Skip to main content
SpringerLink
Log in

Homology modeling of opioid receptor-ligand complexes using experimental constraints

  • Published:
The AAPS Journal Aims and scope Submit manuscript

Abstract

Opioid receptors interact with a variety of ligands, including endogenous peptides, opiates, and thousands of synthetic compounds with different structural scaffolds. In the absence of experimental structures of opioid receptors, theoretical modeling remains an important tool for structurefunction analysis. The combination of experimental studies and modeling approaches allows development of realistic models of ligand-receptor complexes helpful for elucidation of the molecular determinants of ligand affinity and selectivity and for understanding mechanisms of functional agonism or antagonism. In this review we provide a brief critical assessment of the status of such theoretical modeling and describe some common problems and their possible solutions. Currently, there are no reliable theoretical methods to generate the models in a completely automatic fashion. Models of higher accuracy can be produced if homology modeling, based on the rhodopsin X-ray template, is supplemented by experimental structural constraints appropriate for the active orinactive receptor conformations, together with receptor-specific and ligand-specific interactions. The experimental constraints can be derived from mutagenesis and cross-linking studies, correlative replacements of ligand and receptor groups, and incorporation of metal binding sites between residues of receptors or receptors and ligands. This review focuses on the analysis of similarity and differences of the refined homology models of μ, δ, and κ-opioid receptors in active and inactive states, emphasizing the molecular details of interaction of the receptors with some representative peptide and nonpeptide ligands, underlying the multiple modes of binding of small opiates, and the differences in binding modes of agonists and antagonists, and of peptides and alkaloids.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Kieffer BL. Recent advances in molecular recognition and signal transduction of active peptides: receptors for opioid peptides.Cell Mol Neurobiol. 1995;15:615–635.

    Article  PubMed  CAS  Google Scholar 

  2. Waldhoer M, Bartlett SE, Whistler JL. Opioid receptors.Annu Rev Biochem. 2004;73:953–990.

    Article  PubMed  CAS  Google Scholar 

  3. Pasternak GW. Multiple opiate receptors: déjà vu all over again.Neuropharmacology. 2004;47:312–323.

    Article  PubMed  CAS  Google Scholar 

  4. Vaccarino AL, Kastin AJ. Endogenous opiates: 2000.Peptides. 2001;22:2257–2328.

    Article  PubMed  CAS  Google Scholar 

  5. Hruby VJ, Agnes RS. Conformation-activity relationships of opioid peptides with selective activities at opioid receptors.Biopolymers. 1999;51:391–410.

    Article  PubMed  CAS  Google Scholar 

  6. Mansour A, Hoversten MT, Taylor LP, Watson SJ, Akil H. The cloned mu, delta and kappa receptors and their endogenous ligands: evidence for two opioid peptide recognition cores.Brain Res. 1995;700:89–98.

    Article  PubMed  CAS  Google Scholar 

  7. Mosberg HI, Hurst R, Hruby VJ, et al. Conformationally constrained cyclic enkephalin analogs with pronounced delta opioid receptor agonist selectivity.Life Sci. 1983;32:2565–2569.

    Article  PubMed  CAS  Google Scholar 

  8. Pelton JT, Gulya K, Hruby VJ, Duckles S, Yamamura HI. Somatostatin analogs with affinity for opiate receptors in rat brain binding assay.Peptides. 1985;6:159–163.

    Article  PubMed  CAS  Google Scholar 

  9. Pelton JT, Kazmierski W, Gulya K, Yamamura HI, Hruby VJ. Design and synthesis of conformationally constrained somatostatin analogues with high potency and specificity for mu opioid receptors.J Med Chem. 1986;29:2370–2375.

    Article  PubMed  CAS  Google Scholar 

  10. Kawasaki AM, Knapp RJ, Walton A et al. Syntheses, opioid binding affinities, and potencies of dynorphin A analogues substituted in positions 1, 6, 7, 8 and 10.Int J Pept Protein Res. 1993;42:411–419.

    Article  PubMed  CAS  Google Scholar 

  11. Meyer JP, Collins N, Lung FD, et al. Design, synthesis, and biological properties of highly potent cyclic dynorphin A analogues: analogues cyclized between positions 5 and 11J Med Chem. 1994;37:3910–3917.

    Article  PubMed  CAS  Google Scholar 

  12. Arttamangkul S, Murray TF, DeLander GE, Aldrich JV. Synthesis and opioid activity of conformationally constrained dynorphin A analogues. 1. Conformational constraint in the “message” sequence.J Med Chem. 1995;38:2410–2417.

    Article  PubMed  CAS  Google Scholar 

  13. Lung FD, Collins N, Stropova D, et al. Design, synthesis, and biological activities of cyclic lactam peptide analogues of dynorphin A(1-11)-NH2.J Med Chem. 1996;39:1136–1141.

    Article  PubMed  CAS  Google Scholar 

  14. Eguchi M. Recent advances in selective opioid receptor agonists and antagonists.Med Res Rev. 2004;24:182–212.

    Article  PubMed  CAS  Google Scholar 

  15. Okada T, Ernst OP, Palczewski K, Hofmann KP. Activation of rhodopsin: new insights from structural and biochemical studies.Trends Biochem Sci. 2001;26:318–324.

    Article  PubMed  CAS  Google Scholar 

  16. Li J, Edwards PC, Burghammer M, Villa C, Schertler GF. Structure of bovine rhodopsin in a trigonal crystal form.J Mol Biol. 2004;343:1409–1438.

