protein membrane 35 set out lt 36 37 if e S out pdb then 38 echo File out pdb exists 39 echo Rename existing file or choose new file name and start again 40 exit 1 41 else if S out psf then 42 echo File out psf exists 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 echo Rename existing file or choose new file name and start again exit 1 endif Create and start tcl script out tcl if e out tcl then echo Tcl script file out tcl exists Remove or rename it exit 1 endif Substitutions for MEM PROT and OUT in Tcl script part set begin tcl grep n START 0 cut d f1 echo begin tcl tail n begin tcl 0 sed e s
134. free enthalpy of hydration and solvation the GROMOS force field parameter sets 53A5 and 53A6 J Comput Chem 25 1656 1676 Overington JP Bissan AL Hopkins L 2006 How many drug targets are there Nat Rev Drug Discov 5 993 996 Palczewski K Kumasaka T Hori T Behnke CA Motoshima H Fox BA LeTrong I Teller DC Okada T Stenkamp RE Yamamoto M Miyano M 2000 Crystal structure of rhodopsin a G protein coupled receptor Science 289 739 745 Pardo D Deupi X D lker N Lopez Rodriguez ML Campillo M 2007 The role of internal water molecules in the structure and function of the rhodopsin familiy of G protein coupled receptors Chem Bio Chem 8 19 24 Park JH Scheerer P Hofmann KP Choe HW Ernst OP 2008 Crystal structure of the ligand free G protein coupled receptor opsin Nature 454 183 187 Pei Y Mercier RW Anday JK Thakur GA Zvonok AM Hurst D Reggio PH Janero DR Makriyannis A 2008 Ligand binding architecture of human CB2 cannabinoid receptor ev idence for receptor subtype specific binding motif and modelling GPCR activation Chem Biol 15 1207 1219 Pierce KL Premont RT Lefkowitz RJ 2002 Seven transmembrane receptors Nat Rev Mol Cell Biol 3 639 650 Preuss H Ghorai P Kraus A Dove S Buschauer A Seifert R 2007 Point mutations in the second extracellular loop of the histamine gt receptor do not affect the species selective activity of guanidine type agonists Naunyn Schmiedeberg s Arch Pharmacol 376 253 264 Raimondi
135. g AH and AS One of the methods to determine A H is given by the isothermal titration calorimetry To elucidate the basic principles of this method we will consider a solution contain ing the receptor R with a certain concentration c Assuming constant temperature and constant pressure we will add a small amount of a stock solution of the ligand L in a way that its actual concentration in the titrand solution is c7 The reaction Eq 10 1 will take place and an equivalent portion of the ligand and receptor will form the complex LR with a concentration dependent on the up to now unknown equilibrium constant K Because of the chemical process an enthalpy change will occur which we are able to determine by the mentioned calorimetric method As suming the receptor concentration is small compared to the ligand concentration and neglecting the increase in the system volume caused by adding the stock solution the concentration of the free ligand nearly remains constant and the amount of complex formed after establishing the chemical equilibrium is given by the relation CLRCo 10 22 CL ck where is the unknown equilibrium constant and the term crag denotes concentration of the free receptor cg Solving Eq 10 22 for c s yields the following result c CLR 10 23 Co jy KZ Co The corresponding change in enthalpy Ah per unit volume for dilute solutions is then given by Ah cLRA H 10
136. gment no information at protein data bank http www pdb org no information at protein data bank http www pdb org N UniProtKB P29274 literature Jaakola et al 2008 pdb code 2YDO X ray diffraction H Ho UniProtKB P29274 literature Lebon et al 2011 Appendix 195 naa O mutation UniProtKB resolution 271A molecule adenosine receptor A gt lysozyme chimera fragment no information at protein data bank http www pdb org no information at protein data bank http www pdb org UniProtKB P29274 Xu et al 2011 196 Appendix resolution 330A mutation AS4L TSSA 22 V259A L202A L235A S277A H fmoteeale adenosine mutation 541 TSA RIOTA KIDDA L202A LA VEA S277A UniProtKB P29274 Dore et al 2011 Appendix 197 method X ray diffraction resolution 260 molecule adenosine receptor Axx i O mutation AS4L T88A ROTA 22 L202A L235A V239A S277A UniProtKB 29274 literature Dore et al 2011 198 Appendix Important Amino Acid Sequences Related to the Crystal Structures of GPCRs Source http www expasy org bovine rhod opsin my ss T C SoS 10 20 30 40 50 60 MNGTEGPNFY VPFSNKTGVV RSPFEAPQYY LAEPWOFSML AAYMFLLIML GFPINFLTLY 70 80 90 100 110 120 VTVOH
137. gro cut d 1 J gt set nr mem l membrane gro cut d f1 d gt 811 sites nr prot mem 6 gt echo Protein in lipid bilayer prot lip gro gt echo all sites gt gt prot 1 gt tail n 3 protein autopsf gro head 1 gt gt prot lip gro gt tail n 3 membrane gro gt gt protein_lip gro Now you should have your protein and the lipid bilayer in the file protein_lip gro Of course you can do the analogue manipulations manu ally with an editor In protein_lip gro the lipid sites start again with number 1 To obtain a subsequent numbering and centring the structure in the simulation box use the GROMACS command edi tconf gt editconf f protein lip gro c o system gro The user of vmd2gro and the tcl script combine tcl developed by Bal abin and published at http www ks uiuc edu Research vmd plugins membrane see lines 192 276 in vmd2gro shown below should add the absolute path for top 81127 prot lipid inp in line 207 The script vmd2gro is shown the following 1 bin tcsh 2 3 4 vmd2gro tcsh script to convert vmd format to gro format 4 for a lipid membrane protein complex 6 Detect and remove collisions between protein membrane using a Tcl script for VMD 7 script statements follow a line beginning with the the pattern START TCL 9 Variables containing file names mem prot out 10 Tcl script
138. h P Jensen AA 2007 Structure pharmacology and therapeutic prospects of family G protein coupled receptors Curr Drug Targets 8 169 184 Brown N Lewis RA 2006 Exploiting QSAR methods in lead optimization Curr Opin Drug Discov Devel 9 419 424 Brunskole I Strasser A Seifert R Buschauer A 2011 Role of the second and third extracellu lar loops of the histamine H4 receptor in receptor activation Naunyn Schmiedeberg s Arch Pharmacol 384 301 317 Cabani S Gianni P Mollica V Lepori L 1981 Group contributions to the thermodynamic properties of non ionic organic solutes in dilute aqueous solution J Solution Chem 10 562 505 Cai K Itoh Y Khorana HG 2001 Mapping of contact sites in complex formation between transducin and light activated rhodopsin by covalent crosslinking use of a photoactivatable reagent Proc Natl Acad Sci USA 98 4877 4882 Carloni P Rothlisberger U Parinello M 2002 The role and perspective of ab initio molecular dynamics in the study of biological systems Acc Chem Res 35 455 464 A Strasser H J Wittmann Modelling of GPCRs 209 DOI 10 1007 978 94 007 4596 4 Springer Science Business Media Dordrecht 2013 210 References Chalmers DT Behan DP 2002 The use of constitutively active GPCRs in drug discovery and functional genomics Nature Rev Drug Discov 1 599 608 Cherezov V Rosenbaum DM Hanson MA Rasmussen SGF Thian FS Kobilka TS Choi HJ Kuhn P Weis WI Kobilka BK Stevens RS 2007 High resolu
139. hH4R and ligand This is in good accordance to higher affinity of PH 5 compared to PH 1 Table 7 7 However using the thermodynamic integration method this qualitative explanation could be quantified Table 7 8 A correlation of the experimentally determined pK values with the predicted changes in Gibbs energy of solvation for the transfer of the ligands from aqueous phase into the binding pocket of hH4R is presented in Fig 7 10 As revealed by Fig 7 10 the correlation between predicted and experimental data is quite well In this case there is rather no difference if the predicted value for the transfer of the ligand from aqueous phase in to binding pocket of hH4R or the predicted AG value of the ligand in the binding pocket of hH4R is correlated with sol the experimentally determined pK value However the more accurate way would be 102 7 Calculation of Gibbs Energy of Solvation Table 7 8 Calculated Gibbs energies of solvation for phenylhistamines in water in the binding pocket of hH4R and for the transfer of aqueous phase into the binding pocket of hH4R at a temperature of 298 15 K Wittmann et al 2011 AG wat L hAgR L wat hH4R kJ mol kJ mol kJ mol PH 1 204 1 477 15 273 16 2 224 2 525 11 301 13 PH 3 215 2 516 10 301 12 PH 4 190 2 512 19 322 21 5 205 3 544 13 340 16 6 202 2 517 19 315 2
140. hand this fact is supported by site directed mutagenesis studies However there is only very few knowledge about the ligand recognition on receptor surface and the guiding of the ligand into the binding pocket of a GPCR With experimental studies the whole binding process on molecular level can not be studied in detail In general molecular modelling studies are able to give these insights on molecular level Since the ligand binding is of dynamic nature one would think about using molecular dynamic simulations to study the binding process of a ligand However until now no study observing the complete binding process of a ligand from the extracellular 8 2 Process of Ligand Binding from the Extracellular Side into the Binding 113 side into the binding pocket of a receptor was published The reason for this lack is the large computing time due to the time scale of ligand binding process Some studies used the technique of steered molecular dynamics Isralewitz et al 1997 Kosztin et al 1999 In order to get more insight onto the ligand binding process on molecular level the algorithm LigPath is described in literature as an alternative method Strasser and Wittmann 2007a b 2010 The following part of Chap 8 2 is mainly based on articles in literature Strasser and Wittmann 2007b 2010 Copyright by Springer with permission from Springer Antagonists or inverse agonists are suggested to stabilize the inactive conformation of the
141. he E2 loop by a disulfide bridge with the upper part of TM III Fig 3 10 www allitebooks com 3 4 Homology Modelling 25 E2 loop E2 loop Fig 3 12 Different numbers of disulfide bridges in the E2 loop 3 4 3 Modelling of Internal Water A detailed analysis of the crystal structures of GPCRs reveals that there are internal highly conserved water molecules present Fig 3 13 Several studies showed that these water molecules are involved in the hydrogen bonding within the receptor Based on the published data it can be suggested that these water molecules are essential for stabilizing the receptor or important for receptor activation Pardo et al 2007 Thus in order to generate a stable receptor model the water molecules which are localized crystallized within the receptor should be included into the homology model 3 4 4 Modelling of the C Terminal Part of the Subunit or the Whole Go Subunit Based on several studies it is suggested that a GPCR in its active conformation interacts in the intracellular part with the Go subunit There is only small knowledge about the receptor G protein interaction However recently the crystal structure of opsin cocrystallized with eleven amino acids of the C terminus of the Ga subunit Scheerer et al 2008 and a complete GPCR G protein complex Rasmussen et al 2011 were published A detailed analysis of the corresponding crystal structures 3DQB 3SN6 shows that the C termi
142. he second site C1 CH2 and the first site C4 CH3 is defined There p is related with the value of 0 153 nm whereas the force constant k is related with the value of 7150000 0 kJ mol The related dependence of Ebona in dependence of the distance is given in Fig 9 5 In the section angles the parameters for the bending energy between three bonded atoms are defined Let s look onto the first parameter line of this section 1 2 3 2 109 5 520 0 109 5 520 0 CA Cl C2 Within this line the bending energy between the first C4 CH3 second CH2 and the third site O2 is defined There 25 109 55 and kABC 520 0 kJ mol The corresponding course of the bending energy is shown in Fig 9 6 In the section dihedrals the parameters for the torsional energy between four atoms are defined Let s look onto the first parameter line of this section 1 2 3 4 1 0 0 1 3 3 0 0 1 3 3 dih C4 C102 H2 128 9 Force Fields Fig 9 7 in dependence 3 of the torsion angle example dihedral angle between C4 O2 and H2 of ethanol see above Etors kJ mol Fig 9 8 E in dependence of the distance r between two atoms example coulomb interaction between C4 and O2 of ethanol see above kJ mol 0 00 0 25 0 50 0 75 1 00 1 25 1 50 r nm Fig 9 9 in dependence of the distance r between two atoms example Lennard Jones interaction between C4 and O2 of ethanol see a
143. he standard output As another example the command line gt echo x would not be expanded in the sense of filename and variable substitution but simply outputs the string x Strings enclosed in double quotes will still be command and variable expanded Thus the result of the command gt echo x will have 123 as its output 11 4 Discussion of Selected LINUX Commands The following section lists some important LINUX commands for processing ASCII i e human readable files Each command section is divided into three subsections syntax explanation and example The syntax subsection only mentions the most relevant instances of the command For a complete description the reader is encouraged to consult the corresponding LINUX manual page The explanation subsection gives some more information of the command which is finally discussed in the example section with the help of simple exercises In most cases the contents of a file which will be created later on within an exercise related to the command cat see below will be processed To reproduce the following examples the reader is supposed to have opened a shell terminal primarily a tcsh shell terminal For the use of a bash shell terminal one has to take into account a different meaning of the shell meta characters cat syntax cat file cat file explanation The first form prints the contents of a file to standard output whereas the second form may be
144. he width of the lipid bilayer and you perform the solvation you may get another artefact as shown in Fig 5 14 Here water channels layers through the lipid bilayer are established This is a completely wrong artefact and you should not do simulations with such systems If you detect such a water channel layer after solvation you may remove the solvent decrease the box size in an appropriate manner and solvate again These steps should be repeated until the water channel layer through the lipid bilayer is no longer observed After solvation the system should be minimized using the GROMACS command grompp and mdrun see Chap 6 In the last step the system has to be neutralized see Chap 6 In the following box a short stepwise summary of the alignment of a GPCR in the lipid bilayer is given Construct a lipid bilayer or obtain it via download of a server Align your GPCR correctly into the lipid bilayer Remove the lipid molecules which overlap with the GPCR Center the system in the simulation box Minimize the system with GROMACS Equilibrate the lipids around the GPCR position restraints should be put onto all sites of the protein using appropriate GROMACS commands Solvate your lipid GPCR complex with water in an appropriate manner see also Chap 6 Minimize the simulation box Neutralize the system and minimize again see also Chap 6 Chapter 6 Minimization and Molecul
145. his case you can use your own C code or gawk Thus in the following it is shown how to write an integration routine by yourself In literature a large number of numeric methods with regard to numeric integration are described like the Simpson s rule or the trapezoidal rule A Fig 7 2 6 as function of 293 0 K the coupling parameter for ethanol in water ethanol in water 200 100 dG d kJ mol 92 7 Calculation of Gibbs Energy of Solvation Fig 7 3 46 as function of 293 0 K the coupling parameter for ethanol in vaccuo ethanol in vaccum 0 02 5 0 015 5 0 010 E 3 0 000 0 0 0 2 0 4 0 6 0 8 1 0 aG 7 4 Yaa as function of 293 0 K the coupling parameter for transfer of ethanol Rida from vaccuo into water vaccuo into water this course was calculated based on the 100 data presented in Figs 7 2 and 7 3 dGId2 kJ mol very simple and stable numeric method is the trapezoidal rule and thus we focus onto this The formula for the trapezoidal rule is given by Eq 7 46 Xoth amp Xo f Gro h 7 46 wl m Via summation over all intervals Eq 7 47 is obtained h s 2 147 Be aware that the equation mentioned above is only valid if n intervals of equal width are used In all other cases a modified formula has to be used Xn 1 n 1 f re xi CPG
146. hree yields zero gt expr base 3 we are going to split this sequence into triples and write them to standard output First we define a variable n holding the number of base characters and a loop variable named i is initialized with 1 To create the first triple we cut the characters with number i to 1 2 represented by variable j and print them out Afterwards the value i is incremented by three and we proceed as long as i is less than n gt set n base gt set i 1 gt while i lt n J gt j i 2 J gt echo base cut c i j gt i Si 3 d gt end _ Note the incrementation of variable i in the command just before the end statement assures the while loop to be exited if i is equal or greater than n 11 6 Working with Shell Scripts Referring to our last exercise we recognize two disadvantages Firstly we have to do a lot of work prior to the while statement For each new problem we have to repeat the steps dealing with creating shell variables and test the number of characters via expr After that we have to execute all the statements of the while loop Secondly a mistyping within the while block makes it necessary to abort writing and to repeat all the loop statements Making use of a so called shell script represents a possibility to avoid all these difficulties A shell script is an ASCII file containing all commands 154 11 Important UNIX LINUX Commands necessary to sol
