Skip to main content
SpringerLink
Log in

Homology Modeling and Docking Evaluation of Human Muscarinic Acetylcholine Receptors

  • Protocol
Muscarinic Receptor: From Structure to Animal Models

Part of the book series: Neuromethods ((NM,volume 107))

Abstract

The development of GPCR homology models for virtual screening is an active area of research. Here we describe methods for homology modeling of the acetylcholine muscarinic receptors M1R–M5R. The models are based on the β2-adrenergic receptor crystal structure as the template and binding sites are optimized for ligand binding. An important aspect of homology modeling is the evaluation of the models for their ability to discriminate between active compounds and (presumed) inactive decoy compounds by virtual screening. The predictive ability is quantified using enrichment factors, area under the ROC curve (AUC), and an early enrichment measure, LogAUC. The models produce good enrichment capacity, which demonstrates their unbiased predictive ability. The optimized M1R–M5R homology models have been made freely available to the scientific community to allow researchers to use these structures, compare them to their results, and thus advance the development of better modeling approaches.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Palczewski K, Kumasaka T, Hori T, Behnke CA, Motoshima H, Fox BA, Le Trong I, Teller DC, Okada T, Stenkamp RE, Yamamoto M, Miyano M (2000) Crystal structure of rhodopsin: a G protein-coupled receptor. Science 289(5480):739–745

    Article  CAS  PubMed  Google Scholar 

  2. Cherezov V, Rosenbaum DM, Hanson MA, Rasmussen SG, Thian FS, Kobilka TS, Choi HJ, Kuhn P, Weis WI, Kobilka BK, Stevens RC (2007) High-resolution crystal structure of an engineered human beta2-adrenergic G protein-coupled receptor. Science 318(5854):1258–1265

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  3. Rasmussen SG, Choi HJ, Rosenbaum DM, Kobilka TS, Thian FS, Edwards PC, Burghammer M, Ratnala VR, Sanishvili R, Fischetti RF, Schertler GF, Weis WI, Kobilka BK (2007) Crystal structure of the human beta2 adrenergic G-protein-coupled receptor. Nature 450(7168):383–387

    Article  CAS  PubMed  Google Scholar 

  4. Rosenbaum DM, Cherezov V, Hanson MA, Rasmussen SG, Thian FS, Kobilka TS, Choi HJ, Yao XJ, Weis WI, Stevens RC, Kobilka BK (2007) GPCR engineering yields high-resolution structural insights into beta2-adrenergic receptor function. Science 318(5854):1266–1273

    Article  CAS  PubMed  Google Scholar 

  5. Yang J, Zhang Y (2014) GPCRS-EXP: a database for experimentally solved GPCR structures. http://zhanglab.ccmb.med.umich.edu/GPCR-EXP/. Accessed 3 Dec 2014

  6. Fredriksson R, Lagerstrom MC, Lundin LG, Schioth HB (2003) The G-protein-coupled receptors in the human genome form five main families. Phylogenetic analysis, paralogon groups, and fingerprints. Mol Pharmacol 63(6):1256–1272. doi:10.1124/mol.63.6.1256

    Article  CAS  PubMed  Google Scholar 

  7. Shoichet BK, Kobilka BK (2012) Structure-based drug screening for G-protein-coupled receptors. Trends Pharmacol Sci 33(5):268–272. doi:10.1016/j.tips.2012.03.007

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  8. Stevens RC, Cherezov V, Katritch V, Abagyan R, Kuhn P, Rosen H, Wuthrich K (2013) The GPCR Network: a large-scale collaboration to determine human GPCR structure and function. Nat Rev Drug Discov 12(1):25–34. doi:10.1038/nrd3859

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Mason JS, Bortolato A, Congreve M, Marshall FH (2012) New insights from structural biology into the druggability of G protein-coupled receptors. Trends Pharmacol Sci 33(5):249–260. doi:10.1016/j.tips.2012.02.005

    Article  CAS  PubMed  Google Scholar 

  10. Granier S, Kobilka B (2012) A new era of GPCR structural and chemical biology. Nat Chem Biol 8(8):670–673. doi:10.1038/nchembio.1025