    Article  PubMed  CAS  Google Scholar 

  17. Flower DR. Modeling G-protein-coupled receptors for drug design.Biochim Biophys Acta 1999;1422:207–234.

    PubMed  CAS  Google Scholar 

  18. Flippen-Anderson JL, George C, Bertha CM, Rice KC. X-ray structure of potent opioid receptor ligands: etonitazene, cis-(+)-3-methylfentanyl, etorphine, diprenorphine, and buprenorphine.Heterocycles. 1994;39:751–766.

    CAS  Google Scholar 

  19. Urbanczyk-Lipkowska Z, Etter MC, Lipkowski AW, Portoghese PS. The crystal structure of a bimorphinan with highly selective kappa opioid receptor antagonist activity.J Mol Struct. 1987;159:287–295.

    Article  CAS  Google Scholar 

  20. Griffin JF, Larson DL, Portoghese PS. Crystal structures of alpha-and beta-funaltrexamine: conformational requirement of the fumaramate moiety in the irreversible blockage of mu opioid receptorsJ Med Chem. 1986;29:778–783.

    Article  PubMed  CAS  Google Scholar 

  21. Calderon SN, Rice KC, Rothman RB, et al. Probes for narcotic receptor mediated phenomena. 23. Synthesis, opioid receptor binding, and bioassay of the highly selective delta agonist (+)-4-[(alpha R)-alpha-((2S,5R)-4-Allyl-2,5-dimethyl-1-piperazinyl)-3-methoxybenzyl]-N,N-diethylbenzamide (SNC 80) and related novel nonpeptide delta opioid receptor ligands.J Med Chem. 1997;40:695–704.

    Article  PubMed  CAS  Google Scholar 

  22. Lavecchia A, Greco G, Novellino E, Vittorio F, Ronsisvalle G. Modeling of kappa-opioid receptor/agonists interactions using pharmacophore-based and docking simulations.J Med Chem. 2000;43:2124–2134.

    Article  PubMed  CAS  Google Scholar 

  23. Doi M, Ishida T, Inoue M. Conformational characteristics of opioid kappa-receptor agonist: crystal structure of (5S, 7S, 8S)-(-)-N-methyl-N-[7-(1-pyrrolidinyl)-1-oxaspiro[4.5] dec-8-yl]benzeneacetamide (U69,593), and conformational comparison with some kappa-agonists.Chem Pharm Bull (Tokyo). 1990;38:1815–1818.

    CAS  Google Scholar 

  24. Subramanian G, Patrelini MG, Portoghese PS, Ferguson DM. Molecular docking reveals a novel binding site model for fentanyl at the mu-opioid receptor.J Med Chem. 2000;43:381–391.

    Article  PubMed  CAS  Google Scholar 

  25. Mosberg HI, Fowler CB. Development and validation of opioid ligand-receptor interaction models: the structural basis of mu vs delta selectivity.J Pept Res. 2002;60:329–335.

    Article  PubMed  CAS  Google Scholar 

  26. Przydzial MJ, Pogozheva ID, Andrews SM, et al. Roles of residues 3 and 4 in cyclic tetrapeptide ligand recognition by the κ-opioid receptor.J Pept Res. 2005;65:333–342.

    Article  PubMed  CAS  Google Scholar 

  27. Mosberg HI, Omnaas JR, Medzihradsky F, Smith CB. Cyclic, disulfide- and dithioether-containing opioid tetrapeptides: development of a ligand with high delta opioid receptor selectivity and affinity.Life Sci. 1988;43:1013–1020.

    Article  PubMed  CAS  Google Scholar 

  28. Mosberg HI, Lomize AL, Wang C, et al. Development of a model for the δ-opioid receptor pharmacophore. 1. Conformationally restricted Tyr1 replacements in the cyclic δ receptor selective tetrapeptide Tyr-c[D-Cys-Phe-D-Pen]OH (JOM-13).J Med Chem 1994a;37:4371–4383.

    Article  PubMed  CAS  Google Scholar 

  29. Mosberg HI, Omnaas JR, Lomize A, et al. Development of a model for the δ-opioid receptor pharmacophore. 2. Conformationally restricted Phe3 replacements in the cyclic δ-receptor selective tetrapeptide Tyr-c[D-Cys-Phe-D-Pen]OH (JOM-13).J Med Chem. 1994b;37:4384–4391.

    Article  PubMed  CAS  Google Scholar 

  30. Mosberg HI, Dua RK, Pogozheva ID, Lomize AL. Development of a model for the δ-opioid receptor pharmacophore. 4. Residue 3 dehydrophenyl-alanine analogs of Tyr-c[D-Cys-Phe-D-Pen]OH (JOM-13) confirm required gauche orientation of aromatic sidechain.Biopolymers. 1996;39:287–296.

    Article  PubMed  CAS  Google Scholar 

  31. Lomize AL, Flippen-Anderson JL, George C, Mosberg HI. Conformational analysis of the δ receptor-selective, cyclic opioid peptide, Tyr-c[D-Cys-Phe-D-Pen]OH(JOM-13): comparison of X-ray crystallographic structures, molecular mechanics simulations and1H NMR data.J Am Chem Soc. 1994;116:429–436.

    Article  CAS  Google Scholar 

  32. Ho JC.Development of a Model for the δ-opioid Receptor Pharmacophore [dissertation]. Ann Arbor, MI: University of Michigan; 1997.

    Google Scholar 

  33. McFadyen IJ, Ho JC, Mosberg HI, Traynor JR. Modifications of the cyclic mu receptor selective tetrapeptide Tyr-c[D-Cys-Phe-D-Pen]NH2 (Et): effects on opioid receptor binding and activation.J Pept Res. 2000;55:255–261.

    Article  PubMed  CAS  Google Scholar 

  34. Fowler CB III, Pogozheva ID III, Lomize AL III, LeVine H III, Mosberg HI. Complex of an active μ-opioid receptor with cyclic peptide agonist modeled from experimental constraints.Biochemistry. 2004a;43:15796–15810.