147. iend G 1990 WHAT IF a molecular modeling and drug design program J Mol Graph 8 52 56 Wacker D Genalti G Brown MA Katritch V Abagyan R Cherezov V Stevens RC 2010 Conserved binding mode of human 2 adrenergic receptor inverse agonists and antagonist revealed by X ray crystallography J Am Chem Soc 132 11443 11445 Wagner E Wittmann HJ Elz S Strasser A 2011 Mepyramine JNJ7777120 hybrid compounds show high affinity to hH R but low affinity to hH4R Bioorg Med Chem Lett 21 6274 6280 Warne A Serrano Vega MJ Baker JG Moukhametzianov R Edward PC Henderson R Leslie AGW Tate CG Schertler GFX 2008 Structure of the D adrenergic G protein coupled receptor Nature 454 486 491 Warne A Moukhametzianov R Baker JG Nehme R Edwards PC Leslie AGW Schertler GFX Tate CG 2011 The structural basis for agonist and partial agonist action on a B adrenergic receptor Nature 469 241 244 Weiland GA Minneman KP Molinoff PB 1979 Fundamental difference between the molecular interactions of agonists and antagonists with the B adrenergic receptor Nature 281 114 117 Wittmann HJ Seifert R Strasser A 2009 Contribution of binding enthalpy and entropy to affinity of antagonist and agonist binding at human and guinea pig histamine H receptor Mol Pharmacol 76 25 37 Wittmann HJ Seifert R Strasser 2011 N methylated phenylhistamines exhibit affinity to the hH4R a pharmacological and molecular modelling study Naunyn Schmiedeberg s A
148. igPath algorithm Fig 8 11 dotted line Besides that a systematic potential energy surface scan presented in Fig 8 11 was performed The potential surface scan reveals a minimum energy path that is in good accordance to the minimum energy pathway calculated by LigPath Fig 8 11 dotted line Thus the LigPath algorithm can be used as alternative to a systematic energy surface scan This is advantageous with regard to a decreased computation time However the systematic surface scan gives more detailed insights onto the potential energy Fig 8 11 Potential energy L R surface for penetration of a partial agonist into the 0 4 binding pocket of a biogenic amine receptor Copyright by dup 0 3 Springer with permission E from Springer modified 3 9 02 E 0 1 0 0 2 5 2 1 5 1 0 5 L R LR rmsd nm S S Epot kJ mol 8 22 Process of Ligand Binding from the Extracellular Side into the Binding 117 55 18 1 5 sof xit 0 500 1000 1500 2000 generation generation Phe 52 Phe55 0 s p 3 t ida Pell 45 s rl 12 9 500 1000 1500 2000 0 500 1000 1500 2000 generation generation Tyr 5 0 30 5 60 80 gt lt 120 150 180 iN 0 500 1000 1500 2000 0 500 1000 1500 2000 generation generation Trp 48 T 48 304 p sd 9 242 E d 15 Ls gn
149. in the first step you have to generate your lipid bilayer with an appropriate width Fig 5 8 step 1 Subsequently the GPCR has to be aligned into the lipid bilayer A very good description in combination with the software vmd http www ks uiuc edu Research vmd is found at the following internet site http www ks uiuc edu Research vmd plugins membrane A detailed description is given at the mentioned site However in the following a short description of a slightly modified procedure using the script combine tcl available at http www ks uiuc edu Research vmd plugins membrane is presented For the following procedure you need the shell script vnd2gro which is shown later on The script vmd2gro was tested in combination with vnd 1 8 7 Be aware that in the presented version of vnd2gro the POPC molecules in vmd notation are transferd into the POPC notation used by Moose http moose bio ucalgary ca index php page Structures and Topologies Thus for further use with GROMACS you need the files lipid itp and popc itp Both are available at http moose bio ucalgary ca index php page 5 5 Embedding a GPCR into a Lipid Bilayer 43 T a ANS lt p e R MS 7 5 A 1 2 gt P sae lt ro SUA EE YA Y T v gt 7 m i gt Z 55 aN PV ERIT A WR OEE Fig 5 7 Artificial close contacts of the pr
150. in water cpp lib cpp define DPOSRES constraints all bonds constraint algorithm 1 unconstrained start yes or no as appropriate integrator sd1 tinit 0 dt 0 001 ps nsteps 1000000 nstcomm 1 Output control nstxout 1000 nstvout 1000 nstfout 0 nstlog 1000 nstenergy 1000 Neighbor searching 7 2 Examples Conceptual and Practical Considerations 97 nstlist 10 ns_type grid pbc xyz rlist Electrostatics coulombtype pme rcoulomb switch 0 rcoulomb 1 4 epsilon 1 0 epsilon rf 7 0 vdwtype Cut off rvdw switch 0 rvdw DispCorr EnerPres fourierspacing 0 3 35 fourier nx 0 fourier_ny 0 fourier nz 0 pme_order 4 ewald rtol le 5 ewald_geometry 3dc optimize_fft yes Temperature coupling tcoupl berendsen tc grps system tau_t 0 1 ref_t 298 15 Energy monitoring energygrps system Pressure coupling is on Pcoupl berendsen pcoupltype isotropic tau_p 0 5 015 015 0 005 0 0 0 compressibility 4 5e 5 4 5e 5 4 5 0 0 0 0 0 0 ref p Lc Generate velocites is on at 298 15 K gen vel yes gen_temp 298 15 gen_seed 173529 free_energy yes init_lambda 0 delta_lambda 0 000001 98 7 Calculation of Gibbs Energy of Solvation sc_alpha 1 5 sc_power 2 0 couple moltype EtOH couple lambda0 vdw q couple lambdal none couple intramol n
151. ined in this manner Another group of operators consists of the symbols lt gt gt gt known as file input output redirection Suppose a program named pgm which normally reads from the standard input providing a file named data pgm may get its input from this file instead from standard input pgm lt data To redirect output of a command to a file use the operator gt 515 al dir gt temp The output of the command 1s will be stored in a file named temp Note that an already existing file temp will be destroyed before redirecting output To append the output of a command to an existing file named data use the symbol gt gt 1s al dir gt gt data Additionally a command line may include meta characters which will be interpreted by the shell in a special manner also known as shell substitution Thus the original command line will be altered after that 11 3 Shell Substitutions The following section will deal with the most important shell substitutions 11 3 Shell Substitutions 141 11 3 1 File Name Substitution If a string contains any of the characters or the file name substitution occurs For instance to remove all objects from the current working directory we use the command gt rm r d Note in a basic UNIX environment the user is not prompted before removal and all files and directories will be lost with two exceptions If an object
152. ing crystal structure if available shows sometimes differences with regard to the helical region Let us for example look onto TM III of the human adrenergic B receptor The transmembrane region is defined from Glu 107 until Val 129 at expasy Fig 3 9a However a closer look onto the corresponding domain at the crystal structure shows that the helical structure is much longer at both sides Fig 3 9b Thus the domains are adopted with regard to the amino acid sequence in Fig 3 9c Additionally in Fig 3 9b the amio acids Glu 107 and Val 129 are men tioned Glu 6 and Val in the Ballesteros nomenclature Some additional amino acids are shown in the Ballesteros nomenclature in Fig 3 9c For the termini and the loops no corresponding nomenclature is available 3 3 3 Amino Acid Sequences Templates Before performing an amino acid sequence alignment one has to decide which structure should be used as template structure for homology modelling Meanwhile a lot of crystal structures of bovin rhodopsin or GPCRs like the human adrener gic B receptor or turkey adrenergic B receptor are available see Tab 3 1 and appendix Important Crystal Structures of GPCRs Source http www pdb org It cannot be decided overall which crystal structure should be used as a template for 3 3 Amino Acid Sequences and Sequence Alignment 21 N Terminus 1 MGQPGNGSAFLLAPNGSHAPDHDVTQQRDEVWVVGMGIVMSLIVLAIVFGNVLVIT S6 I1 loo E1 loo 57 AIAKFERLQTVTN
153. internal energy U of a system with fixed volume temperature and number of particles which will read as U H pir SS V T N pi Fi exp RH o d pidr 7 6 5 AED agar 7 7 k and T denote the Boltzmann constant and the temperature N is the total number of particles in the system and oy is a normalisation constant The integration is extended over all values of the momenta and coordinates of all species i present in the system The quantity Qy is called the partition function at constant volume Having a closer look onto the Eqs 7 6 and 7 7 U is identified as the mean value of the Hamiltonian function H over the so called phase space given by all the momenta and coordinates Referring to a system with fixed pressure temperature and number of particles we get H p T N 2 ario 0 pV exp where pidri T Jaz day 7 8 7 1 Theory Link Between Microscopic and Macroscopic World 71 H Pi r VIA 9 p tr Jagaiav 7 9 is the partition function at constant pressure with the normalisation constant Equations 7 8 and 7 9 contain the product of the pressure p and the volume V to transform the internal energy U into the enthalpy H which must not be mixed up with the Hamiltonian function H p r The Gibbs energy for a system at constant pressure temperature and number of particles reads where G kT ln Q 7 10 It should be ta
154. inus intracellular loops extracellular loops and trans membrane domains are given This information is very helpful for the sequence alignment later on In the section Sequence you can find the whole amino acid sequence of the protein For further proceeding on with the amio acid sequence like for sequence alignment it may be easier for you to download the amino acid sequence as fasta format To do so please click onto the string FASTA Now you get the amino acid sequence as simple ascii file 19 3 3 Amino Acid Sequences and Sequence Alignment S10 sedxoyy dyu 1 Asedx Jo L E za S su avon 3u u dx3 M N jexiod si asn 2104 5ptiop 9909 91 aseqabpaymouy 1024100 t 134 ey me 1 m SMON 15947 218 Buunjee j ONIS 5 1300 e un Did 58 puy euod sin Yat ui 2 M 5908916 224n052J 1e ndog 3jewpos pue saseqejep INU 1 55322 1 uod 824noses s neuuojulol8 815 211 vx eos 1 gwaun peuo Asedxo 5 o gt somossu ats Asya SER 153 won PR errog 9210598 grs e 20 3 Sequence Alignment and Homology Modelling Table 3 2 Highly conserved amino acid a
155. ion of Gibbs Energy of Solvation 7 1 Theory Link Between Microscopic and Macroscopic World In the next chapters a short summary with regard to link the microscopic and macro scopic world is given For a more detailed description the reader is referred to the literature van Gunsteren and Berendsen 1987 Jensen 1999 Frenkel and Smit 2002 van der Spoel et al 2005 7 1 1 Statistical Mechanical Basics In this chapter we deal with the problem to connect a model or a microscopic picture of matter to measurable macroscopic quantities Linking these two worlds represents the only possibility to validate models and gain insight into the molecular processes Referring to the chapter of thermodynamical basics we established a model for the ligand receptor interaction by formulating the equilibrium L R LR 7 1 characterized by its equilibrium constant a measurable quantity CLRCo 7 2 CLCR To understand the processes leading to this equilibrium constant on a molecular level we remember the fundamental equation resulting from the first and second law of thermodynamics in the case of constant pressure and temperature AG RT nK 7 3 Because we transfer the measurable quantity K into the energetic quantity AG we make the first move to answer our central question Obviously the next step is the A Strasser H J Wittmann Modelling of GPCRs 75 DOI 10 1007 978 94 007 4596 4_7 Springer Science Business Media D
156. irst mdp 18 grompp f md first o md first c system p system 19 wait 20 mdrun v s md first e md first o md first c after md g shortlog 21 wait 22 else 23 cp md mdp 24 k i 1 25 cp 5 k after md gro system gro 26 grompp f md o md c system p system 27 wait 28 mdrun v s md e md o md c after_md g shortlog 29 wait 30 endif 31 cd 32 i 33 end The grompp input file md_first mdp with exemplary parameters is shown below N t N O N P 9 9 09 09 C C Q C C Q N N N N N N N N BO B gt Q N P O XO 1 Ui iS QQ N O Q0 O UI i Q OL md first mdp MD Input file title define constraints constraint_algorithm unconstrained_start integrator tinit dt nsteps nstcomm Output control nstxout nstvout nstfout nstlog nstenergy Neighbor searching nstlist ns type pbc rlist Electrostatics coulombtype rcoulomb switch rcoulomb epsilon r epsilon rf vdwtype rvdw switch rvdw DispCorr fourierspacing fourier nx fourier ny fourier nz pme order ewald rtol optimize fft 6 Minimization and Molecular Dynamics System 11 DPOSRES 11 lincs yes 0 0 001 100000 ps 5000 5000 5000 7 0
157. is very use ful to perform the calculations for aqueous and gaseous phase as in two different sub directories aqueous and gaseous Additionally for each A calculation a separate subdirectory in the subdirectory aqueous or gaseous should be used Surely you can perform the simulations for each manually but this is very inefficient There fore it is more useful to use the shell script gibbs_energy shown below Using this script all simulations of the aqueous or gaseous phase can be performed 10 0 8 QQ N P PRR N Fa o 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 7 Calculation of Gibbs Energy of Solvation bin tcsh f set n 18 set base lambda set 1 set lambdas 0 0 0 05 0 1 0 2 0 3 0 4 0 45 0 5 0 55 0 6 0 7 0 8 0 9 0 95 0 975 0 99 0 995 T 0 while i lt n mkdir 5 641 base 551 cp ethanol top if i 1 then cp system_min gro cp md_first mdp grompp f md_first o md_first c system_min r system min p ethanol wait mdrun v md first e md first o md first c after md g shortlog wait else head n 65 md mdp md mdp echo init lambda 1ambdas i gt gt md mdp k i 1 cp base _ k after_md gro system_min gro grompp f md o md c system min r system min p ethanol wait mdrun v s md md o md c after md
158. istributed over a larger system volume V i e the molar concentration c will exhibit a lower value Moreover the displacement of the particles of each species present in the system is altered by the concentration dependent intermolecular interactions between the solute particles and between the solute and the solvent 10 3 Thermodynamic Basics 133 giving rise to the so called activity coefficient y of each species i The resulting term reads as Ci Yi Co RT In 10 6 where R is the gas constant T is the absolute temperature and In denotes the natural logarithm Very often the above expression is written in the form RT Ina 10 7 where a denotes the activity of species i in the solution It is worth mentioning that an activity coefficient may be formulated as an analytical expression only in the case of very simple systems for instance in the case of a solution of potassium chloride in water Biochemical systems however show very complex interactions and therefore it is impossible to represent the activity coefficient by a simple algebraic expression But for a dilute solution the mentioned interactions will become very small resulting in an activity coefficient near value 1 Restricting our considerations to a concentration range of about 107 to 1076 M neglecting the activity coefficient will be a good approximation and rewrites the third energy contribution as RT In lt 10 8 Co The quantity c is the so called refer
159. ite_sort dat To every site a function type second column and a force constant for each coordi nate third to fifth column has to be added Therefore we have to know how much sites should be administered with position constraints Because site_sort dat does not contain any empty lines the appropriate number can be easily obtained using the command we gt 1 site sort dat J In actual example there should be 12lines Thus one has to create a new file containing 1 1000 1000 1000 if each force constant should have the value 1000 12 times This can be done using the following command rm force dat gt set i 1 J gt while i lt 12 gt echo 1 1000 1000 1000 gt gt force dat gt Q i gt end 66 6 Minimization and Molecular Dynamics Now both files site sort dat and force dat can be easily combined using the command paste gt echo position restraints gt posre bb 1000 itp J gt paste site sort dat force dat gt gt posre bb 1000 itp J If you performed all commands correctly you should have the file posre bb 1000 itp with the following data position restraints 987 000 1000 1000 993 000 1000 1000 994 000 1000 1000 995 000 1000 1000 996 000 1000 1000 998 000 1000 1000 1002 000 1000 1000 1003 000 1000 1000 1004 000 1000 1000 1005 000 1000 1000 1011 000 1000 1000 1012 000 1000 1000 You see that the co
160. k 71 molecule guanine nucleotide binding protein G s subunit a isoforms short molecule guanine nucleotide binding protein G 1 G s G t subunit p mutation P54311 guanine nucleotide binding protein G 1 G s G o subunit y2 P63212 lysozyme p adrenergic receptor mutation C54T C97A 96 N187E P07550 00720 camelid antibody VHH fragment OH OH Rasmussen et al 2011 Appendix 185 turkey B adrenergic receptor pdb code 2VT4 X ray diffraction resolution 270 molecule p adrenergic receptor residues 33 243 272 276 279 367 P07700 Warne et al 2008 method X ray diffraction 3 00 molecule adrenergic receptor residues 33 243 272 276 279 367 yes mutation n HN UniProtKB 07700 literature Moukhametzianov et al 2011 186 Appendix 2YCX pdb code resolution _ 3 25 B adrenergic receptor residues 33 243 272 276 279 367 yes 2Y X ray diffraction 3 2 P07700 Moukhametzianov et al 2011 2 method X ray diffraction resolution 3 15 adrenergic receptor mutation P07700 Moukhametzianov et al 2011 yes Appendix 187 pdb code 2YCZ X ray diffraction UniProtKB P07700 Moukhametzianov et al 2011 pdb code 2Y00 X ray diffraction resolution 2 50 p adrenergic receptor residues 33 368 es mutation UniProtKB P0
161. k ko ko ko echo n Do you want to modify the protonation State of amino acid ARG ASP GLU HIS or LYS y n 97 echo k k k k k rd rr dd KKK KKK KKK KKK kck kck kock kck kck kck kock ck ck ck k ko kk 98 99 set answer 100 set answer echo answer tr y Y 101 102 set ARG 103 set ASP 104 set GLU 105 set HIS 106 set LYS 107 108 if Sanswer Y then 109 echo n Change protonation state of ARG y n 0 set h 1 set h echo h tr Y 2af wy then 3 set ARG arg 4 endif 5 116 echo n Change protonation state of ASP y m 117 set h lt 118 set h echo h tr y Y 119 if 5 then 120 set ASP asp 121 endif 122 123 echo n Change protonation state of GLU y n 124 set h lt 125 set h echo h tr Y 126 if then 127 set GLU glu 128 endif 129 130 echo n Change protonation state of HIS y n 131 set h 132 set h echo h tr Y 133 if h Y then 50 144 L45 148 149 134 135 136 137 138 139 140 141 142 143 146 47 150 151 52 53 set endif 5 Lipids his echo n Change protonation state of LYS y n set h lt set h echo h tr Y if Sh Y then set LYS endif endif n lys pdb2gmx f