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  11. Kooistra AJ, Roumen L, Leurs R, de Esch IJ, de Graaf C (2013) From heptahelical bundle to hits from the haystack: structure-based virtual screening for GPCR ligands. Methods Enzymol 522:279–336. doi:10.1016/B978-0-12-407865-9.00015-7

    Article  CAS  PubMed  Google Scholar 

  12. Thomas T, McLean KC, McRobb FM, Manallack DT, Chalmers DK, Yuriev E (2014) Homology modeling of human muscarinic acetylcholine receptors. J Chem Inf Model 54(1):243–253. doi:10.1021/ci400502u

    Article  CAS  PubMed  Google Scholar 

  13. Costanzi S (2013) Modeling G protein-coupled receptors and their interactions with ligands. Curr Opin Struct Biol 23(2):185–190. doi:10.1016/j.sbi.2013.01.008

    Article  CAS  PubMed  Google Scholar 

  14. Yuriev E, Agostino M, Ramsland PA (2011) Challenges and advances in computational docking: 2009 in review. J Mol Recognit 24:149–164

    Article  CAS  PubMed  Google Scholar 

  15. Yuriev E, Ramsland PA (2013) Latest developments in molecular docking: 2010–2011 in review. J Mol Recognit 26(5):215–239. doi:10.1002/jmr.2266

    Article  CAS  PubMed  Google Scholar 

  16. McRobb FM, Capuano B, Crosby IT, Chalmers D, Yuriev E (2010) Homology modeling and docking evaluation of aminergic G protein-coupled receptors. J Chem Inf Model 50:626–637

    Article  CAS  PubMed  Google Scholar 

  17. Wess J, Eglen RM, Gautam D (2007) Muscarinic acetylcholine receptors: mutant mice provide new insights for drug development. Nat Rev Drug Discov 6(9):721–733. doi:10.1038/nrd2379

    Article  CAS  PubMed  Google Scholar 

  18. Kruse AC, Weiss DR, Rossi M, Hu J, Hu K, Eitel K, Gmeiner P, Wess J, Kobilka BK, Shoichet BK (2013) Muscarinic receptors as model targets and antitargets for structure-based ligand discovery. Mol Pharmacol 84(4):528–540. doi:10.1124/mol.113.087551

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  19. Sherman W, Day T, Jacobson MP, Friesner RA, Farid R (2006) Novel procedure for modeling ligand/receptor induced fit effects. J Med Chem 49(2):534–553

    Article  CAS  PubMed  Google Scholar 

  20. Gregory KJ, Hall NE, Tobin AB, Sexton PM, Christopoulos A (2010) Identification of orthosteric and allosteric site mutations in M2 muscarinic acetylcholine receptors that contribute to ligand-selective signaling bias. J Biol Chem 285(10):7459–7474

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  21. Valant C, Gregory KJ, Hall NE, Scammells PJ, Lew MJ, Sexton PM, Christopoulos A (2008) A novel mechanism of G protein-coupled receptor functional selectivity. Muscarinic partial agonist McN-A-343 as a bitopic orthosteric/allosteric ligand. J Biol Chem 283(43):29312–29321. doi:10.1074/jbc.M803801200

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  22. Marquer C, Fruchart-Gaillard C, Letellier G, Marcon E, Mourier G, Zinn-Justin S, Menez A, Servent D, Gilquin B (2011) Structural model of ligand-G protein-coupled receptor (GPCR) complex based on experimental double mutant cycle data: MT7 snake toxin bound to dimeric hM1 muscarinic receptor. J Biol Chem 286(36):31661–31675. doi:10.1074/jbc.M111.261404

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  23. Martinez-Archundia M, Cordomi A, Garriga P, Perez JJ (2012) Molecular modeling of the M3 acetylcholine muscarinic receptor and its binding site. J Biomed Biotechnol 2012:789741. doi:10.1155/2012/789741

    Article  PubMed Central  PubMed  Google Scholar 

  24. Huang X, Zheng G, Zhan CG (2012) Microscopic binding of M5 muscarinic acetylcholine receptor with antagonists by homology modeling, molecular docking, and molecular dynamics simulation. J Phys Chem B 116(1):532–541. doi:10.1021/jp210579b