    Article  PubMed  CAS  Google Scholar 

  35. Mosberg HI. Complementarity of delta opioid ligand pharmacophore and receptor models.Biopolymers. 1999;51:426–439.

    Article  PubMed  CAS  Google Scholar 

  36. Law PY, Loh HH. Regulation of opioid receptor activities.J Pharmacol Exp Ther. 1999;289:607–624.

    PubMed  CAS  Google Scholar 

  37. Chaturvedi K, Christoffers KH, Singh K, Howells RD. Structure and regulation of opioid receptors.Biopolymers. 2000;55:334–346.

    Article  PubMed  CAS  Google Scholar 

  38. Chavkin C, McLaughlin JP, Celver JP. Regulation of opioid receptor function by chronic agonist exposure: constitutive activity and desensitization.Mol Pharmacol. 2001;60:20–25.

    PubMed  CAS  Google Scholar 

  39. Coward P, Wada HG, Falk MS, et al. Controlling signaling with a specifically designed Gi-coupled receptor.Proc Natl Acad Sci USA. 1998;95:352–357.

    Article  PubMed  CAS  Google Scholar 

  40. Pogozheva ID, Lomize AL, Mosberg HI. Opioid receptor 3-dimensional structures from distance geometry calculations with hydrogen bonding constraints.Biophys J 1998;75:612–634.

    PubMed  CAS  Google Scholar 

  41. Surratt CK, Johnson PS, Moriwaki A, et al. Mu opiate receptor: charged transmembrane domain amino acids are critical for agonist recognition and intrinsic activity.J Biol Chem. 1994;269:20548–20553.

    PubMed  CAS  Google Scholar 

  42. Befort K, Tabbara L, Bausch S, Chavkin C, Evans C, Kieffer BL. The conserved aspartate residue in the third putative transmembrane domain of the delta-opioid receptor is not the anionic counterpart for cationic opiate binding but is a constituent of the receptor binding site.Mol Pharmacol. 1996a;49:216–223.

    PubMed  CAS  Google Scholar 

  43. Befort K, Tabbara L, Kling D, Maigret B, Kieffer BL. Role of aromatic transmembrane residues of the delta-opioid receptor in ligand recognition.J Biol Chem. 1996b;271:10161–10168.

    Article  PubMed  CAS  Google Scholar 

  44. Befort K, Zilliox C, Filliol D, Yue S, Kieffer BL. Constitutive activation of the delta opioid receptor by mutations in transmembrane domains III and VII.J Biol Chem 1999;274:18574–18581.

    Article  PubMed  CAS  Google Scholar 

  45. Bot G, Blake AD, Li S, Reisine T. Mutagenesis of the mouse delta opioid receptor converts(-)-buprenorphine from a partial agonist to an antagonist.J Pharmacol Exp Ther. 1998a;284:283–290.

    PubMed  CAS  Google Scholar 

  46. Bot G, Blake AD, Li S, Reisine T. Mutagenesis of a single amino acid in the rat mu-opioid receptor discriminates ligand binding.J Neurochem. 1998b;70:358–365.

    PubMed  CAS  Google Scholar 

  47. Spivak CE, Beglan CL, Seidleck BK, et al. Naloxone activation of mu-opioid receptors mutated at a histidine residue lining the opioid binding cavity.Mol Pharmacol. 1997;52:983–992.

    PubMed  CAS  Google Scholar 

  48. Mansour A, Taylor LP, Fine JL, et al. Key residues defining the mu-opioid receptor binding pocket: a site-directed mutagenesis study.J Neurochem 1997;68:344–353.

    Article  PubMed  CAS  Google Scholar 

  49. Meng F, Ueda Y, Hoversten MT, et al. Creating a functional opioid alkaloid binding site in the orphanin FQ receptor through site-directed mutagenesis.Mol Pharmacol. 1998;53:772–777.

    PubMed  CAS  Google Scholar 

  50. Li JG, Chen C, Yin J, et al. ASP147 in the third transmembrane helix of the rat mu opioid receptor forms ion-pairing with morphine and naltrexone.Life Sci. 1999;65:175–185.

    Article  PubMed  CAS  Google Scholar 

  51. Fukuda K, Terasako K, Kato S, Mori K. Identification of the amino acid residues involved in selective agonist binding in the first extracellular loop of the delta-and mu-opioid receptors.FEBS Lett. 1995;373:177–181.

    Article  PubMed  CAS  Google Scholar 

  52. Minami M, Onogi T, Nakagawa T, et al. DAMGO, a mu-opioid receptor selective ligand, distinguishes between mu-and kappa-opioid receptors at a different region from that for the distinction between mu-and delta-opioid receptors.FEBS Lett. 1995;364:23–27.

    Article  PubMed  CAS  Google Scholar 

  53. Wang JB, Johnson PS, Wu JM, Wang WF, Uhl GR. Human kappa opiate receptor second extracellular loop elevates dynorphin's affinity for human mu/kappa chimeras.J Biol Chem. 1994;269:2966–25969.

    Google Scholar 

  54. Xue JC, Chen C, Zhu J, et al. Differential binding domains of peptide and non-peptide ligands in the cloned rat kappa opioid receptor.J Biol Chem. 1994;269:30195–30199.

    PubMed  CAS  Google Scholar 

  55. Ferguson DM, Kramer S, Metzger TG, Law PY, Portoghese PS. Isosteric replacement of acidic with neutral residues in extracellular loop-2 of the kappa-opioid receptor does not affect dynorphin A(1–13) affinity and function.J Med Chem. 2000;43:1251–1252.