162. ken into consideration that the Gibbs energy G does not represent a mean value like the internal energy U or the enthalpy H which will lead to new concepts in the calculation of this quantity in the framework of Molecular Dynamics So making use of the concepts of Statistical Mechanics we are able to calculate all important thermodynamical quantities after formulating the potential energy Epor We therefore should be able to calculate measurable quantities like the ligand receptor association constant and compare the results with experimental values in order to refine our models 7 1 2 From Potential Energy to the Chemical Potential To calculate the equilibrium constant for the association process Eq 7 1 we remember the equation from the chapter of thermodynamical basics AG wig 7 11 Because the chemical potential of each species LR L or R means its Gibbs energy per mole in accordance to Eq 7 10 we have to evaluate the partition function Q for con stant pressure and constant temperature of an appropriate system containing a num ber of particles LR L or R which equals the Avogadro number NA considering the particular reference state After defining the potential energy we have to inte grate over the whole phase space which indeed is a very difficult task as this function will not be given in a simple analytical form There are attempts to solve this problem with the so called Monte Carlo method Metrop
163. l 152 11 6 Working with Shell 153 11 7 A More Extensive Example 155 ea ee ere eee 161 lm 209 J d X TT 217 www allitebooks com Chapter 1 Introduction The knowledge about conformation of proteins and distinct interactions between a ligand and it s target protein is necessary to explain pharmacological data on a molecular level Additionally based on this knowledge it may be possible to de velop new potent drugs more efficiently But how get these insights on a molecular level Several experimental techniques like mutagenesis studies combined with pharmacological investigations may give hints about amino acids being important for stability of a protein or being important for the interaction between ligand and protein But these studies exhibit no information about energetics and hydrogen bond networking for example Other techniques like determination of structures of proteins or protein ligand complexes by NMR or crystallography are very use ful to obtain information about secondary tertiary or quartary structures of proteins http www pdb org However these experiments are time expensive and cannot be performed for each system of interest like on an assembly line Additionally it has to be taken into account that crystal structures represent a solid phase but proteins are in gener
164. l 1996 the stretching energy is described by the following Eq 9 3 2 1 Erma P Y 9 3 9 1 2 The Bending Energy The bending energy E angie describes the bending of an angle between the three atoms A B and C with a bond between A and B and between B and C Fig 9 2 The bending energy can be represented by the following harmonic approximation 9 4 Eangle ABC ABC 9 4 a C reference angle between the atoms A B and C o PC actual angle between the atoms A B and C constant for the angle between A B and 9 1 The Force Field Energy 123 Fig 9 3 Definition of the torsional angle This simple harmonic approximation is sufficient enough for most problems For more details please have a look at the appropriate literature Jensen 1999 van der Spoel et al 2005 In the GROMOS 96 force field van Gunsteren et al 1996 van der Spoel et al 2005 a simplified Eq 9 5 1 E angle 2 cos g 7e cos 9 5 1s used 9 1 3 The Torsional Energy The torsional energy for rotation around the bond B C within a four atoms A B C and D connected by bonds between A and B B and C C and D Fig 9 3 is described by E tors The corresponding energy term may be described by the Eq 9 6 V cos ne 9 6 dihedral torsional angle n multiplicity V barrier of rotation around the bond B C The term n 1 describes a rotation with 360 p
165. l be named sequence its contents should look like this d usr bin gawk f UJ EGIN getline base lt base dat match base a z seq substr base RSTART RLENGTH AS 1 2 END out for i1 0 1 lt RLENGTH i 3 triple substr seq i 1 3 out out AS triple print out To start this script the user must have read and execute permissions Thus use the command chmod to add the execute right to the existing read right gt chmod u x sequence Now you are able to start the script by typing its name provided it resides in the actual directory gt sequence code dat Thus the shell will execute the following command usr bin gawk f sequence code dat and the output should look like the one you get by typing the whole gawk program on the command line To get the script more flexible one would replace the file name base dat by a variable let s say so the get line action near the pattern BEGIN would read UJ EGIN getline base in 11 7 A More Extensive Example 159 The appropriate command line now looks like that gt sequence v in base dat code dat the option v tells gawk that the next argument is the variable assignment x base dat resulting in a replacement of all instances x within the script by its value base dat Appendix Summary of Important Internet Resources Software for Simulation and Other Calculations
166. layer model and use this for further calculations Alternatively you can construct a lipid bilayer individually with a distinct width with an appropri ate software One suitable software is vmd http www ks uiuc edu Research vmd combined with some scripts as described in more detail later on The great advantage of the latter strategy is that you can individually adopt the size of your lipid bilayer with regard to the size of the GPCR or the GPCR Go f y complex In this context you have to take into account two considerations What do you want to simulate Only a GPCR or a whole GPCR GaBy complex Due to the larger size of a GPCR GoaBy complex compared to GPCR the lipid bilayer has to be large in case of a GPCR GaBy complex However both cases the lipid bilayer must be large enough in order to guarantee that the GPCR or GPCR Gofy complex is embed ded well This means you should have a lipid bilayer with a width of optimally 1 0 1 5 nm around your protein This guarantees that there are not undesirable inter actions between proteins of virtual simulation boxes as a result of periodic boundary conditions as illustrated in Fig 5 7 A lipid bilayer shell larger than 1 5 nm can be principally used but this would not lead to any advantage instead the great disadvantage will be an exponential increase in simulation time For simulation of a GPCR without the G protein a width of the lipid bilayer of about 9 10 nm is recommended Thus
167. le the pattern 29 type gt c 29 data command gt n 29 data J preceeds each line containing the pattern 29 by its line number Now let us have a closer look to the command grep c 29 data We get all the lines containing the regular expression 29 anywhere But how to solve the problem of counting all the lines containing the 11 4 Discussion of Selected LINUX Commands 149 pattern 29 in the fourth field of a line assuming the character as a delimiter Remember the command cut in the form cut d 4 data J which will output the fourth field of each line of data Combining this command with the help of the so called pipe symbol with the command grep using the regular expression 29 will show the desired result gt cut d f 4 data grep c 29 d head syntax head n number file explanation Print out line one up to number of the specified file example Print the first three lines of the file data head n 3 data sed syntax sed s patternl pattern2 file sed ms patternl pattern2 file sed m ns patternl pattern2 file sed n m np file explanation The first form of the command sed replaces the sequence of characters in pattern1 with the sequence of characters in pattern2 once for each input line of file The second and third form of the command sed will do the replacement only for line m and for lines
168. les et al 2006 By experimental studies some regions of GPCR and G protein which interact with each other were identified In general it is supposed that a pocket in the intra cellular part of the GPCR is opened during activation And this pocket is suggested to interact with the C terminus of the Go subunit Scheerer et al 2008 Rasmussen et al 2011 Furthermore mutagenesis studies suggest that amino acids of the 4 loop Bae et al 1999 Cai et al 2001 and 3 5 loop Grishina et al 2000 interact with the GPCR Thus by experimental studies some important suggestions with regard to GPCR G protein interactions could be obtained However there occurs A Strasser H J Wittmann Modelling of GPCRs 105 DOI 10 1007 978 94 007 4596 4_8 Springer Science Business Media Dordrecht 2013 106 8 Special Topics in GPCR Research one significant problem All experimentally detected GPCR G protein interactions cannot be explained by only one model Oldham et al 2008 Thus two hypotheses are suggested First receptor dimers might play a role in interaction with G proteins or secondly a sequential binding model is suggested Herrmann et al 2004 2006 Besides the experimental studies a distinct number of modelling studies with regard to GPCR G protein interactions are available Fanelli et al 1999 Greasley et al 2001 Oliveira et al 2003 Chou 2005 Raimondi et al 2008 Strasser and Wittmann 2010b in press As already men
169. lication of kappa opioid receptor structure m the journal N amp ure cr Moss o February 19 2012 EION x Fig 2 9 Homepage of GPCR network http cmpd scripps edu Chapter 3 Sequence Alignment and Homology Modelling For molecular modeling of proteins in general the structure of the protein is needed How can such a structure be obtained One might consider first a modeling of the protein structure de novo or ab initio based on the amino acid sequence There are several approaches described in literature Fleishman et al 2006 Yarov Yarovoy et al 2006 Taylor et al 2008 Zhang 2008 Barth et al 2009 Zaki et al 2010 For small proteins these techniques result in suitable structures which are in good accordance to experimentally derived structures But it should be taken into account that with increasing number of amino acids thus methods are not longer appropriate because of an exponentially increasing computational time Thus other techniques are necessary One is the technique of homology modelling This is based on the assumption that proteins of on class have a very similar structure Thus if the structure of one protein of a distinct class is evaluated by experimental methods the structures of all other proteins can be modelled in homology to this experimental template The technique of homology modelling is used with regard to several GPCRs Zhang et al
170. lled should be chosen Besides that 1t should be taken into account that different template crystal structures in homology modelling could lead to differences in the resulting homology model However the mainly used templates for modelling class A GPCRs are bovine rhodopsin and the human adrenergic B receptor see appendix Important Crystal Structures of GPCRs Source http www pdb org 3 3 4 Sequence Alignment After retrieving the amino acid sequences of the template structure and the destination receptor the sequence alignment can be performed There exist several techniques to perform the sequence alignment On the one hand the sequence alignment can be performed manually The corresponding steps require some time and concentration On the other hand there exist several software products which allow performing an alignment automatically like clustal http www clustal org see appendix Sum mary of Important Internet Resources However if software is used it is definitely necessary to check to resulting alignment in order to avoid unexpected mistakes or some inaccuracies For a manual sequence alignment the alignment is performed by several steps 1 Use the information of the expasy server http expasy org to get an idea about the amino acids of the seven transmembrane domains for template and target sequence 2 Perform the sequence alignment for each transmembrane domain in ascend ing order Here it is necessary that
171. m to n respectively of the named file If there are multiple instances of pat tern1 to be replaced by pat tern2 on one input line the character g has to be appended after the last slash of the quoted part for instance sed ms patternl pattern2 g file The first three sed command print all the modified and unchanged lines to the standard output The last form of the command just writes lines m to n of ile to standard output example First substitute the string DRG by DRN in all lines of the file data 150 11 Important UNIX LINUX Commands gt sed s DRG DRN data J Do the same only for the line number 4 gt sed As DRG DRN data l In the next example change the string DRG in line one and two to UNK gt sed 1 2s DRG UNK data To print out lines 2 up to 5 of the file data use gt sed n 2 5p data tail syntax tail n m file tail n m file explanation The first form will print out the last m lines of file whereas the second form will print lines beginning with number m to the end of file example Write out the last four lines of the file data gt tail n 4 data Write out all lines of file data beginning with line number 4 gt tail n 4 data J tr syntax tr patternl pattern2 tr s pattern tr d pattern explanation tr is a filter command receiving its input for example by a pipe and prints results to standard output pattern patternl1 a
172. mation at protein data bank http www pdb org mutation no information at protein data bank http www pdb org X lt A ba UniProtKB P02699 Teller et al 2001 Appendix 177 method X ray diffraction ebgdn pdb code 1GZM fragment no information at protein data bank http www no information at protein data bank http www pdb org 7 P02699 literature Li et al 2004 aa ramus fragment no information at protein data bank http www pdb org no information at protein data bank http www pdb org ligand this protein is ligand free rhodopsin opsin masa Xay mekm no information at protein data bank http www pdb org mutation no information at protein data bank http www pdb org this protein is ligand free rhodopsin opsin UniProtKB P02699 l I meric peptide from guanine nucleotide binding protein G t sub unit G molecule fragment C terminal domain residues 340 350 mutation K341L UniProtKB P04695 literature Scheerer et al 2008 178 Appendix fragment no information at protein data bank http www pdb org no information at protein data bank http www pdb org LO LO LOL UniProtKB P02699 molecule guanine nucleotide binding protein G t subunit fragment C terminal peptide residues 340 350 literature Choe et al 2011 no information
173. mmand sequence presented above is very simple in order to construct an appropriate file containing information about position restraints However for your equilibration protocol mentioned above you will need several itp files with different force constants Therefore the command sequence to generate the itp file has to be repeated several times Thus it would be easier to write an appropriate shell script bin tcsh set fconst 1000 800 600 400 200 100 set nr of fconst fconst set i 1 rm site dat rm force dat while i nr of fconst 13 grep C protein gro cut c 16 21 gt gt site dat 14 grep O protein gro cut c 16 21 site dat 15 grep N protein gro cut c 16 21 gt gt site dat 16 grep protein gro cut c 16 21 site dat N F Q N P sort n site dat site sort dat 6 4 Molecular Dynamic Simulation of your System 67 19 20 set nr of res 1 site sort dat Qut d 7 f 1 gt 21 22 set 1 1 23 24 while j nr of res 25 echo 1 fconst i fconst i fconst i gt gt force dat 26 j 27 end 28 29 echo position restraints posre_bb_ fconst i itp 30 paste site_sort dat force dat gt gt posre_bb_ fconst i itp 31 32 rm site dat 33 rm force dat 34 35 i 36 37 end You may name this shell script gen_posre After saving the file ensure the execute permission by using the command gt chm
174. n on molecular level However due to the hypothesis of sequential binding Herrmann et al 2004 as mentioned above more different GPCR G protein complexes should be taken into account The following part of Chap 8 1 is mainly based on articles in literature Strasser and Wittmann 2010b in press Copyright by Springer with permission from Springer In general two strategies for modelling a GPCR G protein complex are possible The most simple strategy would be the homology modelling of the complete GPCR G protein complex based on the crystal structure 3SN6 Rasmussen et al 2011 Alternatively the modeller can try to dock the Ga subunit to the corresponding intracellular part of the receptor manually But it is very hard to find an optimal complex and during this manual docking process a lot of clashes between GPCR and subunit may occur Furthermore by manual docking a large number of GPCR G protein complexes can be received and the modeller needs a criterion to decide which complex is the best one Shortly a manual docking is very unsystematically and it is not recommended Instead a systematic search will lead in an easier way to better results Thus a procedure for systematic search should be introduced now First a homology model of the interesting GPCR in its active conformation should be generated as already shown see Chap 3 Additionally a homology model of the corresponding Go subunit is needed The homology model of the
175. n Eq 7 28 Now let us have a look onto the concentration term in Eq 7 28 OH ngog RT ln 7 31 Co Setting equal to 1 mol the value of is determined by the choice of the number of water molecules which define the system volume Having 800 we get a cubic box size of 2 87538 nm at T 298 15 and p 1 bar The concentration of ethanol for a box volume V is then given by mol CEOH r x 7 32 NAV with a value of 0 0698 mol l The corresponding energy term for 1 mol of ethanol will become RT In 24 6 599 kJ The experimental value of A G is 20 98 mol Thus the concentration term just calculated represents a fraction of approxi mate 30 96 and the corresponding solvent term of about 12 96 To reduce the amount of corrections necessary for calculating solvation energies Villa et al has given a workaround of this problem by taking the number of solvent molecules as 3 000 placed in a cubic box of length 4 5 nm using a so called twin range cut off distance of 0 8 and 1 4 nm respectively Villa and Mark 2002 The partial charges of the sites of the solutes are adjusted to reproduce the exper imental values of the quantity AG neglecting the discussed concentration terms So the calculated difference G 1 G 2 directly corresponds to the Gibbs energy of solvation Referring to our present example a number of 3 000 water molecules and 1 mol molecule of ethanol gives rise t