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  25. Zheng G, Smith AM, Huang X, Subramanian KL, Siripurapu KB, Deaciuc A, Zhan CG, Dwoskin LP (2013) Structural modifications to tetrahydropyridine-3-carboxylate esters en route to the discovery of M5-preferring muscarinic receptor orthosteric antagonists. J Med Chem 56(4):1693–1703. doi:10.1021/jm301774u

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  26. Jakubik J, Randakova A, Dolezal V (2013) On homology modeling of the M2 muscarinic acetylcholine receptor subtype. J Comput Aided Mol Des 27(6):525–538. doi:10.1007/s10822-013-9660-8

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  27. Blaney FE, Raveglia LF, Artico M, Cavagnera S, Dartois C, Farina C, Grugni M, Gagliardi S, Luttmann MA, Martinelli M, Nadler GM, Parini C, Petrillo P, Sarau HM, Scheideler MA, Hay DW, Giardina GA (2001) Stepwise modulation of neurokinin-3 and neurokinin-2 receptor affinity and selectivity in quinoline tachykinin receptor antagonists. J Med Chem 44(11):1675–1689

    Article  CAS  PubMed  Google Scholar 

  28. Lebon G, Langmead CJ, Tehan BG, Hulme EC (2009) Mutagenic mapping suggests a novel binding mode for selective agonists of M1 muscarinic acetylcholine receptors. Mol Pharmacol 75(2):331–341. doi:10.1124/mol.108.050963

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  29. Avlani VA, Langmead CJ, Guida E, Wood MD, Tehan BG, Herdon HJ, Watson JM, Sexton PM, Christopoulos A (2010) Orthosteric and allosteric modes of interaction of novel selective agonists of the M1 muscarinic acetylcholine receptor. Mol Pharmacol 78(1):94–104. doi:10.1124/mol.110.064345

    Article  CAS  PubMed  Google Scholar 

  30. Kaye RG, Saldanha JW, Lu ZL, Hulme EC (2011) Helix 8 of the M1 muscarinic acetylcholine receptor: scanning mutagenesis delineates a G protein recognition site. Mol Pharmacol 79(4):701–709. doi:10.1124/mol.110.070177

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  31. Xu J, Chen H (2012) Interpreting the structural mechanism of action for MT7 and human muscarinic acetylcholine receptor 1 complex by modeling protein-protein interaction. J Biomol Struct Dyn 30(1):30–44. doi:10.1080/07391102.2012.674188

    Article  PubMed  Google Scholar 

  32. Daval SB, Valant C, Bonnet D, Kellenberger E, Hibert M, Galzi JL, Ilien B (2012) Fluorescent derivatives of AC-42 to probe bitopic orthosteric/allosteric binding mechanisms on muscarinic M1 receptors. J Med Chem 55(5):2125–2143. doi:10.1021/jm201348t

    Article  CAS  PubMed  Google Scholar 

  33. Daval SB, Kellenberger E, Bonnet D, Utard V, Galzi JL, Ilien B (2013) Exploration of the orthosteric/allosteric interface in human M1 muscarinic receptors by bitopic fluorescent ligands. Mol Pharmacol 84:71–85. doi:10.1124/mol.113.085670

    Article  CAS  PubMed  Google Scholar 

  34. Jójárt B, Balint AM, Balint S, Viskolcz B (2012) Homology modeling and validation of the human M1 muscarinic acetylcholine receptor. Mol Inf 31(9):635–638. doi:10.1002/minf.201200062

    Article  Google Scholar 

  35. Jacobson MA, Kreatsoulas C, Pascarella DM, O’Brien JA, Sur C (2010) The M1 muscarinic receptor allosteric agonists AC-42 and 1-[1′-(2-methylbenzyl)-1,4′-bipiperidin-4-yl]-1,3-dihydro-2H-benzimidazol-2-one bind to a unique site distinct from the acetylcholine orthosteric site. Mol Pharmacol 78(4):648–657. doi:10.1124/mol.110.065771