    Article  PubMed  CAS  Google Scholar 

  56. Bonner G, Meng F, Akil H. Selectivity of mu-opioid receptor determined by interfacial residues near third extracellular loop.Eur J Pharmacol. 2000;403:37–44.

    Article  PubMed  CAS  Google Scholar 

  57. Xu H, Lu YF, Partilla JS, et al. Opioid peptide receptor studies. 11. Involvement of Tyr148, Trp318 and His319 of the rat mu-opioid receptor in binding of mu-selective ligands.Synapse. 1999;32:23–28.

    Article  PubMed  CAS  Google Scholar 

  58. Ulens C, Van Boven M, Daenens P, Tytgat J. Interaction of p-fluoro fentanyl on cloned human opioid receptors and exploration of the role of Trp-318 and His-319 in mu-opioid receptor selectivity.J Pharmacol Exp Ther. 2000;294:1024–1033.

    PubMed  CAS  Google Scholar 

  59. Pepin MC, Yue SY, Roberts E, Wahlestedt C, Walker P. Novel “restoration of function” mutagenesis strategy to identify amino acids of the delta-opioid receptor involved in ligand binding.J Biol Chem. 1997;272:9260–9267.

    Article  PubMed  CAS  Google Scholar 

  60. Valiquette M, Vu HK, Yue SY, Wahlestedt C, Walker P. Involvement of Trp-284, Val-296, and Val-297 of the human delta-opioid receptor in binding of delta-selective ligands.J Biol Chem. 1996;271:18789–18796.

    Article  PubMed  CAS  Google Scholar 

  61. Hjorth SA, Thirstrup K, Grandy DK, Schwartz TW. Analysis of selective binding epitopes for the kappa-opioid receptor antagonist norbinaltorphime.Mol Pharmacol. 1995;47:1089–1094.

    PubMed  CAS  Google Scholar 

  62. Cavalli A, Babey AM, Loh HH. Altered adenylyl cyclase responsiveness subsequent to point mutations of Asp 128 in the third transmembrane domain of the delta-opioid receptor.Neuroscience. 1999;93:1025–1031.

    Article  PubMed  CAS  Google Scholar 

  63. Li J, Huang P, Chen C, de Riel JK, Weinstein H, Liu-Chen LY. Constitutive activation of the mu opioid receptor by mutation of D3.49(164), but not D3.32(147): D3.49(164) is critical for stabilization of the inactive form of the receptor and for its expression.Biochemistry. 2001;40:12039–12050.

    Article  PubMed  CAS  Google Scholar 

  64. Mouledous L, Topham CM, Moisand C, Mollereau C, Meunier JC. Functional inactivation of the nociceptin receptor by alanine substitution of glutamine 286 at the C terminus of transmembrane segment VI: evidence from a site-directed mutagenesis study of the ORLI receptor transmembrane-binding domain.Mol Pharmacol. 2000;57:495–502.

    PubMed  CAS  Google Scholar 

  65. DeCaillot FM, Befort K, Filliol D, Yue S, Walker P, Kieffer BL. Opioid receptor random mutagenesis reveals a mechanism for G protein-coupled receptor activation.Nat Struct Biol. 2003;10:629–636.

    Article  PubMed  CAS  Google Scholar 

  66. Spivak CE, Beglan CL, Zollner C, Surratt CK. Beta-Funaltrexamine, a gauge for the recognition site of wildtype and mutant H297Q mu-opioid receptors.Synapse. 2003;49:55–60.

    Article  PubMed  CAS  Google Scholar 

  67. Chen C, Yin J, Riel JK, et al. Determination of the amino acid residue involved in [3H]beta-funaltrexamine covalent binding in the cloned rat mu-opioid receptor.J Biol Chem. 1996;271:21422–21429.

    Article  PubMed  CAS  Google Scholar 

  68. Jones RM, Hjorth SA, Schwartz TW, Portoghese PS. Mutational evidence for a common kappa antagonist binding pocket in the wild-type kappa and mutant mu[K303E] opioid receptors.J Med Chem. 1998;41:4911–4914.

    Article  PubMed  CAS  Google Scholar 

  69. Larson DL, Jones RM, Hjorth SA, Schwartz TW, Portoghese PS. Binding of norbinaltorphimine (norBNI) congeners to wild-type and mutant mu and kappa opioid receptors: molecular recognition loci for the pharmacophore and address components of kappa antagonists.J Med Chem. 2000;43:1573–1576.

    Article  PubMed  CAS  Google Scholar 

  70. Fowler CB III, Pogozheva ID III, LeVine H III, Mosberg HI. Refinement of a homology model of the μ-opiodd receptor using distance constraints from intrinsic and engineered zinc-binding sites.Biochemistry. 2004b;43:8700–8710.

    Article  PubMed  CAS  Google Scholar 

  71. Metzger TG, Paterlini MG, Portoghese PS, Ferguson DM. An analysis of the conserved residues between halobacterial retinal proteins and G-protein coupled receptors: implications for GPCR modeling.J Chem Inf Comput Sci. 1996;36:857–861.

    Article  PubMed  CAS  Google Scholar 

  72. Strahs D, Weinstein H. Comparative modeling and molecular dynamics studies of the delta, kappa and mu opioid receptors.Protein Eng. 1997;10:1019–1038.

    Article  PubMed  CAS  Google Scholar 

  73. Alkorta I, Loew GH. A 3D model of the delta opioid receptor and ligand-receptor complexes.Protein Eng. 1996;9:573–583.

    Article  PubMed  CAS  Google Scholar 

  74. Subramanian G, Paterlini MG, Larson DL, Portoghese PS, Ferguson DM. Conformational analysis and automated receptor docking of selective arylacetamide-based kappa-opioid agonists.J Med Chem. 1998;41:4777–4789.