176. n above you get the output containing 461 lines onto your xterm However we are not interested for the whole information of a line Instead if only backbone atoms should be administered with position restraints we have to look for the corresponding site numbers column title nr of the backbone atoms column title atom using the following sequence of commands head n 467 protein3 top tail n 461 tr s cut d 2 6 grep C cut d fl gt site dat J gt head n 467 protein3 top tail n 461 tr s cut d f2 6 grep O cut d 1 site datel gt head n 467 protein3 top tail n 461 tr s cut d 2 6 grep N cut d f1 gt gt site dat gt head n 467 protein3 top tail n 461 tr s cut d 2 6 grep H cut d fl gt gt site dat The output of the head and tail command is directed via pipe to the command tr The command tr with the option s combines all subsequent white space characters to exactly one For example echo xxx xxx tr s outputs XXX XXX Thus line 7 containing information about site 1 may look like that after using the command tr s as described above 1 NL 1 ALA N 1 0 129 14 0067 qtot 0 129 Due to the white space character in column 1 column 2 and are of interest for us Column 2 in the line above contains information about the site and column 6 in the line above contains
177. n et al 2004 This hypothesis may be supported by the modelling results because a sequential binding pathway connecting model I and Ia was determined on the potential energy surface Fig 8 6 As crystal structures are snapshots of distinct conformations in the solid state molecular modelling studies afford insight into distinct amino acid interactions be tween the receptor and Ga not only for minima but also for intermediate states which cannot be obtained via crystal structures Thus molecular modelling studies may allow deeper insights onto binding mechanism of a to a GPCR 112 8 Special Topics in GPCR Research Fig 8 6 Potential energy a surfaces of the predicted hB R Go complex and the minimum energy pathway a Minimum energy pathway connecting model Ia point 1 and model I point 8 b Schematic presentation of the minimum energy pathway connecting model Ia point 1 and model I point 8 along with the corresponding angles B and y Copyright by Springer with permission from Springer gt m gt N gt R a 5 a 5 reaction coordinate 8 2 Process of Ligand Binding from the Extracellular Side into the Binding Pocket of aGPCR It is widely accepted that ligands bind deeply between the transmembrane domains of for example biogenic amine receptors On the one hand this is suggested by crystal structures cocrystallized with a ligand in the binding pocket On the other
178. nd do not close your browser Copy your GROMACS coordinates with polar aromatic hydrogens and save them as gro file Copy your GROMACS topology and save it as itp file Load your gromacs coordinate file into an editor for visualization of molecules and verify the structure Next we present another example dealing with the ligand dobutamin Fig 4 7 Fig 4 7 Structure of OH dobutamine only R enantiomer shown HO cocrystallized with the turkey B adrenergic receptor in the crystal structure 2 00 N Warne et al 2011 H OH Dobutamine is a D sympathomimetic drug It is cocrystallized with the turkey adrenergic receptor in the crystal structure 2Y00 Warne et al 2011 36 4 Construction of Ligands Exercise Please upload the dobutamine in its neutral form as pointed out in Fig 4 7 to the PRODRG server and create the appropriate files as mentioned above If you have done so you should have a closer look onto the output of the PRODRG server Fig 4 8 You can see that now the dobutamine is positively charged since there is an additional hydrogen at the amino moiety Remember you uploaded dobutamine in its neutral form Be aware that this is typical for the PRODRG server molecules with a basic or acid moiety are calculated in its charged form Vis PR00806 Server Marilla Par x Das peim pan 9 Xo Serv
179. nd pattern2 each represent a sequence of characters The number of characters in the sets patterni and pattern2 should be equal Assuming an input file named data using the following command cat data tr patternl pattern2 translates each character of the set pattern into the corresponding character of pat tern2 for all the lines of the file data The command cat data tr s pattern 11 4 Discussion of Selected LINUX Commands 151 replaces each sequence of repeated characters listed in pattern with a single occurrence of that character for each input line of the file data The command tr d pattern deletes the characters listened in pat tern from each input line example The file data contains items in the so called csv format e g the character separates the data fields and the decimal point is replaced by a comma Most LINUX commands require fields separated by one or more spaces or tabs and expect a decimal point Thus one has to transform the contents of data with help of the command tr up dates tipt at al Have a look onto the string aBBcAAAfrBB where the repeated characters A and B are to be replaced by a single character A and s B in order to yield the sequence aBcAfrB gt echo aBBcAAAfrBB tr s AB 66 Lo Now assuming the field delimiter we will delete th
180. nit 105 Gy subunit 105 G subunit 25 Gaseous 87 103 gawk 91 147 155 157 159 Gibbs energy 77 80 84 100 102 135 Gibbs energy of solvation 80 82 85 87 91 95 96 98 99 GPCR 2 5 9 10 14 37 60 99 105 112 217 DOI 10 1007 978 94 007 4596 4 Springer Science Business Media Dordrecht 2013 218 GPCR G protein interaction 105 106 111 grep 64 70 148 149 GROMACS 29 31 33 43 46 58 60 64 81 85 87 123 125 H Hamilton function 76 78 79 head 38 Heat capacity 137 Heterotrimeric G proteins 8 9 105 Histamine receptor 13 Homology modelling 13 14 20 22 23 26 114 I Inactive conformation 8 14 113 Inactive receptor 113 115 118 Internal water 25 Intracellular loops 6 24 Inverse agonist 7 13 14 113 K Kinetic energy 77 83 132 L Ligand binding 7 80 112 118 120 135 Ligand penetration 115 119 Ligand receptor complex 1 73 138 LigPath 114 116 118 120 LINUX 45 60 108 144 151 Lipid 37 40 43 45 55 Lipid bilayer 5 37 39 40 42 44 53 60 62 114 M MD 3 22 31 38 62 73 78 79 81 83 100 Membrane protein 37 Minimization 28 63 109 125 Molecular dynamics 2 26 42 59 63 113 Monte Carlo 77 N N terminus 5 7 22 Neutralization 62 P Partial agonist 100 116 Partition function 76 Periodic boundary conditions 42 81 Phase integral 2 Phosphoglycerides 37 38 Phospholipid bilaye
181. nus of the Go subunit is deeply bound in a pocket between the transmembrane domains Leaving out this part of the will result in some problems in subsequent molecular dynamic simulations In general if molecular dynamic simulations of a receptor are performed the receptor is embedded in its natural surrounding Thus if the C terminal part of Ga or the whole Go is 26 3 Sequence Alignment and Homology Modelling Fig 3 13 Crystal structure of bovin rhodopsin 1GZM with internal water red balls Li et al 2004 missing the resulting free space is filled with water molecules Water molecules are highly polar and thus have completely other surface properties than the C terminal part of Ga Thus leaving out the C terminal part of and substitution by water molecules in molecular dynamics can lead to instabilities of the receptor during the molecular dynamic simulation Thus it is suggested to include at the whole Go or least the C terminal part of in a homology model Be aware that each GPCR couples to a distinct Ga subunit Fig 2 8 3 4 5 Refinement of the Receptor Model After finishing the homology modelling several checks of the complete model should be performed A typical error of beginners in molecular modelling is presented in Figs 3 14 3 16 During homology modelling some amino acid side chains have to be mutated into the correct amino acid side chain Sometimes especially with regard to long side chains
182. o The last nine lines of this file govern the calculation of For an explanation of the keywords and the corresponding values the reader is referred to the GRO MACS manual van der Spoel et al 2005 The comparison of the integration cycles according to method 1 and 2 presented in Fig 7 6 shows a good accordance The Gibbs energy of solvation of ethanol using method 2 is predicted to be 24 3 1 7 kJ mol Fig 7 6 Comparison of transfer of ethanol from vaccuo 468 in dependence of the into water coupling parameter A for the transfer of ethanol from vaccuo into water at a 1 method 1 temperature of 298 15 K 5 _method 2 calculated with method 1 10 method 2 lt lt 20 S 30 5 40 0 0 0 2 0 4 0 6 0 8 1 0 Experimental data In general itis very important to compare properties predicted by molecular modelling techniques with experimental data This is also recom mended for predicted thermodynamic parameters like AH or AS A sol 50i large number of thermodynamic parameters of solvation can be found in litera ture Cabani et al 1981 Abraham 1984 Such comparison of predicted data with known experimental data is necessary to judge the predictive quality of a molecular modelling technique and or the used force field parameters The predicted AG value of ethanol Table 7 4 is in very good accordance with sol the experimentally determined value Table 7 5 In contrast
183. o a mol fraction of water xp o 0 999667 whereas the molar concentration of ethanol reads as 6 0 01822 mol l At a tem perature of 298 15 K the concentration terms of Eq 7 28 will influence the above mentioned difference of the Gibbs energies by RT npg In xr o 12 41 kJ per mol ethanol which is about 60 of the experimental value 7 2 Examples Conceptual and Practical Considerations 83 Table 7 1 Differences in Run Cut off nm Ej kJ mol Eis kJ mol potential and kinetic TF T of one ethanol surrounded by 1 0 5 85 911 33 463 3 000 water molecules for 1 4 128 801 33 459 2 0 128 968 33 458 different cut off s 20 98 kJ mol Cabani et al 1981 Thus the evaluation of the parameters of any force field which should describe properties of solutions in an exact manner has to consider these facts to avoid artificial effects As G 1 G 2 is the quantity resulting from a simulation the term to be subject of adjustment is given by G 1 G 2 RT v In a nmo In smo i 7 33 Co for an arbitrary species i Another problem arises from the so called cut off distance for calculating the coulomb and van der Waals interactions between sites during a MD simulation Short cut off distances will fasten the calculation but lead to more inaccurate results Using boundary conditions and the PME method this cut off must not exceed the
184. od u x gen_posre Start your shell script by typing gt gen The contents of the new itp files should be proofed using an editor With this extensive example you should see that the linux commands presented in the corre sponding Chap 11 are very useful in generating and handling large files However the lines above only represent a rudimentary shell script which can be expanded in order to be more flexible like checking if a file which has to be created is already there in the directory Actually the script posre does not take care about this However you can use and adopt the presented shell script posre for your own purposes Take into account that the first column in the itp file has to contain the site numbers of the atoms which have to be administered with position restraints The numbering must be according to the numbering in the topology file You can use the gro file as we did in our example if you have only one protein and if the protein is the first molecule in your gro file If this is not the case you are suggested to adopt the script gen posre with regard to the topology file Next distinct parts of a typical GROMACS topology file named protein3 top of a protein are shown 68 6 Minimization and Molecular Dynamics moleculetype Name nrexcl Protein 3 3 atoms resnr residue atom cgnr charge mass typeB chargeB massB 1 NL 1 ALA N 1 0 129 14 0067 qtot 0 1
185. olis 1987 Bouzida et al 1992 but this procedure takes a lot of time and the results very often are not satisfactory For large biochemical systems the Molecular Dynamics is a widely accepted alternative Christen and van Gunsteren 2008 This concept uses the Newton equation of mo tion to follow the evolution of an arbitrary system with time i e we will monitor all properties of interest for example the potential and kinetic energy of our system in their dependence of time But now another problem arises in defining the equilibrium state and calculating the corresponding macroscopic quantities U H and G 78 7 Calculation of Gibbs Energy of Solvation First we postulate the equality between the mean values in phase space and the mean on time scale from MD calculations which is applicable for the quantities U and H Having a look on Eq 7 10 we see that this concept does not hold for the Gibbs energy So there is no simple possibility to calculate this important quantity and therefore no way to estimate the equilibrium constant on the base of Molecular Dynamics To overcome this problem the concept of perturbation with respect to the potential energy is introduced Suppose we have a system at constant pressure temperature and constant number of particles We indicate this state as state 1 and according to Eq 7 9 the partition function Q 1 for an arbitrary species is given by the equation f ffe eT LP aaa 7 12 Now as
186. ollowing Eq 7 49 can be used for linear fit to obtain AS and AC sol ol p sol T To F AC sol T m T T _ T p AC o In 7 49 Usually the fit performed with adequate software Besides that you program a leastsquare method by yourself was set to 293 K After fitting the following thermodynamic parameters were obtained for a temperature of 293 K Table 7 4 Table 7 4 Predicted AG thermodynamic reference AH parameters at 293 K for the AS solvation of ethanol in water 20 7 0 2 kJ mol 30 6 1 7 kJ mol 33 7 5 8 J mol K 498 572 J mol 96 7 Calculation of Gibbs Energy of Solvation The data points and the corresponding fit are shown in Fig 7 5 Fig 7 5 Predicted values for 20 0 the Gibbs energy of solvation for ethanol at different temperatures 20 5 21 0 kJ mol 21 5 22 0 280 285 290 295 300 305 Alternatively to the method presented above method 1 for calculation of the Gibbs energy of solvation a second method method 2 can be used To transfer gaseous ethanol from ideal gas state at 1 bar and an arbitrary temperature into pure solvent to obtain an ideal solution of ethanol in water which corresponds to the difference G 1 G 2 cf Eq 7 37 the following mdp file has to be applied H MD 4 Input file title Ethanol
187. on Translation of the Ga loop depot e 5 p subunit in in z direction Rotation of the Ga subunit loop P around the x axis Rotation of the Ga subunit around the y axis loop Rotation of the Ga subunit around the z axis amp Minimization of the resulting structure amp Geometrical check of the minimized structure loop 8 1 Interaction Between a GPCR and the Go subunit 109 minimization within your C code After minimization you can go back in your C code determine the potential energy of the minimized structure and save the potential energy in an appropriate data structure Additionally we strongly recommend to per form a geometrical check of each minimized structure Especially in the case where the Ga subunit is very close to the receptor collisions which were not cleaned by minimization can occur It may take some time until the program code works quite fine but a full automatization of all steps due to the large number of structures is necessary and cannot be performed manually Furthermore we strongly recommend to split the program code into several modules For example one can establish a func tion for translation a function for rotation and a function for calling a shell script with the GROMACS routines for minimization As a result of the potential surface scan one obtains the corresponding potential energy surfaces A section of the potential surface with regard to translation on z axis and rot
188. one might conclude that all is well However often during molecular dynamic simulation problems occur and the simulation stops with an error If this is the case you have to go back to your starting structure and look for the error Often an error similar to that described above Fig 3 16 causes the problem A similar problem can occur not only within the protein but also between protein and lipid molecules If there are collisions between amino acid side chains one has to decide how to remove this collisions In general there are two possibilities First one can simply perform an energy minimization But in some cases this could lead to artefacts especially if two aromatic moieties are linked together Thus it is suggested that one looks separately onto each collision and tries to remove the collisions by carefully changing the corresponding dihedral angles After completing these steps the homology model can be energetically minimized Here it is suggested that the energy minimization is performed step by step In order to avoid structural artefacts induced by minimization it is important that the backbone of the transmembrane domains is provided with position restraints during a first minimization In a subsequent minimization steps the receptor can be minimized without any position restraints Afterwards the model should be checked addressing the following items and if everything is correct one can start with further modelling
189. or aromatic rings collisions between the side chains arise There are two types of collisions In the first type two side chains are in close contact as shown in Fig 3 14 In most of these cases energy minimization is sufficient to 3 4 Homology Modelling 27 minimization Fig 3 14 Close contact between the atoms of a lysine and phenylalanine Left before minimization right after minimization Fig 3 15 Part of a protein structure after minimization What is the problem PUTAS remove the collision and suitable structures might be obtained The second type of collision is a more difficult pitfall which is illustrated in Figs 3 15 and 3 16 Look carefully onto the Fig 3 15 Where is the problem After a careful look onto the picture you may see that there is a problem with regard to a lysine and phenylalanine in box B3 This is also illustrated in Fig 3 16 Here a long amino acid side chain like present in lysine is located within an aromatic ring like present in tyrosine phenylalanine tryptophane or histidine 28 3 Sequence Alignment and Homology Modelling minimization Fig 3 16 Wrong close contact between the atoms of a lysine and phenylalanine Left before minimization right wrong structure after minimization Unfortunately a large number of modelling software minimizes a protein containing such type of wrong structure And additionally in most cases the potential energy is negative Thus