    Article  CAS  PubMed  Google Scholar 

  36. Ma L, Seager MA, Wittmann M, Jacobson M, Bickel D, Burno M, Jones K, Graufelds VK, Xu G, Pearson M, McCampbell A, Gaspar R, Shughrue P, Danziger A, Regan C, Flick R, Pascarella D, Garson S, Doran S, Kreatsoulas C, Veng L, Lindsley CW, Shipe W, Kuduk S, Sur C, Kinney G, Seabrook GR, Ray WJ (2009) Selective activation of the M1 muscarinic acetylcholine receptor achieved by allosteric potentiation. Proc Natl Acad Sci U S A 106(37):15950–15955. doi:10.1073/pnas.0900903106

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  37. Chin SP, Buckle MJC, Chalmers DK, Yuriev E, Doughty SW (2014) Towards activated homology models of the human M1 muscarinic acetylcholine receptor. J Mol Graph Model 49:91–98

    Article  CAS  PubMed  Google Scholar 

  38. McMillin SM, Heusel M, Liu T, Costanzi S, Wess J (2011) Structural basis of M3 muscarinic receptor dimer/oligomer formation. J Biol Chem 286(32):28584–28598. doi:10.1074/jbc.M111.259788

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  39. Espinoza-Fonseca LM, Pedretti A, Vistoli G (2008) Structure and dynamics of the full-length M1 muscarinic acetylcholine receptor studied by molecular dynamics simulations. Arch Biochem Biophys 469(1):142–150. doi:10.1016/j.abb.2007.09.002

    Article  CAS  PubMed  Google Scholar 

  40. Suite 2012: Maestro, version 9.3; LigPrep, version 2.5; Schrödinger Suite 2012 Protein Preparation Wizard; Schrödinger Suite 2012 Induced Fit Docking protocol; Glide version 5.8; Prime version 3.1, Schrödinger, LLC (2012). New York, NY

    Google Scholar 

  41. Jacobson MP, Pincus DL, Rapp CS, Day TJ, Honig B, Shaw DE, Friesner RA (2004) A hierarchical approach to all-atom protein loop prediction. Proteins 55(2):351–367

    Article  CAS  PubMed  Google Scholar 

  42. Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22(22):4673–4680

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  43. Sastry GM, Adzhigirey M, Day T, Annabhimoju R, Sherman W (2013) Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. J Comput Aided Mol Des 27(3):221–234. doi:10.1007/s10822-013-9644-8

    Article  PubMed  Google Scholar 

  44. Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47(7):1739–1749

    Article  CAS  PubMed  Google Scholar 

  45. Halgren TA, Murphy RB, Friesner RA, Beard HS, Frye LL, Pollard WT, Banks JL (2004) Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J Med Chem 47(7):1750–1759

    Article  CAS  PubMed  Google Scholar 

  46. Chalmers DK, Roberts BP (2011) Silico—a Perl Molecular Modelling Toolkit, Monash University: Melbourne

    Google Scholar 

  47. Mobarec JC, Sanchez R, Filizola M (2009) Modern homology modeling of G-protein coupled receptors: which structural template to use? J Med Chem 52(16):5207–5216. doi:10.1021/jm9005252

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  48. Kolaczkowski M, Bucki A, Feder M, Pawlowski M (2013) Ligand-optimized homology models of D1 and D2 dopamine receptors: application for virtual screening. J Chem Inf Model 53:638–648. doi:10.1021/ci300413h

    Article  CAS  PubMed  Google Scholar 

  49. Pala D, Beuming T, Sherman W, Lodola A, Rivara S, Mor M (2013) Structure-based virtual screening of MT2 melatonin receptor: influence of template choice and structural refinement. J Chem Inf Model 53(4):821–835. doi:10.1021/ci4000147

    Article  CAS  PubMed  Google Scholar 

  50. Rataj K, Witek J, Mordalski S, Kosciolek T, Bojarski AJ (2014) Impact of template choice on homology model efficiency in virtual screening. J Chem Inf Model 54(6):1661–1668. doi:10.1021/ci500001f

    Article  CAS  PubMed  Google Scholar 

  51. Tang H, Wang XS, Hsieh JH, Tropsha A (2012) Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening? Proteins 80(6):1503–1521. doi:10.1002/prot.24035