    Article  PubMed  CAS  Google Scholar 

  75. Paterlini G, Portoghese PS, Ferguson DM. Molecular simulation of dynorphin A-(1–10) binding to extracellular loop 2 of the kappa-opioid receptor: a model for receptor activation.J Med Chem. 1997;40:3254–3262.

    Article  PubMed  CAS  Google Scholar 

  76. Filizola M, Caakkonen L, Loew GH. 3D modeling, ligand binding and activations studies of the cloned mouse delta, mu, and kappa opioid receptors.Protein Eng. 1999a, 12:927–942.

    Article  PubMed  CAS  Google Scholar 

  77. Filizola M, Carteni-Farina M, Perez JJ. Molecular modeling study of the differential ligand-receptor interaction at the mu, delta and kappa opioid receptors.J Comput Aided Mol Des. 1999b;13:397–407.

    Article  PubMed  CAS  Google Scholar 

  78. Pogozheva ID, Lomize AL, Mosberg HI. The transmembrane 7 alpha-bundle of rhodopsin: distance geometry calculations with hydrogen bonding constraints.Biophys J. 1997;72:1963–1985.

    PubMed  CAS  Google Scholar 

  79. Lomize AL, Pogozheva ID, Mosberg HI. Structural organization of G-protein-coupled receptors.J Comput Aided Mol Des. 1999;13:325–353.

    Article  PubMed  CAS  Google Scholar 

  80. Vaidehi N, Floriano WB, Trabanino R, et al. Prediction of structure and function of G protein-coupled receptors.Proc Natl Acad Sci USA. 2002;99:12622–12627.

    Article  PubMed  CAS  Google Scholar 

  81. Shacham S, Topf M, Avisar N, et al. Modeling the 3D structure of GPCRs from sequence.Med Res Rev. 2001;21:472–483.

    Article  PubMed  CAS  Google Scholar 

  82. Shi L, Javitch JA. The binding site of aminergic G protein-coupled receptors: the transmembrane segments and second extracellular loop.Annu Rev Pharmacol Toxicol. 2002;42:437–467.

    Article  PubMed  CAS  Google Scholar 

  83. Lawson Z, Wheatley M. The third extracellular loop of G-protein-coupled receptors: more than just a linker between 2 important transmembrane helices.Biochem Soc Trans. 2004;32:1048–1050.

    Article  PubMed  CAS  Google Scholar 

  84. Baker D, Sali A. Protein structure prediction and structural genomics.Science. 2001;294:93–96.

    Article  PubMed  CAS  Google Scholar 

  85. Palczewski K, Kumasaka T, Hori T, et al. Crystal structure of rhodopsin: a G protein-coupled receptor.Science. 2000;289:739–745.

    Article  PubMed  CAS  Google Scholar 

  86. Ballesteros JA, Shi L, Javitch JA. Structural mimicry in G protein-coupled receptors: implications of the high-resolution structure of rhodopsin for structure-function analysis of rhodopsin-like receptors.Mol Pharmacol. 2001;60:1–19.

    PubMed  CAS  Google Scholar 

  87. Klabunde T, Hessler G. Drug design strategies for targeting G-protein-coupled receptors.ChemBioChem. 2002;3:928–944.

    Article  PubMed  CAS  Google Scholar 

  88. Bissantz C, Bernard P, Hibert M, Rognan D. Protein-based virtual screening of chemical databases. II. Are homology models of G-protein coupled receptors suitable targets?.Proteins. 2003;50:5–25.

    Article  PubMed  CAS  Google Scholar 

  89. Evers A, Klebe G. Ligand-supported homology modeling of g-protein-coupled receptor sites: models sufficient for successful virtual screening.Angew Chem Int Ed Engl. 2004a;43:248–251.

    Article  PubMed  CAS  Google Scholar 

  90. Horn F, Bettler E, Oliveira L, Campagne F, Cohen FE, Vriend G. GPCRDB information system for G protein-coupled receptors.Nucleic Acids Res. 2003;31:294–297.

    Article  PubMed  CAS  Google Scholar 

  91. Huang P, Li J, Chen C, Visiers I, Weinstein H, Liu-Chen LY. Functional role of a conserved motif in TM6 of the rat mu opioid receptor: constitutively active and inactive receptors result from substitutions of Thr6.34(279) with Lys and Asp.Biochemistry. 2001;40:13501–13509.

    Article  PubMed  CAS  Google Scholar 

  92. Sali A, Blundell TL. Comparative protein modeling by satisfaction of spatial restraints.J Mol Biol. 1993;234:779–815.

    Article  PubMed  CAS  Google Scholar 

  93. Fiser A, Sali A. Modeller: generation and refinement of homology-based protein structure models.Methods Enzymol. 2003;374:461–491.

    PubMed  CAS  Google Scholar 

  94. Peitsch MC. ProMod and Swiss-Model: internet-based tools for automated comparative protein modelling.Biochem Soc Trans. 1996;24:274–279.

    PubMed  CAS  Google Scholar 

  95. Lund O, Frimand K, Gorodkin J, et al. Protein distance constraints predicted by neural networks and probability density functions.Protein Eng. 1997;10:1241–1248.

    Article  PubMed  CAS  Google Scholar 

  96. Shindyalov IN, Bourne PE. Improving alignments in HM protocol with intermediate sequences. In: Forth Meeting on the Critical Assessment of Techniques for Protein Structure Prediction; 2000:A-92.

  97. Lambert C, Leonard N, De Bolle X, Depiereux E. ESyPred3D: prediction of proteins 3D structures.Bioinformatics. 2002;18:1250–1256.