190. ordrecht 2013 76 7 Calculation of Gibbs Energy of Solvation connection of AG to the interactions which take place when the ligand L leaves its solvation state and enters the receptor R to form the complex LR This link is given by the concepts of Classical Statistical Mechanics in combination with Quantum Mechanics As formerly stated Chap 1 Quantum Mechanics would be the best choice for describing the behaviour of matter in a microscopic world but up to now it is impossible to handle large biochemical systems So we use the Classical Statistical Mechanics which uses the Hamiltonian function H p r Exin P Epor 7 4 the sum of the total kinetic Ekin and the potential energy Epor as a central function to calculate macroscopic quantities H depends on the momenta p and the coordinates 7 of all species present in the system of interest Because we are interested in the equilibrium state of a system H depends not explicitly on time The expression for the kinetic part of H is the sum over the kinetic energies of all species i 22 Exin B 7 5 where denotes the mass and p the momentum of a particle i The potential energy comprises energies resulting from binding interactions ion ion ion dipole or dipole dipole interactions Note that the Hamiltonian function does not contain variables like the pressure p or the temperature T These parameters appear in the expressions of macroscopic quantities like the
191. ormational energetics and properties of organic liquids J Am Chem Soc 118 11225 11236 Kenakin T 1997 Pharmacologic analysis of drug receptor interaction Lippincott Williams and Wilkins New York Khelashvili G Dorff K Shan J Camacho Artacho M Skrabanek L Vroling B Bouvier M Devi LA George SR Javitch JA Lohse MJ Milligan G Neubig RR Palczewski K Parmentier M Pin JP Vriend G Campagne F Filizola M 2010 GPCR OKB the G protein coupled receptor oligomer knowledge base Bioinformatics 26 1804 1805 Klotz IM Rosenberg RM 2008 Chemical thermodynamics basic concepts and methods 7th edn Wiley Hoboken Kobilka BK Deupi X 2007 Conformational complexity of G protein coupled receptors TRENDS Pharmacol Sci 28 397 406 Kondepudi P Prigognie I 1998 Modern thermodynamics from heat engines to dissipative structures Wiley New York Kosztin D Izrailev S Schulten K 1999 Unbinding of retinoic acid from its receptor studied by steered molecular dynamics Biophys J 76 188 197 Kristiansen K 2004 Molecular mechanisms of ligand binding signalling and regulation within the superfamily of G protein coupled receptors molecular modelling and mutagenesis approaches to receptor structure and function Pharmacol Ther 103 21 80 Kubinyi H 2011 3D QSAR in drug design Springer Berlin Kukol A ed 2010 Molecular modeling of proteins Humana Press New York Leavitt S Freire E 2001 Direct measurement of protein binding energeti
192. otein in the simulation box with the proteins in the neighboured virtual simulation boxes due to periodic boundary conditions Structures_and_Topologies and can also be found in the appendix POPC Para meters In the script vmd2gro the tcl script combine developed by Balabin and published at http www ks uiuc edu Research vmd plugins membrane was used see lines 192 276 in vmd2gro shown below Before starting you need your protein as a correct pdb file which can be used as an input file for the GROMACS command pdb2gmx without special options In this example this file is named protein pdb In the next step you can start vmd to generate the lipid bilayer Therefore choose in the main menu Extentions Modelling Membrane Builder There choose POPC as lipid because the script vmd2gro only consid ers in the version presented here Define the length of the lipid bilayer in x and y direction Be aware to define the values in In the actual version of the script vnd2gro a box size of about 10 x 10 x 10 nm is defined see line 188 44 Fig 5 8 Step 1 Generate or download a lipid bilayer of appropriate size However you can change the values in the script of later on in the gro file if nec essary So for example type 100 for width in x and y direction in the appropriate field of vmd As ouput prefix type membrane Subsequently the mem brane is generated and is shown in vmd Additionally in the
193. pe pme rcoulomb 21 4 epsilon r 21 0 vdwtype Cut off rvdw 1 4 DispCo EnerPres Tcoupl Pcoupl no gen vel Energy monitoring energygrps system Afterwards you can start to neutralize your system Fig 6 1 step 4 To get in formation about the total charge of the system have a look onto the output of the grompp command Subsequently you have to think about which ions and how much you want to put into system In general sodium and chlorine ions are used The concentration of sodium and chlorine ions should be chosen that approximately physiological conditions are achieved Now you can neutralize your system using the command geni on as described in the GROMACS manual van der Spoel et al 2005 After neutralization the system should be minimized again gt grompp f mini c system p system mdrun v s If your system is minimized carefully and there are no bugs as described in Sect 3 4 5 the MD simulation should work quite well 6 4 Molecular Dynamic Simulation of your System Now the molecular dynamic simulation van Gunsteren et al 1990 can be started In general a MD simulation is divided into two phases The equilibration phase and the productive phase What does equilibration phase mean Even if you put your GPCR very carefully in the lipid bilayer the interactions between the lipid bilayer and the receptor are not very optimal lets say not equilibrated Furthermore during the
194. pid membrane gro file echo number of atoms gt gt gro file set unit 1 set atom no 1 while Sunit lt Sunits set 1 11 Sunit 1 n pdb while n n gro line i1 map n gawk v u Sunit v line pdb line v atom atom no v label gro label n NR 1line printf 51 33s 7s 5i 8 3 8 3 8 3f n u POP label atom 6 10 0 7 10 0 8 10 0 S mem pdb gt gt gro file n atom_no end 8 unitt end echo 10 00 10 00 10 00 gt gt gro file exit 0 Je KR KK k k k k k K K K K K K K KK K K K K K K ck kc kckck KOK KOK K K K KK START TCL script part do not edit or delete this label Following tcl commands for VMD embed parts of protein into a membrane Ilya Balabin ilya ks uiuc edu 2002 2003 197 198 199 You need a membrane structure membrane psf pdb b properly oriented and aligned to the membrane 200 protein structure protein psf pdb 201 202 2 Q N P 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 5 Lipids set echo on for debugging echo on need psfgen module and topology package require psfgen topology top_all27_prot_lipid inp load structures resetpsf readpsf MEM psf coordpdb MEM pdb readpsf protein psf readpsf PROT psf coordpdb
195. polarfaromatic H s ow polar H s only or no H s MDL Molfile H s polar H s only cx or no pi B GROMOS87 GROMACS all H s polar aromatic H s or polar H s only zi Xay refinement Y CNS parameters p and topology e REFMACS5 gt Download everything as a gzipped tarfile or as a zip archive read OOREADME in the archive Get the animated GIF or look at the log file Fig 4 4 Overview of different outputs of the PRODRG server Construction of Ligands 33 The PROORG Server Mozilla Firefox me x Que Aht Cronk Eyres te The PROORG Server lt duree S H moons 8 The GROMOS87 GROMACS coordinate file polar hydrogens F PRODRG COORDS 1 1 810 0 683 0 517 1 a 1 1 710 0 738 0 619 1c 3 1 75 0 757 0 744 1c 4 1 709 0 792 0 811 0 44400 0 44400 0 44400 The GROMOS87 GROMACS coordinate file polar aromatic hydrogens PRODRG COORDS 4 124 1 1 010 0 0 517 1 710 0 74 0 619 3 1 5 0 757 0 744 1c m 4 1 709 0 792 0 811 0 44400 0 44400 0 The GROMOS87 GROMACS coordinate file all hydrogens 0095 9 1d 1 810 0 682 0 517 1 849 0 588 0 552 1 760 0 668 0 421 mi m2 1 lt 1 888 0 758 0 510 1 710 0 738 0 619 1 634 0 661 0 622 1 671 0 033 0 54 519115 0 757 0 744 1c 1 709 0 792 0 811 0
196. ppropriate biochemical reactions Furthermore a lot of regulatory processes control the complicated sequences of the molecular reaction cycles and signal cascades and may be influenced by information in form of physical effects or chemical compounds coming from the environment of the individuals So all what we call life is subject to biochemical processes and may be described by thermodynamic and kinetic concepts Energetic and entropic aspects were therefore used in a larger extent to explore the behaviour of chemical compounds addressing G protein coupled receptors residing in the cell membrane In this context drug design in the past was done by chemical synthesis and pharmaco logical testing afterwards hoping to obtain a powerful new active compound But in order to have specific drugs exhibiting a minimum of side effects and to reduce costs and time of research and production a deeper insight onto processes linked with the interaction of ligands and receptors on molecular level is necessary So nowadays a scientist working on the field of drug design has to use the physicochemical concepts to successfully predict the properties of compounds But an increasing knowledge of the processes determining the behaviour of the interaction between ligands and re ceptors reveal a great complexity of this research field Computational methods have to be used in order to describe quantitatively the processes setting up the network of ligand receptor intera
197. r 37 39 PME 83 Index POPC 38 42 45 Position restraints 28 59 63 67 70 Potency 1 Potential energy 2 78 79 115 121 132 Potential energy surface 2 3 59 107 109 111 114 118 Precoupling model 105 Productive phase 62 R Receptor activation 25 114 118 120 131 132 Receptor dimers 106 Restraints 115 S sed 149 Semiempirical calculation 2 Sequence alignment 18 20 22 Sequential binding model 106 Shell script 42 66 67 153 155 Signalling cascade 10 105 Simulation box 42 46 58 59 61 87 100 Simulation protocol 55 Site concept 31 124 Solvation 4 58 60 Statistical mechanics 77 Statistical thermodynamics 77 Stretching energy 121 122 126 T tail 38 Thermodynamic cycle 86 99 100 Thermodynamic integration 85 99 101 Thermodynamics of solutions 134 Titration calorimetry 136 TM 5 Topology 29 33 45 60 69 Torsional energy 121 123 128 tr 69 143 151 Transmembrane domain 5 6 20 22 23 37 59 Transmembrane helix 119 U UNIX 139 146 der Waals interactions 83 86 87 121 w wc 65 143
198. r 1 230 lysozyme 2 161 adrenergic receptor 263 348 E122W N187E C1054T C1097A P07550 P00720 Wacker et al 2010 3NY8 X ray diffraction 2 84 A f2 adrenergic receptor lysozyme chimeric protein of B adrenoreceptor 1 230 lysozyme 2 161 B adrenergic receptor 263 348 E122W N187E C1054T C1097A P07550 P00720 Wacker et al 2010 182 Appendix method X ray diffraction molecule p adrenergic receptor lysozyme chimeric protein of B adrenoceptor 1 230 lysozyme 2 161 fragment adrenergic receptor 263 348 E122W NI87E C1054T C1097A P07550 P00720 Wacker et al 2010 method X ray diffraction resolution 540 molecule p adrenergic receptor Fab light chain Fab heavy chain no information at protein data bank http www pdb org mutation no information at protein data bank http www pdb org without ligand UniProtKB P07550 Bokoch et al 2010 Appendix pdb code UniProtKB pdb code resolution UniProtKB 183 3P0G X ray diffraction 3 50 p adrenergic receptor T4 lysozyme chimera P07550 residues 1 230 263 365 00720 residues 2 161 N187E OH H OH P07550 P00720 Rasmussen et al 2011 3PDS X ray diffraction 3 50 fusion protein B adrenergic receptor lysozyme no information at protein data bank http www pdb org H93C NI87E 265 P07550 P00720 Rosenbaum et al 2011 184 Appendix ma
199. r visualization of molecular structures vmd http www ks uiuc edu Research vmd A molecular visualization program Rasmol http rasmol org A molecular visualization software xmgrace http plasma gate weizmann ac il Grace 2D data visualisation Databases Name Source and short description GPCRDB http www gpcr org 7tm Information system for G protein coupled receptors PDB http www pdb org Archive containing information about experimentally determind structures of proteins for example Expasy http www expasy org Provides access to scientific databases and software tools http www expasy org Drug Bank http www drugbank ca A drug data and drug target database GPCR network http cmpd scripps edu Platform of the GPCR community gpDB http bioinformatics2 biol uoa gr gpDB A database of GPCRs G Proteins Effectors and their interactions Elefsinioti et al 2004 Theodoropoulou et al 2008 GPCR OKB http data gpcr okb org gpcr okb A database about GPCR oligomerization Skrabanek et al 2007 Khelashvili et al 2010 IUPHAR http www iuphar db org Database on receptor nomenclature and drug classification Sources with Regard to Lipids URL http lipidbook bioch ox ac uk http moose bio ucalgary ca index php page Structures_and_Topologies http www Irz muenchen de heller membrane membrane html http www scmbb ulb ac be Users lensink lipid Appendix Natural Amino Acids Alanine i Glutamine aci
200. rch Pharmacol 384 287 299 Wise A Gearing K Rees S 2002 Target validation of G protein coupled receptors Drug Discov Today 7 235 246 Woolf TB Roux B 1996 Structure energetics and dynamics of lipid protein interactions a molecular dynamics study of the gramicidin A channel in a DMPC bilayer Prot Struc Func Genet 24 92 114 Wu B Chien YET Mol CD Fenalti G Liu W Katritch V Abagyan R Brooun A Wells P Bi FC Hamel DJ Kuhn P Handel TM Cherezov V Stevens RC 2010 Structures of the CXCR4 chemokine GPCR with small molecules and cyclic peptide antagonists Science 330 1066 1071 Xu F Wu H Katritch V Han GW Jacobson KA Gao ZG Cherezov V Stevens RC 2011 Agonist bound structure of the human adenosine receptor Science 332 322 327 Yarov Yarovoy V Schonbrun J Baker D 2006 Multipass membrane structure prediction using Rosetta Prot Struct Funct Bioinfor 62 1010 1025 Zaki MJ Bystroff C 2010 Protein structure prediction 2nd edn Human Press Inc New York Zhang Y DeVries ME Skolnick J 2006 Structure modeling of all identified G protein coupled receptors in the human genome PLOS Comput Biol 2 88 99 Zhang Y 2008 Progress and challenges in protein structure prediction Curr Opin Struct Biol 18 342 348 Index A Ab initio calculation 2 Active conformation 7 9 14 25 106 113 Active receptor 105 118 Adenosine receptor 14 Adrenergic receptor 13 14 35 39 Affinity 2 83 100 103 Agonist
201. re the interactions between the ligand and the receptor will be switched off We define the starting state 3 composed of moles of ligand receptor complexes and ns moles of solvent where ns is much larger than and nz By switching of the interactions between the ligand and the receptor we arrive at state 4 comprising of the ligand as an ideal gas and the empty receptor located in the solvent The Gibbs energy of state 3 G 3 and state 4 G 4 are represented by the Eqs 7 38 and 7 39 CLR G 3 2 nig RT In n u RT In 7 38 Co CR G6 muni na u RT m m us 7 39 Formulating the difference G 4 G 3 the entire solvent terms cancel and we get G 4 GG 4 RTIn Ds 7 40 NLR wie RT In Co 7 2 Examples Conceptual and Practical Considerations 85 Because the ligand the receptor and the ligand receptor complex are charged gen erally appropriate counter ions have to be present in an electrically neutral solution For the discussion of the thermodynamics of the association process we presuppose that these counter ions do not influence the formation of the ligand receptor complex For the process under consideration we have NLR hp 7 41 So the concentration terms cancel and the difference yields G 4 GG n ups us 7 42 Establishing the difference G 2 G 1 G 4 G 3 7 4
202. reate an array AS using the base triplets as an index string and the corresponding amino acid name as the value V V VV VV VN NV AS results in Met and so on Let us test this part of our example gt gawk 5 51 52 END base aga print AS base code dat will output the string Arg The first pattern action statement merely consists of an action which means that this part will be applied to all lines of the input file code dat For each line the first field denoted by 517 is used as an index of the array AS the second field 52 represents the value of the array element It should be taken into account that the entries in the first column of the file code dat should be different for use as array indices The second pattern action statement exhibits the special pattern END so the corresponding actions separated by a semi colon will be executed after all lines of the file code dat have been processed The first command assigns the value aga to string variable base The next statement prints out the array element AS base which equals the amino acid arginine Next we will read the base alignment and extract the first substring containing only lower case letters This part of the problem may be treated in the following way gt gawk match 0 a z seq substr 0 RSTART RLENGTH END print seq RSTART RLENGHT base dat The first action statement makes a c
203. riple whereas all other users may only read from triple For mike to execute a program or shell script his access mode list should look like rwx To change and verify the mode of the file triple enter the following command in a shell terminal 11 7 More Extensive Example 155 gt chmod u x triple gt 15 al triple Note that the file access mode for user mike now has changed to rwx Thus mike is able to start the script by typing gt triple atgtctttcctcccaggaatgacc where the string not necessarily has to be quoted Now have a closer look to the shell script The first line bin tcsh indicates that a tcsh shell is to be started to execute the commands of the shell script Scripts should always start with a first line defining the command processor A character in a line other than the first introduces a comment which extends to the end of the line Note the variable substitution 51 which is special to shell scripts refers to the first argument when calling triple Further parameters can be referenced by 2 3 and so on The notation means all arguments given to the command So the i statement checks whether an argument the base string is available and if not indicated by the null string provides some messages to the user Here the notation 50 refers to the command itself After that the script exits caused by the command exit completed by an arbitrarily error number in