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  52. Beuming T, Sherman W (2012) Current assessment of docking into GPCR crystal structures and homology models: successes, challenges, and guidelines. J Chem Inf Model 52(12):3263–3277. doi:10.1021/ci300411b

    Article  CAS  PubMed  Google Scholar 

  53. Phatak SS, Gatica EA, Cavasotto CN (2010) Ligand-steered modeling and docking: a benchmarking study in class a g-protein-coupled receptors. J Chem Inf Model 50(12):2119–2128

    Article  CAS  PubMed  Google Scholar 

  54. Neves MA, Simoes S, Sáe Melo ML (2010) Ligand-guided optimization of CXCR4 homology models for virtual screening using a multiple chemotype approach. J Comput Aided Mol Des 24(12):1023–1033

    Article  CAS  PubMed  Google Scholar 

  55. Katritch V, Kufareva I, Abagyan R (2011) Structure based prediction of subtype-selectivity for adenosine receptor antagonists. Neuropharmacology 60(1):108–115. doi:10.1016/j.neuropharm.2010.07.009

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  56. Kufareva I, Rueda M, Katritch V, Stevens RC, Abagyan R (2011) Status of GPCR modeling and docking as reflected by community-wide GPCR Dock 2010 assessment. Structure 19(8):1108–1126. doi:10.1016/j.str.2011.05.012

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  57. Michino M, Abola E, Brooks CL III, Dixon JS, Moult J, Stevens RC (2009) Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008. Nat Rev Drug Discov 8(6):455–463

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  58. Kufareva I, Katritch V, Participants of GPCR Dock 2013, Stevens RC, Abagyan R (2014) Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: meeting new challenges. Structure 22(8):1120–1139. doi:10.1016/j.str.2014.06.012

    Article  CAS  PubMed  Google Scholar 

  59. Ballesteros JA, Weinstein H, Stuart CS (1995) Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptors. Methods Neurosci 25:366–428

    Article  CAS  Google Scholar 

  60. Bymaster FP, Felder CC, Tzavara E, Nomikos GG, Calligaro DO, McKinzie DL (2003) Muscarinic mechanisms of antipsychotic atypicality. Prog Neuro Psychopharmacol Biol Psychiatry 27(7):1125–1143. doi:10.1016/j.pnpbp.2003.09.008

    Article  CAS  Google Scholar 

  61. Holst B, Nygaard R, Valentin-Hansen L, Bach A, Engelstoft MS, Petersen PS, Frimurer TM, Schwartz TW (2010) A conserved aromatic lock for the tryptophan rotameric switch in TM-VI of seven-transmembrane receptors. J Biol Chem 285(6):3973–3985. doi:10.1074/jbc.M109.064725

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  62. Spalding TA, Birdsall NJ, Curtis CA, Hulme EC (1994) Acetylcholine mustard labels the binding site aspartate in muscarinic acetylcholine receptors. J Biol Chem 269(6):4092–4097

    CAS  PubMed  Google Scholar 

  63. Anighoro A, Rastelli G (2013) Enrichment factor analyses on G-protein coupled receptors with known crystal structure. J Chem Inf Model 53(4):739–743. doi:10.1021/ci4000745

    Article  CAS  PubMed  Google Scholar 

  64. Gatica EA, Cavasotto CN (2012) Ligand and decoy sets for docking to G protein-coupled receptors. J Chem Inf Model 52(1):1–6. doi:10.1021/Ci200412p

    Article  CAS  PubMed  Google Scholar 

  65. Okuno Y, Tamon A, Yabuuchi H, Niijima S, Minowa Y, Tonomura K, Kunimoto R, Feng C (2008) GLIDA: GPCR—ligand database for chemical genomics drug discovery—database and tools update. Nucleic Acids Res 36(Suppl 1):D907–D912. doi:10.1093/nar/gkm948

    CAS  PubMed Central  PubMed  Google Scholar 

  66. Huang N, Shoichet BK, Irwin JJ (2006) Benchmarking sets for molecular docking. J Med Chem 49(23):6789–6801

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  67. Irwin JJ, Sterling T, Mysinger MM, Bolstad ES, Coleman RG (2012) ZINC: a free tool to discover chemistry for biology. J Chem Inf Model 52:1757–1768. doi:10.1021/ci3001277