    Article  PubMed  CAS  Google Scholar 

  98. Kim DE, Chivian D, Baker D. Protein structure prediction and analysis using the Robetta server.Nucleic Acids Res. 2004;32:W526-W531.

    Article  PubMed  CAS  Google Scholar 

  99. Pieper U, Eswar N, Braberg H, et al. MODBASE, a database of annotated comparative protein structure models, and associated resources.Nucleic Acids Res. 2004;32:D217-D222.

    Article  PubMed  CAS  Google Scholar 

  100. Eswar N, John B, Mirkovic N, et al. Tools for comparative protein structure modeling and analysis.Nucleic Acids Res. 2003; 31:3375–3380.

    Article  PubMed  CAS  Google Scholar 

  101. John B, Sali A. Comparative protein structure modeling by iterative alignment, model building and model assessment.Nucleic Acids Res. 2003;31:3982–3992.

    Article  PubMed  CAS  Google Scholar 

  102. Riek RP, Rigoutsos I, Novotny J, Graham RM. Non-alpha-helical elements modulate polytopic membrane protein architecture.J Mol Biol. 2001;306:349–362.

    Article  PubMed  CAS  Google Scholar 

  103. Fiser A, Do RK, Sali A. Modeling of loops in protein structures.Protein Sci. 2000;9:1753–1773.

    PubMed  CAS  Google Scholar 

  104. Chothia C, Lesk AM. Helix movements and the reconstruction of the haem pocket during the evolution of the cytochrome c family.J Mol Biol. 1985;182:151–158.

    Article  PubMed  CAS  Google Scholar 

  105. Meng EC, Bourne HR. Receptor activation: what does the rhodopsin structure tell us?Trends Pharmacol Sci. 2001;22:587–593.

    Article  PubMed  CAS  Google Scholar 

  106. Karnik SS, Gogonea C, Patil S, Saad Y, Takezako T. Activation of G-protein-coupled receptors: a common molecular mechanism.Trends Endocrinol Metab. 2003;14:431–437.

    Article  PubMed  CAS  Google Scholar 

  107. Ghanouni P, Steenhuis JJ, Farrens DL, Kobilka BK. Agonist-induced conformational changes in the G-protein-coupling domain of the beta 2 adrenergic receptor.Proc Natl Acad Sci USA. 2001a;98:5997–6002.

    Article  PubMed  CAS  Google Scholar 

  108. Farrens DL, Altenbach C, Yang K, Hubbell WL, Khorana HG. Requirement of rigid-body motion of transmembrane helices for light activation of rhodopsin.Science. 1996;274:768–770.

    Article  PubMed  CAS  Google Scholar 

  109. Gether U, Lin S, Ghanouni P, Ballesteros JA, Weinstein H, Kobilka BK. Agonists induce conformational changes in transmembrane domains III and VI of the beta2 adrenoceptor.EMBO J. 1997;16:6737–6747.

    Article  PubMed  CAS  Google Scholar 

  110. Dunham TD, Farrens DL. Conformational changes in rhodopsin: movement of helix F detected by site-specific chemical labeling and fluorescence spectroscopy.J Biol Chem. 1999;274:1683–1690.

    Article  PubMed  CAS  Google Scholar 

  111. Han M, Smith SO, Sakmar TP. Constitutive activation of opsin by mutation of methionine 257 on transmembrane helix 6.Biochemistry. 1998;37:8253–8261.

    Article  PubMed  CAS  Google Scholar 

  112. Cai K, Klein-Seetharaman J, Hwa J, Hubbell WL, Khorana HG. Structure and function in rhodopsin: effects of disulfide cross-links in the cytoplasmic face of rhodopsin on transducin activation and phosphorylation by rhodopsin kinase.Biochemistry. 1999;38:12893–12898.

    Article  PubMed  CAS  Google Scholar 

  113. Ghanouni P, Gryczynski Z, Steenhuis JJ, et al. Functionally different agonists induce distinct conformations in the G protein coupling domain of the beta 2 adrenergic receptor.J Biol Chem. 2001b;276:24433–24436.

    Article  PubMed  CAS  Google Scholar 

  114. Janz JM, Farrens DL. Rhodopsin activation exposes a key hydrophobic binding site for the transducin alpha-subunit C terminus.J Biol Chem. 2004;279:29767–29773.

    Article  PubMed  CAS  Google Scholar 

  115. Hubbell WL, Altenbach C, Hubbell CM, Khorana HG. Rhodopsin structure, dynamics, and activation: a perspective from crystallography, site-directed spin labeling, sulfhydryl reactivity, and disulfide crosslinking.Adv Protein Chem. 2003;63:243–290.

    Article  PubMed  CAS  Google Scholar 

  116. Lin SW, Sakmar TP. Specific tryptophan UV-absorbance changes are probes of the transition of rhodopsin to its active state.Biochemistry. 1996;35:11149–11159.

    Article  PubMed  CAS  Google Scholar 

  117. Altenbach C, Cai K, Khorana HG, Hubbell WL. Structural features and light-dependent changes in the sequence 306–322 extending from helix VII to the palmitoylation sites in rhodopsin: a sitedrected spin-labeling study.Biochemistry. 1999a;38:7931–7937.

    Article  PubMed  CAS  Google Scholar 

  118. Altenbach C, Klein-Seetharaman J, Hwa J, Khorana HG, Hubbell WL. Structural features and light-dependent changes in the sequence 59–75 connecting helices I and II in rhodopsin: a site-directed spinlabeling study.Biochemistry. 1999b;38:7945–7949.

    Article  PubMed  CAS  Google Scholar 

  119. Altenbach C, Cai K, Klein-Seetharaman J, Khorana HG, Hubbell WL. Structure and function in rhodopsin: mapping light-dependent changes in distance between residue 65 in helix TM1 and residues in the sequence 306–319 at the cytoplasmic end of helix TM7 and in helix H8.Biochemistry. 2001a;40:15483–15492.

    Article  PubMed  CAS  Google Scholar 

  120. Altenbach C, Klein-Seetharaman J, Cai K, Khorana HG, Hubbell WL. Structure and function in rhodopsin: mapping light-dependent changes in distance between residue 316 in helix 8 and residues in the sequence 60–75, covering the cytoplasmic end of helices TM1 and TM2 and their connection loop CL1.Biochemistry. 2001b;40:15493–15500.

    Article  PubMed  CAS  Google Scholar 

  121. Gether U, Kobilka BK. G protein-coupled receptors. II. Mechanism of agonist activation.J Biol Chem. 1998;273:17979–17982.

    Article  PubMed  CAS  Google Scholar 

  122. Devanathan S, Yao Z, Salamon Z, Kobilka B, Tollin G. Plasmon-waveguide resonance studies of ligand binding to the human beta 2-adrenergic receptor.Biochemistry. 2004;43:3280–3288.

    Article  PubMed  CAS  Google Scholar 

  123. Salamon Z, Cowell S, Varga E, Yamamura HI, Hruby VJ, Tollin G. Plasmon resonance studies of agonist/antagonist binding to the human delta-opioid receptor: new structural insights into receptor-ligand interactions.Biophys J. 2000;79:2463–2474.

    PubMed  CAS  Google Scholar 

  124. Salamon Z, Hruby VJ, Tollin G, Cowell S. Binding of agonists, antagonists and inverse agonists to the human delta-opioid receptor produces distinctly different conformational states distinguishable by plasmon-waveguide resonance spectroscopy.J Pept Res. 2002;60:322–328.

    Article  PubMed  CAS  Google Scholar 

  125. Alves ID, Ciano KA, Boguslavski V, et al. Selectivity, cooperativity, and reciprocity in the interactions between the delta-opioid receptor, its ligands, and G-proteins.J Biol Chem. 2004a;279:44673–44682.

    Article  PubMed  CAS  Google Scholar 

  126. Alves ID, Cowell SM, Salamon Z, Devanathan S, Tollin G, Hruby VJ. Different structural states of the proteolipid membrane are produced by ligand binding to the human delta-opioid receptor as shown by plasmon-waveguide resonance spectroscopy.Mol Pharmacol. 2004b;65:1248–1257.

    Article  PubMed  CAS  Google Scholar 

  127. Tramontano A, Morea V. Exploiting evolutionary relationships for predicting protein structures.Biotechnol Bioeng. 2003;84:756–763.

    Article  PubMed  CAS  Google Scholar 

  128. Bates PA, Kelley LA, MacCallum RM, Sternberg MJ. Enhancement of protein modeling by human intervention in applying the automatic programs 3D-JIGSAW and 3D-PSSM.Proteins. 2001;39–46.

  129. Li X, Jacobson MP, Friesner RA. High-resolution prediction of protein helix positions and orientations.Proteins. 2004;55:368–382.

    Article  PubMed  CAS  Google Scholar 

  130. Evers A, Gohlke H, Klebe G. Ligand-supported homology modelling of protein binding-sites using knowledge-based potentials.J Mol Biol. 2003;334:327–345.

    Article  PubMed  CAS  Google Scholar 

  131. Ward SD, Hamdan FF, Bloodworth LM, Wess J. Conformational changes that occur during M3 muscarinic acetylcholine receptor activation probed by the use of an in situ disulfide cross-linking strategy.J Biol Chem. 2002;277:2247–2257.

    Article  PubMed  CAS  Google Scholar 

  132. Swaminath G, Lee TW, Kobilka B. Identification of an allosteric binding site for Zn2+ on the beta2 adrenergic receptor.J Biol Chem. 2003;278:352–356.

    Article  PubMed  CAS  Google Scholar 

  133. Elling CE, Thirstrup K, Holst B, Schwartz TW. Conversion of agonist site to metal-ion chelator site in the beta(2)-adrenergic receptor.Proc Natl Acad Sci USA. 1999;96:12322–12327.

    Article  PubMed  CAS  Google Scholar 

  134. Holst B, Elling CE, Schwartz TW. Partial agonism through a zincion switch constructed between transmembrane domains III and VII in the tachykinin NK(1) receptor.Mol Pharmacol. 2000;58:263–270.

    PubMed  CAS  Google Scholar 

  135. Lagerstrom MC, Klovins J, Fredriksson R, et al. High affinity agonistic metal ion binding sites within the melanocortin 4 receptor illustrate conformational change of transmembrane region 3.J Biol Chem. 2003;278:51521–51526.

    Article  PubMed  CAS  Google Scholar 

  136. Ewing TJ, Makino S, Skillman AG, Kuntz ID. DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases.J Comput Aided Mol Des. 2001;15:411–428.

    Article  PubMed  CAS  Google Scholar 

  137. Jones G, Willett P, Glen RC, Leach AR, Taylor R. Development and validation of a genetic algorithm for flexible docking.J Mol Biol. 1997;267:727–748.

    Article  PubMed  CAS  Google Scholar 

  138. Rarey M, Wefing S, Lengauer T. Placement of medium-sized molecular fragments into active sites of proteins.J Comput Aided Mol Des. 1996;10:41–54.

    Article  PubMed  CAS  Google Scholar 

  139. Taylor RD, Jewsbury PJ, Essex JW. FDS: flexible ligand and receptor docking with a continuum solvent model and soft-core energy function.J Comput Chem. 2003;24:1637–1656.

    Article  PubMed  CAS  Google Scholar 

  140. Halgren TA, Murphy RB, Friesner RA, et al. Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening.J Med Chem. 2004;47:1750–1759.

    Article  PubMed  CAS  Google Scholar 

  141. Venkatachalam CM, Jiang X, Oldfield T, Waldman M. LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites.J Mol Graph Model. 2003;21:289–307.

    Article  PubMed  CAS  Google Scholar 

  142. Cavasotto CN, Abagan RA. Protein flexibility in ligand docking and virtual screening to protein kinases.J Mol Biol. 2004;337:209–225.

    Article  PubMed  CAS  Google Scholar 

  143. Perola E, Walters WP, Charifson PS. A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance.Proteins. 2004;56:235–249.

    Article  PubMed  CAS  Google Scholar 

  144. Halperin I, Ma B, Wolfson H, Nussinov R. Principles of docking: an overview of search algorithms and a guide to scoring functions.Proteins. 2004;47:409–443.

    Article  CAS  Google Scholar 

  145. Kontoyianni M, McClellan LM, Sokol GS. Evaluation of docking performance: comparative data on docking algorithms.J Med Chem. 2004;47:558–565.

    Article  PubMed  CAS  Google Scholar 

  146. Carlson HA, McCammon JA. Accommodating protein flexibility in computational drug design.Mol Pharmacol. 2000;57:213–218.

    PubMed  CAS  Google Scholar 

  147. Evers A, Klebe G. Successful virtual screening for a submicromolar antagonist of the neurokinin-1 receptor based on a ligand-supported homology model.J Med Chem. 2004b;47:5381–5392.

    Article  PubMed  CAS  Google Scholar 

  148. Heyl DL, Mosberg HI. Modification of the Phe3 aromatic moiety in delta receptor-selective dermorphin/deltorphin-related tetrapeptides: effects on opioid receptor binding.Int J Pept Protein Res. 1992;39:450–457.

    Article  PubMed  CAS  Google Scholar 

  149. Sebastian A, Bidlack JM, Jiang Q, et al. 14 beta-[(p-nitrocinnamoy 1)amino]morphinones, 14 beta-[(p-nitrocinnamoyl)amino]-7,8-dihydromorphinones, and their codeinone analogues: synthesis and receptor activity.J Med Chem. 1993;36:3154–3160.

    Article  PubMed  CAS  Google Scholar 

  150. Sagara T, Egashira H, Okamura M, Fujii I, Shimohigashi Y, Kanematsu K. Ligand recognition in mu opioid receptor: experimentally based modeling of mu opioid receptor binding sites and their testing by ligand docking.Bioorg Med Chem. 1996;4:2151–2166.

    Article  PubMed  CAS  Google Scholar 

  151. Chabre M, Breton J. Orientation of aromatic residues in rhodopsin: rotation of one tryptophan upon the meta I to meta II transition after illumination.Photochem Photobiol. 1979;30:295–299.

    Article  PubMed  CAS  Google Scholar 

  152. Baneres JL, Martin A, Hullot P, Girard JP, Rossi JC, Parello J Structure-based analysis of GPCR function: conformational adaptation of both agonist and receptor upon leukotriene B4 binding to recombinant BLT1.J Mol Biol. 2003;329:801–814.

    Article  PubMed  CAS  Google Scholar 

  153. Ruprecht JJ, Mielke T, Vogel R, Villa C, Schertler GF. Electron crystallography reveals the structure of metarhodopsin I.EMBO J. 2004;23:3609–3620.

    Article  PubMed  CAS  Google Scholar 

  154. Sammes PG, Taylor JB. Opioid receptors. In: Hansch C, ed.Comprehensive Medicinal Chemistry. Oxford, UK: Pergamon Press; 1990;805–844.

    Google Scholar 

  155. Schiller PW, Weltrowska G, Nguyen TM-D, Lemieux C, Chung NN, Lu Y. Conversion of μ-, δ- and κ-receptor selective opioid peptide agonists into μ-, δ-, and κ-receptor selective antagonists.Life Sci. 2003;73:691–698.

    Article  PubMed  CAS  Google Scholar 

  156. Huang P, Kim S, Loew G. Development of a common 3D pharmacophore for delta-opioid recognition from peptides and non-peptides using a novel computer program.J Comput Aided Mol Des. 1997;11:21–28.

    Article  PubMed  CAS  Google Scholar 

  157. Filizola M, Villar HO, Loew GH. Molecular determinants of non-specific recognition of delta, mu, and kappa opioid receptors.Bioorg Med Chem. 2001a;9:69–76.

    Article  PubMed  CAS  Google Scholar 

  158. Filizola M, Villar HO, Loew GH. Differentiation of delta, mu, and kappa opioid receptor agonists based on pharmacophore development and computed physicochemical properties.J Comput Aided Mol Des. 2001b;15:297–307.

    Article  PubMed  CAS  Google Scholar 

  159. Bernard D Jr, Coop A Jr, MacKerell AD Jr. 2D conformationally sampled pharmacophore: a ligand-based pharmacophore to differentiate delta opioid agonists from antagonists.J Am Chem Soc. 2003;125:3101–3107.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, 428 Church St, 48109-1065, Ann Arbor, MI

    Irina D. Pogozheva, Magdalena J. Przydzial & Henry I. Mosberg

Authors
  1. Irina D. Pogozheva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Magdalena J. Przydzial
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Henry I. Mosberg
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

Published: October 5, 2005

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pogozheva, I.D., Przydzial, M.J. & Mosberg, H.I. Homology modeling of opioid receptor-ligand complexes using experimental constraints. AAPS J 7, 43 (2005). https://doi.org/10.1208/aapsj070243

Download citation

  • Received:

  • Accepted:

  • DOI: https://doi.org/10.1208/aapsj070243

Keywords

Search

Navigation