204. rol Fig 5 3 The cholesterol scaffold contains four condensed rings leading to a distinct rigidity This structure is hydrophobic and thus it is able to insert into the hydrophobic inner layer of the lipid bilayer The polar hydroxyl moiety is located at the surface of the lipid bilayer Fig 5 3 Structure of cholesterol CH HO Cholesterol is sometimes found cocrystallized in combination with crystal struc tures of GPCRs For example a cholesterol specific binding site was identified for the human B adrenergic receptor within the crystal structure 3D4S Hanson et al 2008 5 2 Structure of the Phospholipid Bilayer In Fig 5 4 a site model of a lipid bilayer is presented The hydrophobic chains point inside the lipid bilayer whereas the polar head groups are facing towards the surrounding water 40 5 Lipids Fig 5 4 Model of a lipid bilayer with water on both sides water 4 XOT head x e groups KRS AES Sve hydrophobic core l AS K Be head gt groups water 5 3 Lipid Bilayer Models Used Molecular Modelling Several lipid models were constructed for use in molecular modelling Some of them are summarized in Table 5 1 Table 5 1 Summary of some Dipalmitoylphosphatidylcholine lipids often used in molecular DMPC Dimyristoylphosphatidylcholine modelling studies DOPC Dioleoylphosphatidylcholine POPC 1 palmitoyl 2 oleoylphosphatidylcholine POP
205. roteins on the other hand are known http www pdb org In 2008 a crystal structure of opsin cocrystallized with a part of the C terminus of Ga was published Scheerer et al 2008 In order to get a more detailed insight into interactions between a GPCR and the Go subunit in 2010 a hB R Ga complex was predicted Strasser et al 2010 One year later 2011 a crystal structure of the hB R Go y complex which is shown Fig 2 7 was published Rasmussen et al 2011 hf R Gay Nb35 T4 Lysozyme Nb35 T4 Lysozyme Ab hp R Gapy Nb35 T4 Lysozyme hp R Gafy Nb35 T4 Lysozyme hp R Ga hp R Gay Nb35 T4 Lysozyme Fig 2 7 Crystal structure of a hB R Gorf y Nb35 T4 Lysozyme complex Rasmussen et al 2011 G protein coupled receptors interact with heterotrimeric G proteins located in the intracellular part of a cell comprised of a Go subunit and a GBy heterodimer If an agonist binds to a GPCR the GPCR undergoes a conformational change from the inactive to the active state Kobilka and Deupi 2007 In the active conformation the GPCR interacts with the appropriate G protein Subsequently the conformation of the Go subunit changes by release of GDP and GTP binds to the ternary complex 10 2 GProtein Coupled Receptors consisting of the agonist the GPCR and the G protein This leads to conformational change of the Go subunit and the heterotrimeric G protein complex dissociates into a
206. rts with one On output the specified fields will be separated by the char acter delim Thus the last three commands will lead to the following results Print out field n of each line of a file using the character delim as delimiter 146 11 Important UNIX LINUX Commands Print out field m to n of each line of a file using delim as delimiter Print out the fields m n of each line of a file using the character delim as delimiter example Write out character 7 of each line of file data gt cut c 7 data Write out characters 7 to 9 of each line of file data gt c 7 9 data Write out characters 2 4 6 8 of each line of file data cut c 2 4 6 8 data Print field number 3 using the delimiter of each line of the file data gt cut d 3 data Write out the first second and fourth field of each line of the file 2 data using as delimiter gt cut d f 1 2 4 data J Finally generate an output with the fields 2 4 of each line of file 93 data using delimiter gt cut d f 2 4 data J gawk syntax gawk pattern actions file s explanation gawk sometimes referred to as awk certainly is the most powerful command for UNIX In its simplest form it consists of a sequence of pattern action statements Each input line of file s matching the pattern is divided into fields using blanks and or tabs as delimit
207. s gt Acta Crystallogr D60 1355 1363 moleculetype Name nrexcl 02 3 atoms 5 nr type resnr resid atom cgnr charge mass CH3 LIG C4 1 0 074 15 0350 2 CH2 LIG C1 1 0 091 14 0270 3 OA 1 LIG 02 1 0 202 15 9994 4 H 1 LIG H2 1 0 037 1 0080 bonds ai aj fu cO cl 32 0 153 7150000 0 0 153 7150000 0 C1 C4 13 32 0 143 8180000 0 0 143 8180000 0 Cl 02 3 X 2 0 100 15700000 0 0 100 15700000 0 02 H2 pairs ai aj fu 1 4 1 CA H2 angles ai aj ak fu c0 cl 4 22 230 109 5 520 0 109 5 520 0 C4 C1 O2 2 Be Al lt 2 109 5 450 0 109 5 450 0 C1 02 H2 dihedrals ai aj ak al fu cL ms 15202203 4 1 3 0 0 1 3 3 7 dihH CM 02 H2 In the section bonds the parameters for the stretching energy between two bonded atoms are defined Let s look onto the first parameter line of this section 2 1 2 0 153 7150000 0 0 153 7150000 0 C1 C4 9 3 The Force Field Parameters 127 Fig 9 5 Ebona in dependence 125 of the distance between two atoms example bond 100 between and C4 of ethanol see above 75 2 8 50 2 5 0 012 043 044 045 046 047 0 18 r nm Fig 9 6 Eangie in dependence 1 5 of the angle between three atoms example angle between C4 and O2 of 55 ethanol see above 1 0 3 E 2 0 5 ul 0 0 104 106 108 110 112 114 a Within this line the stretching energy between t
208. s of base dat in the variable base which in turn will be processed by the functions match and substr to generate the base sequence The following action statement will be applied to each line of the file code dat building up the array AS whose elements will be printed Finally the END action prints out the base sequence The complete form of the gawk command is presented next gt gawk BEGIN getline base lt base dat match base a z seq substr base RSTART RLENGH AS 1 2 END out for i 0 i lt RLENGTH i 3 triple substr seq it 1 3 out out AS triple print out code dat The main work is done by the END section within a loop statement The base sequence is split into triples by means of an index variable i which defines the end of the foregoing triple The function substr locates the triple from the string seq starting at character position 1 1 spawning three characters Next the corresponding amino acid is retrieved from the array AS with the help of the just calculated variable triple Next we connect it with the string out which holds the amino acids detected so far To get the desired result we make use of the or loop statement which starts after an initialization out where an empty output string out is defined The loop first assigns the value zero to its loop variable i The next controlling statement ensures a definite number of loop cycles given b
209. ski J Stansfeld P Sansom MSP Beckstein O 2010 Lipidbook a public repository for force field parameters used in membrane simulations J Membrane Biol 236 255 258 Dore AS Robertson N Errey JC Ng I Hollenstein K Tehan B Hurrell E Bennett K Congreve M Magnani F Tate CG Weir M Marshall FH 2011 Structure of the adenosine 2 receptor in complex with ZM241385 and the xanthenes XAC and caffeine Structure 19 1283 1293 Duan Y Wu C Chowdhury S Lee MC Xiong G Zhang W Yang R Cieplak P Luo R Lee T Caldwell J Wang J Kollman P 2003 A point charge force field for molecular mechanics simulations of proteins based on condensed phase quantum mechanical calculations J Comput Chem 24 1999 2012 Dudek AZ Arodz T Galvez J 2006 Computational methods in developing quantitative structure activity relationships QSAR a review Comb Chem High Throughput Screen 9 213 228 Elefsinioti AL Bagos PG Spyropoulos IC Hamodrakas SJ 2004 A database for G proteins and their interaction with GPCRs Bioinformatics 5 208 215 Evers A Klebe G 2004 Successful virtual screening for a submicromolar antagonist of the neurokinin 1 receptor based on a ligand supported homology model J Med Chem 47 5381 5392 Fanelli F Menziani C Scheer A Cotecchia S de Benedetti PG 1999 Theoretical study of the electrostatically driven step of receptor G protein recognition Proteins 37 145 156 Fanelli E Menziani C Scheer A Cotecchia S de Benedetti PG 1999
210. ssociation constant is given as 250 nM the quantity K in Eq 10 18 has to be substituted by 250 107 in order to get the true value of AG for the ligand receptor dissociation process The quantity AG comprises two terms firstly the enthalpy A H and secondly the entropy A S AG TAS 10 19 where T represents the temperature and AH H H H2 10 20 AS 59 82 5 10 21 With respect to the chemical reaction Eq 10 1 the quantities AG AH and AS apply to the formation of one mole of ligand receptor complex LR The enthalpy term A H contains information about the change in energy during a particular reaction whereas the entropy term AS lacks any simple interpretation Nevertheless very often AS is connected with the concept of order and disorder in the course of chemical reactions As these terms are not defined exactly the interpretation of A S in most cases leads to severe mistakes in inspecting of chemical processes and should therefore used with caution To gain more detailed insight in the ligand receptor interaction that is to under stand the magnitude of the equilibrium constant K we have to analyze the energy term A H and the entropy term S a molecular level But before doing so we first have to deal with the determination of these two quantities which will be the subject of the following section 136 10 Thermodynamics of Ligand Receptor Interaction 10 4 Evaluatin
211. structural change of the ligand CCK9 nM kcal mol kcal mol compound CCK9 1 38 0 15 Asp 8 Ala 253 8 11 4 3 21 0 3 3 00 7 S Tyr 3 gt Tyr 108 8 4 8 2 7 X 0 1 1 9 0 4 7 2 Examples Conceptual and Practical Considerations 101 Table 7 7 Binding affinities of six phenylhistamine derivatives at hH4R at a temperature of 298 15 K Wittmann et al 2011 R R pK hH4R H PheHIS 1 H H 4 79 0 04 N N ga PheHIS 2 H 5 91 0 12 Y PheHIS 3 H 5 76 0 01 N PheHIS 4 H CH 6 13 0 08 H PheHIS 5 6 80 0 04 R PheHIS 6 Br CH 6 56 0 06 TM V phenylhistamine derivative phenylhistamine derivative R R H CF R CH Fig 7 9 Binding mode of two phenylhistamine derivatives PH 1 left and PH 5 right in the binding pocket of hH4R Wittmann et al 2011 copyright by Springer with permission from Springer In case that the small phenylhistamine R R is bound to the receptor two small empty pockets Fig 7 9 left arrow 1 and arrow 2 were identified If a more bulkier phenylhistamine R CF3 R CH3 is bound to the receptor the methyl moiety CH3 fits well into pocket 1 Fig 7 9 right arrow 1 and the trifluoromethyl moiety CF3 fits well into pocket 2 Fig 7 9 right arrow 2 Thus it can be suggested that the additional methyl and trifluoromethyl moieties result in an increase of interaction between the
212. studies like docking or molecular dynamic simulations Check for the correct amino acid sequence Check for the presence of the disulfide bridge between the E2 loop and the upper part of TM III Check for the correct configuration of the amino acids Check for collisions or bad contacts between amino acid side chains Chapter 4 Construction of Ligands Some molecular modelling software include very comfortable editors which al low to construct ligands Additionally distinct atom types can be assigned to these atoms In contrast Gromacs http www gromacs org is a powerful software pack age for molecular dynamic simulations and no editor for construction of ligands is included Therefore we recommend that you download an appropriate editor like chimera http www cgl ucsf edu chimera and install this on your computer In general you can also use other software to construct your 3D molecules but the software should be able to save the molecule as pdb file Before you can use Gro macs http www gromacs org to simulate organic compounds like a ligand you have to generate a topology file of the molecule of interest In general your molecule editor is not able to create an appropriate topology file We do not recommend con structing a topology file manually because therefore you need detailed knowledge about types of the atoms or sites and their force field parameters on the one hand On the other hand
213. sume the Hamiltonian energy of our system has changed to state 2 by variation of the particle interactions for example We will then write the partition function Q 2 HO apa av 7 13 kT Calculating the Gibbs energy for example of state 2 according to Eq 7 10 yields G 2 kT In Q Q 7 14 Let us reformulate this equation in the following way Q 1 To what extent does this mathematical manipulation help us to solve our problem First we can write the right hand side of Eq 7 15 in the following form 0 0 G 2 kT In 7 15 G 2 kT In Q 1 kT In 0 0 7 16 and making use of Eq 7 10 we G 2 G 1 kT In 0 02 7 17 Next we will reformulate Q 2 0 JJ f ep H 1 pi Ti pV exp T kT HQ Pi fi pV GI piri 2 7 18 7 1 Theory Link Between Microscopic and Macroscopic World 79 which only means to multiply the integrand of Eq 7 13 by one Now the resultant term 9 2 represents the phase mean of the quantity HQ Bi Fi pV HO Bi Fi 5 7 19 kT This result is very important for the Molecular Dynamics simulation procedure be cause this phase mean corresponds to the mean in time scale We follow the time evolution of our system in state 1 and calculate H 2 for the same set of variables pi and r The result represents the difference
214. surround the name x by braces gt echo x abc This command will print 123abc to the standard output Here the use of does not mean file name substitution rather insulating the variable name from following characters because of the special symbol The symbol 8 allows arithmetic positive integer range calculations performed with variables e g gt set x 1 gt x x 3 gt echo x Therein the first command defines a variable x with value 1 In the next statement the number 3 is added and finally the new value of the variable x is printed 11 3 Shell Substitutions 143 11 3 3 Command Substitution If the shell encounters a string enclosed in back quotes the command substitution takes place The string is considered as a command and is executed in a subshell Its output replaces the string including the back quotes in the original command Have a look onto the sequence of DNA bases ATCctgegtatccccCCT which is to be checked for an even number of triples made of lower case characters For this we can make use of the command expr for a complete description see the appropriate manual page to evaluate the arithmetic remainder of a number divided by 3 for example gt expr 21 3 will print out zero But how to determine the number of lower case characters in the sequence First we will define a variable named base to hold the complete sequence set base ATCctgcgtatccccCCT a Now we are a
215. t L starts to bind to the inactive conformation of the receptor R but during the ligand binding process the receptor gets activated and the active ligand receptor complex LR is established 114 8 Special Topics in GPCR Research As pointed out the receptor activation can take place during different states of ligand binding In order to get more detailed insights into ligand induced receptor activation LigPath calculations can be performed For such a calculation a starting and a destination structure is needed The starting structure may be defined by the inactive receptor embedded in its natural surrounding like lipid bilayer intra and extracellular water and the ligand somewhere in the aqueous phase of the extracellular side In contrast the destination structure may be defined by the active ligand receptor complex embedded in its natural surrounding Both starting and destination structure can be obtained by homology modelling Subsequently both models should be embedded into the appropriate surrounding and molecular dynamic simulations see Chap 6 should be performed in order to obtain a well equilibrated starting and destination structure The aim of the LigPath calculation is to get deeper insight into the activation process during binding of a partial agonist As pointed out in Fig 8 7 several pathways la and 1b 2a and 2b and 3 have to be considered Consequently a complete systematic scan of the potential energy s
216. t of commands for an effective manipulation of data files necessary for different runs of modeling programs The central interface for getting the benefit of this performance is the so called shell the command line interpreter of a UNIX system In the last decade many different shells have become available to the user For example the Bourne Shell sh or bash the Korn Shell ksh the C Shell csh or the TC Shell tesh which will be utilized in this book The syntax of most so called external UNIX commands is independent of the choice of the shell Differences appear in commands internal to the shell or when one makes use of the meta characters Thus when a shell other than tcsh is used it is advisable to contact the appropriate manual pages to get information about specific syntax elements whereas most of the features of the tcsh will also be valid in the csh command interpreter To reproduce the examples and exercises of the following chapters the reader should be familiar with the basic concepts of files and directories including the concept of access modes and the corresponding commands to create remove copy rename or list these objects Furthermore the user should be able to operate on a text editor like gedit or vi 11 2 The Use of Shell Operators and Meta Characters in Tcsh Environments A UNIX command line exhibits the following general structure command options objects Therein the command denotes a
217. te Next create a file containing the data shown in Table 7 2 In this example we name the file ethanol sol dat which should look like this 0 00 90 02 0 05 204 43 0 10 124 34 0 20 76 86 0 30 54 48 0 40 38 24 0 45 22 34 0 50 13 78 0 55 11 96 0 60 41 98 0 70 41 61 94 7 Calculation of Gibbs Energy of Solvation 80 37 91 90 43 95 95 50 02 975 52 40 99 55 31 995 56 47 00 57 90 For integration perform the following command gt cat ethanol sol dat integrate The output should like this 20 7068 kJ mol Sometimes it might be the case that you have no pure dat file containing the two columns as given in ethanol sol dat Perhaps you have a xvg file xvg files are often an output of GROMACS Here you see an example file ethanol sol xvg This file was created Thu Dec 11 11 43 19 2008 by the following command mdrun v s md md o md c after md g shortlog mdrun is part of G R O M A C 8 GROwing Monsters And Cloning Shrimps title dG d 81 4 xaxis label lambda yaxis label dG d 81 4 kJ molNS 1NN N81N4 NS 1NN TYPE xy 0 00 90 02 0 05 204 43 0 10 124 34 0 20 76 86 0 30 54 48 0 40 38 24 0 45 22 34 0 50 13 78 0 55 11 96 0 60 41 98 0 70 41 6 0 80 37 91 0 90 43 95 0 95 50 02 0 975 52 40 7 2 Examples Conceptual and Practical
218. teractions between ethanol and water arriving in a system state 2 comprising of the pure solvent and a solute which will be considered as an ideal gas The Gibbs energy corresponding to state 1 will read CEtOH NEtOH RT In ezon n Hmo Hino RT In 7 26 7 2 Examples Conceptual and Practical Considerations 81 Here we assume a dilute solution of ethanol in water in order to neglect the interac tions between the solute molecules and the influence of remaining ethanol molecules on the interaction of a particular solute molecule with the solvent This assumption allows omitting the activity coefficients compare Chap 10 and so we are able to establish an ideal solution The reference chemical potential of the solvent refers to the pure solvent at 1 bar and 298 15 K The corresponding concentration variable is then given by the mole fraction xg o For state 2 we may write mol ino 7 27 where Uio y denotes the reference state of the ideal gas ethanol at standard pressure Taking the difference G 1 G 2 we arrive at G 1 ngou Mgog RT In ng oRT Inxmo 7 28 because the terms containing the reference chemical potential for the solvent cancel and the first term within parenthesis of the right hand side of Eq 7 28 corresponds to the Gibbs energy of solvation The left hand side of Eq 7 28
219. the difference between prediction Table 7 4 and experiment Table 7 5 for A H and A 59 is larger than for A reason for this difference might be that the force field parameters were optimized only with regard to but not with regard to AH and AS Villa and Mark 2002 A more detailed comparison between predicted and experimental Values for analogues of amino acid side chains can be found in literature Villa and Mark 2002 7 2 Examples Conceptual and Practical Considerations 99 Table 7 5 Thermodynamic parameters of solvation for ethanol at 25 C Cabani et al 1981 The standard entropy of solvation was calculated based on the standard Gibbs energy and enthalpy of solvation AG 20 98 kJ mol 52 40 kJ mol AS 105 4 J mol K 7 2 4 Example 2 Gibbs Energy of Binding Above we introduced the calculation of the Gibbs energy of solvation of a ligand in water However we are not interested in this value Rather in context of GPCRs we are interested in the Gibbs energy of binding AGpjng of a ligand from aqueous phase into the binding pocket of a GPCR Fig 7 7 To calculate this quantity the concept of thermodynamic integration already shown for ethanol in water can be used as well Fig 7 7 Thermodynamic cycle for a ligand in the binding pocket of a receptor coloured ligand full interactions grey ligand no Coulomb and van der Waals interactions Before
220. the highly conserved amino acid of each transmembrane domain has the same position in template and target 3 Now the alignment for the termini and loops can be performed There you have to take into account several points In most crystal structures the N terminus and C terminus are often not com plete Thus there you can perform the alignment of such regions but there is no real use in homology modelling since no template structure is given for such regions E1 I2 and E3 loop can be aligned easily in most cases to the template sequence However it should be taken into account that corresponding loops of different GPCRs could differ in their length This has to be taken carefully into account later on in the homology modelling To declare a vacant position in amino acid sequence a hyphen is used in general I3 loop differs significantly in length from some ten to some hundred amino acids within the different GPCRs Additionally the I3 loop is not com pletely present in the crystal structures available up to now Thus a complete alignment is useless for homology modelling However for MD simu lations it will be useful to close the open ends between TM V and TM VI 3 4 Homology Modelling 23 TMI hH1R 1 MSLPNSSCLLEDKMCEGNKTTMASPQLMPLVVVLST I CLVTVGLEELLVLYAVRSERKLHTVGNLY IVSLSVABLIVGA 78 hH4R 1 MPDTNSTINLSLSTRVTLAFFMSLVAFAIM LVILAFVVDKNLRHR
221. the most fast and most flexible one A short schematic description of an appropriate source code is illustrated in Fig 8 2 The coordinates of the whole system i e GPCR and Gocsubunit must be read in In the program code it should be separated between sites of the receptor and sites of the Ga subunit Afterwards you have to construct an architecture of six interlocking loop constructs In the first three loops the Ga subunit is translated in X y and z direction and in the last three loops the Ga subunit is rotated around the x y and z axis Please be aware that the loops must be ordered in an interlock ing manner A subsequent series each after the other does not result in the desired systematic search If you want to search on 10 points on each of the six dimensions three dimensions for translation and three dimensions for rotation you have to cal culate 105 points Within the 6th loop you have to write out the coordinates of your resulting structure including receptor and Ga subunit Be aware that only the coor dinates of the Ga subunit were changed Afterwards you can call the GROMACS Generation of a starting structure Reading the coordinates of the starting structure Translation of the Ga subunit in in x direction Fig 8 2 Schematic presentation of a procedure to perform a systematic surface scan between a GPCR and a Ga subunit loop Translation of the Ga loop 5 subunit in in y directi
222. the range 0 255 In most cases the exit number is of no importance to further work The second if statement carries out a test on the right number of base triples and the script exits if it fails All other commands correspond to statements in our loop exercise In order to test a few situations of calling the script enter the following commands and have a look onto the output gt triple gt triple aggt It should be mentioned that the script triple is subject of further extensions as to test if the base string contains for instance numbers or other special symbol Thus here we present only a basic work out 11 7 A More Extensive Example Construction of a sequence of amino acids from a base sequence using gawk To elucidate the use of the gawk command we will construct the sequence of amino acids resulting from a base sequence First create a file base dat which holds the base sequence gt cat gt base dat 156 11 Important UNIX LINUX Commands gt ATGGCCatgtctttcctcCACCATccccect gt d Next provide a file code dat containing the assignment of base triplets and amino acids see appendix 13 2 cat gt code dat Met aga Arg gga Gly tct Ser ttc Phe gca Ala ctc Leu Ag 1 Assume we want to translate the base sequence given by the first substring composed of lower case letters into a sequence of corresponding amino acids We will read the file code dat and c
223. the rmsd between the actual structure and the destination structure should be as small as possible too This criterion guarantees on the one and that only structures with low potential energies are chosen but on the other hand the structure is guided because of the different child groups without restraints into direction of the destination structure as pointed out in Fig 8 10 Based on the combined energy rmsd criterion mentioned above the best structure can be related with movement of ligand only with movement of receptor only or with movement of ligand and receptor Thus the pathway starting from the free ligand and free inactive receptor L 4 R forward to the active ligand recetor complex LR is not restrained This fact is very important in order to get knowledge at which stage of ligand penetration the receptor gets activated 116 8 Special Topics in GPCR Research L R 1a LR 2a 1b L R 2b LR Fig 8 10 Schematic presentation of a non restrained LigPath calculation the three arrows begin ning for each generation in the same origin represent the three groups of children in each generation the black arrows represent the best child of each generation the final point of each black arrow is the starting point for the next generation Copyright by Springer with permission from Springer For the binding of a partial agonist to a biogenic amine receptor the binding path way was calculated with the L
224. thermodynamical A Strasser H J Wittmann Modelling of GPCRs 1 DOI 10 1007 978 94 007 4596 4_1 Springer Science Business Media Dordrecht 2013 www allitebooks com 2 1 Introduction quantities So there were a lot of efforts in the past to classify ligands as agonists or antagonists with the help of AH and AS One attempt to distinguish between the two groups of ligands is based on the term enthalpy or entropy driven association pro cess Enthalpy driven means AH lt 0 and AS lt 0 entropy driven is indicated by AH gt 0 and AS gt 0 whereas AH lt 0 and AS gt 0 is called enthalpy entropy driven Weiland et al 1979 Wittmann et al 2009 But by investigating the extensive data material no definite discrimination between agonists and antagonists is possible on this basis The crucial point results from the fact that AH and AS determine the affinity of a ligand investigated in a binding assay But if we talk about agonists or antagonists we put our focus on the efficacy which will be determined from cor responding assays To combine binding properties like AH or AS with quantities describing the efficacy will not lead to satisfactory results Thus is there a chance at all to predict the binding behaviour of a ligand on the base of the thermodynamical concept discussed in Chap 10 As a first step we have to establish a binding model based on our knowledge or intuition of the interaction between the ligand and the
225. thors use the thermodynamic cycle presented in Fig 7 8 For calculation of the change in Gibbs energy of binding for mutation of the ligand CCK9 the authors use the following Eq 7 50 Ap AG 7 50 A comparison of the experimental and predicted results is given in Table 7 6 general the correlation between experimental and calculated data is well Thus this method may be useful for predicting the influence of a structural modification within the ligand with regard to binding affinity Example2 2 Within a pharmacological study the binding affinity of several phenyl histamines at the human histamine H4 receptor hRH4R was determined Wittmann et al 2011 The pharmacological data revealed large differences in binding affinity of the six phenylhistamines at hH4R as shown in Table 7 7 In order to explain the pharma cological data molecular modelling studies were performed Since the phenylhis tamines act as partial agonists at hH4R these compounds were docked into an active state model and subsequently molecular dynamic simulations were performed in order to obtain a stable binding mode The binding mode for two phenylhistamine derivatives is shown in Fig 7 9 Table 7 6 Comparison of experimental exp and calculated calc changes in Gibbs energy of binding with respect to mutations in the ligand CCK9 Henin et al 2006 The terms and represent the change in Gibbs energy of binding for
226. ties Even this modified procedure leads to a very time consuming calculation Thus ab initio methods are not suitable to handle bio chemical systems However sometimes this method is used in context with GPCR research Carloni et al 2002 Mehler et al 2006 Jongejan et al 2008 The so called semiempirical methods use potential functions based on some experimental insight to find local minima across the potential energy surface Stewart 1989 Stewart 2004 Lipkowitz et al 2007 This concept reduces the computational time but introduces a new problem based on the choice of the semiempirical method which seriously influences the computed results In order to get a very simple functional form of the potential energy resulting in small computational times molecular dynamics molecular mechanics makes use of so called force fields see Chap 9 which en tirely depend on empirical quantities so the quality of the results strongly depends on the experimental parameters used to define the particular force field To combine www allitebooks com Introduction 3 the well founded theoretical concept of quantum mechanics with the advantage of a short computational time hybrid methods such as quantum mechanics molecular mechanics QM MM concept are introduced Monard et al 1999 The interesting part of the system is calculated using the principles of quantum mechanics whereas the remainder of the system is treated by the methods of molecular me
227. tion crystal structure of an engineered human adrenergic protein coupled receptor Science 318 1258 1265 Chien EY Liu W Zhao Q Katritch V Han GW Hanson MA Shi L Newman AH Javitch JA Cherezov V Stevens RC 2010 Structure of the human dopamine receptor in complex with Do Ds selective antagonist Science 330 1091 1095 Choe HW Kim YJ Park JH Morizumi T Pai EF Kraub N Hofmann KP Scheerer P Ernst OP 2011 Crystal structure of metarhosopsin II Nature 471 651 655 Chou KC 2005 Coupling interaction thromboxane receptor and alpha 13 subunit of guanine nucleotide binding protein J Proteome Res 4 1681 1686 Christen M van Gunsteren WF 2008 On searching in sampling of and dynamically moving through conformational space of biomolecular systems a review J Comput Chem 29 157 166 Clark M Cramer RD van Opdenbosch N 1989 Validation of the general purpose tripos 5 2 force field J Comput Chem 10 982 1012 Cornell WD Cieplak B Bayly CI Gould IR Merz KM Ferguson DM Spellmeyer DC Fox T Caldwell JW Kollmann PA 1995 A second generation force field for the simulation of proteins nucleic acids and organic molecules J Am Chem Soc 117 5179 5197 Costanzi S Joshi BV Maddileti S Mamedova L Gonzalez Moa MJ Marquez VE Harden TK Jacobson KA 2005 Human P2Y receptor molecular modeling leads to the rational design of a novel agonist based on a unique conformational preference J Med Chem 48 8108 8111 Doman
228. tioned before meanwhile the molecular dynamic simulation of GPCRs in its natural surrounding is state of the art However it should be taken into account that in case of simulating a ligand receptor complex in its active state a pocket in the intracellular part of the GPCR is widely open Thus if the intracellular part of the GPCR is not in contact with the Go subunit but instead with water this might lead to artefacts in simulations Thus the inclusion of the G protein or at least a part of it during active state simulations is recom mended A crystal structure of opsin cocrystallized with the 11 last amino acids ofthe C terminus of Go is available Scheerer et al 2008 Thus by homology modelling this crystallized system inclusive the part of the C terminus of Ga can be adopted to the interesting system However the 11 last amino acids of the C terminus of Ga rep resent only a very small part of the whole Go and there are still important regions of interactions missing As already mentioned in Chap 2 in 2011 acrystal structure of the hB R GoBy complex which is shown Fig 2 7 was published for the first time code 3SN6 http www pdb org Rasmussen et al 2011 Despite the missing of a complete I3 loop and complete C terminus of hB R in the crystal structure 3SN6 http www pdb org this crystal gives a snapshot of one GPCR GaBy complex and thus a more detailed insight onto the interaction between a GPCR and a G protei
229. tot 6 441 N 53 HISB N 194 20 31 14 0067 qtot 5 69 442 H 53 HISB H 194 0 31 1 008 qtot 6 443 CH1 53 HISB CA 195 0 13 019 qtot 6 444 CH2 53 HISB cB 195 0 14 027 qtot 6 445 c 53 HISB 196 0 12 011 qtot 6 446 NR 53 HISB ND1 196 0 54 14 0067 qtot 5 46 447 CR1 53 HISB CD2 196 0 14 13 019 qtot 5 6 448 CR1 53 HISB 1 196 0 14 13 019 qtot 5 74 449 NR 53 HISB NE2 196 0 05 14 0067 qtot 5 69 450 H 53 HISB HE2 196 0 31 1 008 qtot 6 451 53 HISB 197 0 45 12 011 qtot 6 45 452 53 HISB 197 0 45 15 9994 qtot 6 453 N 54 VAL N 198 0 31 14 0067 qtot 5 69 454 H 54 VAL H 198 0 31 1 008 qtot 6 455 CH1 54 VAL CA 199 0 13 019 qtot 6 456 CH1 54 VAL CB 199 0 13 019 qtot 6 457 CH3 54 VAL CG1 199 0 15 035 qtot 6 458 CH3 54 VAL CG2 199 0 15 035 qtot 6 459 54 VAL c 200 0 27 12 011 qtot 6 27 460 OM 54 VAL 01 200 0 635 15 9994 qtot 5 635 461 54 VAL 02 200 0 635 15 9994 qtot 5 bonds ai aj funct cO c2 c3 1 2 2 2 1 3 2 gb2 6 4 Molecular Dynamic Simulation of your System 69 This topology file also consists of all information which is needed for construction of a position restraint file The protein consists of 461 sites which are defined from line 7 467 Thus to extract information with regard to site number and atom the lines 7 467 are important and they can be obtained via the command line gt head n 467 protein3 top tail n 461 If you perform the command as show
230. ubunit alpha isoform short P04896 GNAS UniProtKB sequence Isoform GNAS 1 Alpha S2 10 MGCLGNSKTE 70 RILHVNGFNG 130 NPENQFRVDY 190 KIDVIKQDDY 250 VTAIIFVVAS 310 VLAGKSKIED 370 PHFTCAVDTE 20 DORNEEKAQR 80 EGGEEDPQAA 140 ILSVMNVPDF 200 VPSDQDLLRC 260 SSYNMVIRED 320 YFPEFARYTT 380 NIRRVFNDCR 30 EANKKIEKOL 90 RSNSDGEKAT 150 DFPPEFYEHA 210 RVLTSGIFET 270 NOTNRLOEAL 330 PEDATPEPGE 390 DIIQRMHLRQ 40 OKDKOVYRAT 100 KVQDIKNNLK 160 KALWEDEGVR 220 KFQVDKVNFH 280 NLFKSIWNNR 340 DPRVTRAKYF YELL 50 HRLLLLGAGE 110 EAIETIVAAM 170 ACYERSNEYQ 230 MFDVGGQRDE 290 WLRTISVILF 350 IRDEFLRIST 60 SGKSTIVKOM 120 SNLVPPVELA 180 LIDCAQYFLD 240 RRKWIQCFND 300 LNKODLLAEK 360 ASGDGRHYCY sequence Isoform GNAS 2 Alpha S1 length 380 amino acids 10 MGCLGNSKTE 70 RILHVNGFNG 130 MNVPDFDFPP 190 QDLLRCRVLT 250 MVIREDNOTN 310 FARYTTPEDA 370 VFNDCRDIIQ 20 DQRNEEKAQR 80 DGEKATKVQD 140 EFYEHAKALW 200 SGIFETKFQV 260 RLOEALNLFK 320 TPEPGEDPRV 380 RMHLRQYELL 30 EANKKIEKQL 90 IKNNLKEAIE 150 EDEGVRACYE 210 DKVNFHMFDV 270 SIWNNRWLRT 330 TRAKYFIRDE 40 OKDKOVYRAT 100 TIVAAMSNLV 160 RSNEYQLIDC 220 GGORDERRKW 280 ISVILFLNKQ 340 FLRISTASGD 50 HRLLLLGAGE 110 PPVELANPEN 170 AQYFLDKIDV 230 IQCFNDVTAI 290 DLLAEKVLAG 350 GRHYCYPHFT
231. ules and ng moles of solvent molecules at a given pressure and temperature We assume that ns is much larger than Thus the interactions between the ligand particles may be neglected just as the influence of the ligand molecules on the solvation of 84 7 Calculation of Gibbs Energy of Solvation a particular ligand molecule The system state 2 will be defined for all interactions between ligand and solvent particles switched off so we have a system containing the ligand as an ideal gas and the pure solvent Making use of the concept of the foregoing section we are able to calculate the difference G 2 G 1 We may write the expressions for G 1 and G 2 from a thermodynamic point of view G 1 n 4 RT In RT In j 1 34 Co Here again for the solvent we make use of the reference chemical potential for the pure state of water at 1 bar and 298 15 K G 2 nsus 1 35 where u denote the reference chemical potential of the pure solvent with mole fraction xs and 7 denotes the reference chemical potential of the ligand as an ideal gas Substracting G 1 from G 2 yields 05 G n u RT In 2 Co ns u RT In 7 36 As the terms for the reference potential of the solvent cancel the Eq 7 36 now reads G 2 G l n uj RT In 2 nsRT ln xs 7 37 Next we will do a similar calculation for the ligand receptor complex whe
232. urface as shown schematically in Fig 8 8 has to be performed L R LR 2a P 1b L R LR Fig 8 8 Schematic presentation of a systematic surface scan the long black arrows indicate the direction for the pathway calculation whereas the white and black boxes represent schematically the lattice points used for surface calculation Copyright by Springer with permission from Springer To reduce the computation time the LigPath algorithm can be used alternatively to such a systematic scan Specific for the LigPath algorithm is the generation child scheme as illustrated in Fig 8 9 Therein in each cycle also named generation of the calculation three different groups of child structures are calculated In the first group Fig 8 9 D only the ligand atoms are guided differentially in direction of their destination position The guiding of the ligand atoms is combined with a Monte Carlo like procedure so that the guiding also has a random character In the second group Fig 8 9 ID only the atoms of the receptor are guided differentially in direction of their destination position As for the ligand atoms the guiding of the receptor atoms is combined with a Monte Carlo like procedure thus the guiding has a random character again In the third group Fig 8 9 IID ligand as well as receptor atoms differentially 8 2 Process of Ligand Binding from the Extracellular Side into the Binding 115 Starting point
233. used to create a simple data file example Create a file in the so called csv format with the name data using the second form of the command 11 4 Discussion of Selected LINUX Commands 145 gt cat gt data J Then the text cursor will be placed on the beginning of the next line Now enter the following strings each terminated by a newline character 1 DRG 3 39 2952 24 80 2 DRG 3 42 2934 24 92 3 DRN 3 29 3043 24 37 4 DRG 2 29 4376 24 46 5 S0L 2 13 4719 24 75 6 UNK 2 06 4864 24 74 To finish data input press the buttons Strg or Ctrl and abbrevi ation d simultaneously at the beginning of a new line to signalize END OF FILE to the shell Now the command gt cat data will print out the contents of the recently created data file with the name data cut syntax cut c n file cut c m n file cut c m n file cut d delim f n file cut d delim f m n file cut d delim f m n file explanation The first three instances of cut will perform the following tasks Print out the n th character of each line of a file Print out a range of characters m to n of each line of a file Print out the characters m n of each line of a file The last three commands use a character delim enclosed in single quotes to divide each line of a file into fields A line beginning with the character delim forces an empty first field Field numbering always sta
234. ve a particular problem just as you would enter these commands within a shell terminal Syntax errors would be easily eliminated in a test run and further on the script can be applied to similar applications of a project by means of minor changes To elucidate the implementation of a shell script we will repeat our last example First start an editor for example gedit Then enter the following statements one per line Empty lines will be ignored by the shell 4 bin tcsh Determine triples of DNA base sequence if 1 then echo Missing base string echo SYNTAX 0 base string exit 1 endif if expr 1 3 0 then echo wrong number of characters in base sequence exit 1 endif set n 21 set i l while i lt n j i 2 echo 1 cut c i j i i 3 end After the end statement of the while loop save this file for example as triple and quit the editor To start this script the user must have appropriate rights to execute the commands within the file Suppose a user mike has created this shell script After calling gt ls al triple the user will get the output presented in the next line rw r r lmike users 308 22 Jan 17 17 triple where the columns 2 10 represent the file access mode for user mike rw the owner of triple the members of the group users r and for others r indicating that user mike is able to read from and write to file t
235. ve to be performed Generate a complete model of the interesting GPCR Minimize the GPCR position restraints should be put onto at least the backbone of the GPCR Put your GPCR correct into the lipid bilayer see Chap 5 Equilibrate the lipid bilayer around the GPCR position restraints should be put onto at least the backbone of the GPCR If not already performed center your system in the simulation box Solvate your lipid GPCR complex with water see Chap 5 Minimize your complete system position restraints should be put onto at least the backbone of the GPCR Neutralize your simulation box to charge zero by putting an appropriate number of ions into the extra or intracellular water A Strasser H J Wittmann Modelling of GPCRs 59 DOI 10 1007 978 94 007 4596 4_6 Springer Science Business Media Dordrecht 2013 60 6 Minimization and Molecular Dynamics step 1 step 2 Fig 6 1 Main steps for construction of a simulation box of a GPCR in the lipid bilayer 6 1 Generating a Complete Model of the Interesting GPCR As already described in detail in Chap 3 you should have designed a homology model of your GPCR and minimize the model in the gas phase Fig 6 1 step 1 In order to avoid destroying of the helical structure of the transmembrane domains we recommend to set position constraints at least onto the backbone atoms Therefore you may use appropriate command of the GR
236. w expands to dat1 new and geo new 11 3 2 Variable Substitution Use of shell variables within commands will make work easier and more efficient The command set allows a user to define a name and assign a value to it 142 11 Important UNIX LINUX Commands gt set var 123 declares a variable var with the value 123 The name of a variable consists of case sensitive letters digits and the underscore _ not starting with a digit To reference the value of a variable the meta character is used Thus the command gt echo var will print 123 to standard output To remove a variable use the unset command gt unset var This will destroy the variable var Assume we will frequently copy files from a directory named share data project md Defining a variable dir with the value of the mentioned object gt set dir share data project md will simplify for example the cp command gt cp S dir enzyme we make use of the two meta characters for variable substitution and for file name substitution So all files in share data project md whose names start with enzyme will be copied to the current working directory indicated by a dot Now define a variable x with value 123 gt set x 123 J command gt echo xabc will result in an error message indicating that the shell will not recognize the name xabc To prevent the shell from misinterpreting the string xabc
237. wah JME or paste your input coordinates MOL SYBYL Moi fie or text Grzwing here Chry Xem vorm Please be patient hitbng Run PRODRG once is completely sufficient Fig 4 2 Site for compound submission of the PRODRG server Construction of Ligands 31 HEADER ETHANOL COMPND ETHANOL REMARK GENERATED BY SYBYL TRIPOS INC 15 AUG 10 HETATM 1 02 LIG 8 207 3 565 0 317 1 00 0 40 HETATM 2 H3 LIG 7 452 3 455 0 253 1 00 0 21 HETATM 3 C1 LIG 9 325 2 747 0 067 1 00 0 04 HETATM 4 H2 LIG 9 665 3 010 1 084 1 00 0 06 HETATM 5 H1 LIG 10 148 2 959 0 635 1 00 0 06 HETATM 6 C4 LIG 8 958 1 244 0 007 1 00 0 04 HETATM 7 H6 LIG 8 620 0 992 1 024 1 00 0 03 HETATM 8 H5 LIG 8 149 1 012 0 702 1 00 0 03 HETATM 9 H4 LIG 9 834 0 624 0 241 1 00 0 03 CONECT 1 2 3 CONECT 2 1 CONECT 3 1 4 5 6 CONECT 4 3 CONECT 5 3 CONECT 6 3 7 89 CONECT 7 6 CONECT 8 6 CONECT 9 6 MASTER 0 0 0 0 0 0 0 0 9 0 9 0 END Open the file ethanol pdb with an editor copy all data and paste them into the appropriate field of the PRODRG site shown in Fig 4 2 Since ethanol is not chiral you can choose no at the corresponding field Additionally choose full charges and yes with regard to EM EM means energy minimization Afterwards click at the button Run PRODRG
238. within ethanol The energy which is necessary to remove all non bonded internal interactions like Coulomb or van der Waals interaction for the solute in vacuum is represented by Fig 7 1 Therefore all sites of state 1 mutated gradually into dummy sites corresponding to state 2 In GROMACS for example a dummy is represented 7 2 Examples Conceptual and Practical Considerations 87 by DUM where all partial charges and van der Waals interaction parameters are set to zero Therefore in the section atoms three additional columns for type charge and mass of the dummy sites are necessary Setting the charges of all solute sites to zero and defining the site type DUM switches off the Coulomb and van der Waals interactions between the sites of the solute However all internal bonded interactions and masses remain unchanged The analogous energy term to remove all non bonded internal interactions for the solute and between the solute and the solvent is described by A 5 Fig 7 1 neglecting the concentration terms for ethanol and water as discussed in this chapter in the framework of parameter adjustment Therefore the same procedure as mentioned above for AG has to be performed The energy which is necessary to transfer the dummy solute from vacuum into solvent is described by A G gt Fig 7 1 Since there is no interaction of the dummy solute with the remaining system this value is zero The values for AG and AG3
239. wn about the interaction of a GPCR with a G protein on molecular level On the on hand there is an increasing number of crystal structures of GPCRs described in literature see Appendix Important Crystal Structures of GPCRs Source http www pdb org and on the other hand some crystal structures of heterotrimeric G proteins are known Recently the structure of opsin cocrystallized with a part of the C terminus of was published Scheerer et al 2008 But until 2011 there exists no crystal structure of a complete GPCR G protein complex However within a small number of experimental and theoretical studies the interactions between GPCR and G protein were investigated Fanelli et al 1999 Greasley et al 2001 Oliveira et al 2003 Chou 2005 Raimondi et al 2008 In general there is only little knowledge about the interactions between GPCR and G protein on molecular level In literature two different models with regard to GPCR G protein coupling are discussed This is on the one hand the so called collision coupling model Within this model it is suggested that only the active receptor interacts with the G protein Tolkovsky et al 1978 In contrast the second model the so called precoupling model suggests that the G proteins interact with the GPCR before the receptor is activated by an partial agonist Thus GPCR and G protein are pre coupled The precoupling model is provided by several studies Alves et al 2003 2005 Ga
240. wo ligand receptor complexes will result in the determination of the sum CLRI T CLR2 10 37 which reads as c c CLRI t 2 Ki 22 10 38 1 K o The right hand side of Eq 10 38 exhibits the same form as the right hand side of Eq 10 23 in the case of exact one ligand receptor complex As a consequence it is impossible to determine the binding constants K gt of each complex separately using traditional experimental techniques but we will get only the sum K2 The only possibility to get information on the properties of the distinct orientations of the ligand in the binding pocket of the receptor exists in constructing a model for each ligand receptor complex and calculating the corresponding binding constants afterwards The sum of these quantities has to be compared to the experimental value of K gt for validation of the model So if we are forced to deal with more than two orientations we will encounter much more difficulties to gain information about the binding properties of ligands Chapter 11 Important UNIX LINUX Commands 11 1 Some Basic Aspects of the Operating System UNIX LINUX UNIX especially its implementation LINUX is a very powerful tool to perform all the tasks in the framework of molecular modelling On the one hand a lot of programs dealing with molecular modelling make use of the operating system UNIX which on the other hand offers an extensive se
241. wrong System setup and the lipid bilayer one might think that the system has to be solvated in the next step Doing so would lead to an artificial system as pointed out in Fig 5 11 Due to the gap between the GPCR and the lipid bilayer a large number of water molecules would be put into this gap during the solvation of the system This water between the GPCR and the lipid bilayer is artificial and may lead to problems during the simulation or to artefacts because the hydrophobic transmembrane domains of the receptor and the hydrophobic fatty acid side chains of the lipids are in contact to the hydrophilic water Thus both the hydrophobic side chains and lipids might obtain energetically more favoured conformations without contact to the hydrophilic water This may lead to instabilities of the receptor during simulation However some 10 water molecules all in all between lipid and receptor should not lead to problems during the simulation They can be removed but in most cases they move into the extra or intracellular water during the simulation In order to avoid scenarios as illustrated in Fig 5 11 the lipid bilayer should be equilibrated around the GPCR Fig 5 12 before solvating the system Therefore different simulation protocols can be used However positions constraints have to be put at least onto the protein in order to avoid any conformational change of the protein during the lipid equilibration process In order to o
242. y a relational expression The expression i 3 is evaluated as the last one after each set of the loop statements and increments the controlling variable i by three So the loop will be exited if the value of i becomes equal to the value of RLENGTH The next 158 11 Important UNIX LINUX Commands pair of braces holds the so called loop statements comprising the definition of the variable triple and the concatenation of the strings out and the amino acid name AS triple with the help of a blank as the appropriate operator Note that in case of more than one statement inside a loop all the statements have to be placed into braces As a last step the whole amino acid sequence is printed out Of course the last gawk command exhibits a very complex structure so typing it on the command line may be very hard especially in the case of spelling mistakes To avoid such problems gawk is able to interpret a script containing the pattern action statements To create such a command script start an editor and enter the program between the quotes of the last gawk command Take into consideration that the first line of this script must have the following form if we assume gawk resides in the directory usr bin d usr bin gawk f The shell will start the command gawk with the option and the script name as the next argument Additional arguments on the command line will be made available to gawk in the usual manner Assume the script wil
243. ylmoieties of the ligand Due to the binding process of the ligand Fig 8 13 1 the ligand gets in close contact to Phe5 5_ This induces a cascade of conformational changes Fig 8 13 2 5 55 undergoes large conforma tional change in the early beginning of the binding process Fig 8 12 The dihedral angles of the 655 side chain change significantly during the process of ligand binding and switch back into their original conformation after the ligand is bound to the binding pocket Fig 8 13 Sequence of conformational changes of distinct amino acid side chains during binding of a partial agonist Copyright by Springer with permission from Springer 8 2 Process of Ligand Binding from the Extracellular Side into the Binding 119 During the whole phase of ligand penetration further changes in dihedral angles of Phe Tyr Trp 8 and Phe9 could be observed Fig 8 12 However changes during ligand penetration and receptor activation do not take place only in the upper part of the transmembrane domains but also in the intracel lular part Some representative changes of amino acid conformations within the H receptor during activation are shown in Figs 8 14 and 8 15 ds ts tots inactive r H active Fig 8 14 Snapshots of Trp 8 Phe 44 and Ser during the activation process of the gpHiR Copyright by Springer with permission from Springer Fig 8 15 Ser switch and
244. you have to define bonds angles and dihedrals which is a very complicated procedure for a beginner Besides generating a topology file manually is very susceptible for mistakes Solving this task you can use the PRODRG server http davapc1 bioch dundee ac uk prodrg The starting page of the server is shown in Fig 4 1 If you have started the PRODRG server http davapcl bioch dundee ac uk prodrg use the button Run PRODRG which will bring up the next page Fig 4 2 The academic use of the PRODRG server is free but in order to avoid abuse one user is allowed to perform about three runs per day Therefore you have to order a so called token by submitting your e mail address Within some minutes you should get your token Now copy and paste your valid token into the appropriate field Afterwards you can fill the remaining fields and submit your PRODRG job For obtaining the GROMACS coordinate and topology file of ethanol for example start a molecule editor like chimera construct ethanol and save the molecule as pdb file named ethanol pdb A Strasser H J Wittmann Modelling of GPCRs 29 DOI 10 1007 978 94 007 4596 4_4 Springer Science Business Media Dordrecht 2013 30 4 Construction of Ligands Que W The PROURG Server lt ih GlycogioChem PRODRG Home Run PRODRG X ray refinement VO PROORG will take description of small molecule as

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