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  68. Shi L, Javitch JA (2002) The binding site of aminergic G protein-coupled receptors: the transmembrane segments and second extracellular loop. Annu Rev Pharmacol Toxicol 42:437–467. doi:10.1146/annurev.pharmtox.42.091101.144224

    Article  CAS  PubMed  Google Scholar 

  69. Hawkins PCD, Warren GL, Skillman AG, Nicholls A (2008) How to do an evaluation: pitfalls and traps. J Comput Aided Mol Des 22(3–4):179–190

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  70. Nicholls A (2008) What do we know and when do we know it? J Comput Aided Mol Des 22(3–4):239–255

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  71. Mysinger MM, Shoichet BK (2010) Rapid context-dependent ligand desolvation in molecular docking. J Chem Inf Model 50(9):1561–1573

    Article  CAS  PubMed  Google Scholar 

  72. Katritch V, Rueda M, Lam PC, Yeager M, Abagyan R (2010) GPCR 3D homology models for ligand screening: lessons learned from blind predictions of adenosine A2a receptor complex. Proteins 78(1):197–211

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  73. Lin X, Huang XP, Chen G, Whaley R, Peng S, Wang Y, Zhang G, Wang SX, Wang S, Roth BL, Huang N (2012) Life beyond kinases: structure-based discovery of sorafenib as nanomolar antagonist of 5-HT receptors. J Med Chem 55(12):5749–5759. doi:10.1021/jm300338m

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  74. Miao Y, Nichols SE, Gasper PM, Metzger VT, McCammon JA (2013) Activation and dynamic network of the M2 muscarinic receptor. Proc Natl Acad Sci U S A 110(27):10982–10987. doi:10.1073/pnas.1309755110

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  75. Bottegoni G, Rocchia W, Rueda M, Abagyan R, Cavalli A (2011) Systematic exploitation of multiple receptor conformations for virtual ligand screening. PLoS One 6(5), e18845. doi:10.1371/journal.pone.0018845

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  76. Korb O, Olsson TS, Bowden SJ, Hall RJ, Verdonk ML, Liebeschuetz JW, Cole JC (2012) Potential and limitations of ensemble docking. J Chem Inf Model 52(5):1262–1274. doi:10.1021/ci2005934

    Article  CAS  PubMed  Google Scholar 

  77. Rueda M, Totrov M, Abagyan R (2012) ALiBERO: evolving a team of complementary pocket conformations rather than a single leader. J Chem Inf Model 52(10):2705–2714. doi:10.1021/ci3001088

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  78. Xu M, Lill MA (2012) Utilizing experimental data for reducing ensemble size in flexible-protein docking. J Chem Inf Model 52(1):187–198. doi:10.1021/ci200428t

    Article  CAS  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgments

T.T. is a recipient of an Australian Postgraduate Award (APA) scholarship. This work was supported by the Victorian Life Sciences Computation Initiative (VLSCI, grant number VR0004), and by the National Computational Infrastructure (grant number: y96), which is supported by the Australian Commonwealth Government.

Author information

Authors and Affiliations

  1. Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville Campus, 381 Royal Parade, Parkville, VIC, 3052, Australia

    Trayder Thomas, David K. Chalmers & Elizabeth Yuriev

Authors
  1. Trayder Thomas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David K. Chalmers
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elizabeth Yuriev
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to David K. Chalmers or Elizabeth Yuriev .

Editor information

Editors and Affiliations

  1. Institute of Physiology, Charles University, Prague, Czech Republic

    Jaromir Myslivecek

  2. Department of Neurochemistry, Acad. of Sciences of the Czech Rep. Institute of Physiology, Prague, Czech Republic

    Jan Jakubik

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media New York

About this protocol

Cite this protocol

Thomas, T., Chalmers, D.K., Yuriev, E. (2016). Homology Modeling and Docking Evaluation of Human Muscarinic Acetylcholine Receptors. In: Myslivecek, J., Jakubik, J. (eds) Muscarinic Receptor: From Structure to Animal Models. Neuromethods, vol 107. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2858-3_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2858-3_2

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-2857-6

  • Online ISBN: 978-1-4939-2858-3

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation