Учет гидрофобных взаимодействий при оценке пространственной структуры мембранных белков и разработке действующих на них лигандов: на примере антагонистов β2AR-рецептора тема диссертации и автореферата по ВАК РФ 03.01.02, кандидат физико-математических наук Новоселецкий, Валерий Николаевич

• Новоселецкий, Валерий Николаевич
• кандидат физико-математических наук
• 2010

Оглавление диссертации кандидат физико-математических наук Новоселецкий, Валерий Николаевич

Список сокращений.

Глава 1 Введение.

Глава 2 Методы моделирования структуры GPCR, оценки качества упаковки белковых структур и предсказания биологической активности низкомолекулярных соединений (обзор литературы).

2.1. Актуальность моделирования пространственной структуры мембранных белков

2.2. Распространенные методы моделирования рецепторов семейства GPCR.

2.2. L. Общая информация о рецепторах GPCR.

2.2.2. Методы моделирования ab initio.

2.2.3. Методы моделирования на основании гомологии.

2.3. Существующие методы оценки качества упаковки белков.

2.4. Молекулярная динамика мембранных белков.

2.4.1. Полноатомное представление белковых структур.

2.4.2. Крупнозернистое представление белковых структур.

2.5. Расчет гидрофобных взаимодействий.

2.6. Изучение соотношений «структура - активность» для лигандов бета2-адренэргического рецептора.

2.6.1. Экспериментальное изучение влияния структуры на активность соединений

2.6.2. Компьютерный поиск активных соединений.

Глава 3 Результаты и обсуждение.

3.1. Разработка и тестирование оценочных функций для мембранных белков.

3.1.1. Анализ экспериментально установленных структур мембранных белков.

3.1.2. Крупнозернистая и полноатомная оценочные функции.

3.1.3. Идентификация кристаллографической структуры родопсина среди набора неточных моделей.

3.1.4. Формулирование критерия корректности структур МБ на основе оценочных функций.

3.1.5. Возможность оптимизации моделей с правильной укладкой основной цепи.

3.1.6. Выявление ошибок в выравнивании с помощью разработанных оценочных функций.

3.1.7. Сравнение разработанных оценочных функций с существующими.

3.2. Гидрофобная комплементарность бета-блокаторов в сайте связывания р2-адренэргического рецептора и её использование для предсказания константы связывания.

3.2.1. Анализ гидрофобной организации комплексов вРСЯ с лигандами.

3.2.2. Результаты докинга бета-блокаторов.

3.2.3. Комплементарность гидрофобных свойств в комплексах бета-блокаторов.

3.2.4. Фрагментарная функция расчета аффинности.

3.2.5. Поиск соединений с потенциально высокой аффинностью.

3.2.6. Сравнение предложенного метода предсказания аффинности с существующими.

Список литературы диссертационного исследования кандидат физико-математических наук Новоселецкий, Валерий Николаевич, 2010 год

1. Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J. (1990). Basic local alignment search tool. J. Mol. Biol. 215, 403^110.

2. Altschul, S.F., Madden, T.L., Schaffer, A.A., Zhang, J., Zhang, Z., Miller, W., Lipman, DJ. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389-3402.

3. Andrade, S.L., Dickmanns, A., Ficner, R., Einsle, O. (2005). Crystal structure of the archaeal ammonium transporter Amt-1 from Archaeoglobus fulgidus. Proc. Natl. Acad. Sci. Usa 102, 14994-14999.

4. Anfinsen, C.B., Harrington, W.F., Hvidt, A., Lindstrom-Lang, K. (1955). Studies on the structural basis of ribonuclease activity. Biochim. Biophys. Acta 17, 141—142.

5. Archer, E., Maigret, В., Escrieut, C., Pradayrol, L., Fourmy, D. (2003). Rhodopsin crystal: new template yielding realistic models of G-protein-coupled receptors? Trends Pharmacol. Sci. 24, 36^10.

6. Ayton, G.S., Voth, G.A. (2009). Systematic inultiscale simulation of membrane protein systems. Curr. Opin. Struct. Biol. 19, 138-44.

7. Baker, D., Sali, A. (2001). Protein structure prediction and structural genomics. Science 294, 93-96.

8. Baker, J.G. (2005). The selectivity of beta-adrenoceptor antagonists at the human betal, beta2 and beta3 adrenoceptors. Br. J. Pharmacol. 144, 317—322.

9. Baldwin, J.M., Schertler, G.F., Unger, V.M. (1997). An a-carbon template for the transmembrane helices in the rhodopsin family of G-protein-coupled receptors. J. Mol. Biol. 272,144-164.

10. Basdevant, N., Borgis, D., Ha-Duong, T. (2007). A coarse-grained protein-protein potential derived from an all-atom force field. J. Phys. Chem. B. Ill, 9390-9399.

11. Becker, O.M., Marantz, Y., Shacham, S., Inbal, B., Heifetz, A., Kalid, O., Bar-Haim, S., Warshaviak, D., Fichman, M., Noiman, S. (2004). G protein-coupled receptors: in silico drug discovery in 3D. Proc. Natl. Acad. Sci. U. S. A. 101, 11304-11309.

12. Benkert, P., Tosatto, S.C.E., Schomburg, D. (2008). QMEAN: A comprehensive scoring function for model quality assessment. Proteins: Structure, Function, arid Bioinformatics 71, 261-277.

13. Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E. (2000). The Protein Data Bank. Nucleic Acids Research 28, 235-242.

14. Beuming, T., Weinstein, H. (2005). Modeling membrane proteins based on low-resolution electron microscopy maps: a template for the TM domains of the oxalate transporter OxlT. Protein Eng. Des. Sel. 18, 119-125.

15. Bhattacharya, S., Hal, S.E., Li, H., Vaidehi, N. (2008). Ligand-stabilized conformational states of human beta(2) adrenergic receptor: insight into G-protein-coupled receptor activation. Biophys. J. 94, 2027-2042.

16. Bowie, J. U.; Liithy, R.; Eisenberg, D. (1991). A method to identify protein sequences that fold into a known three-dimensional structure. Science 253, 164-170.

17. Brodsky L.I., Ivanov V.V., Kalaidzidis Ya.L., Leontovich A.M., Nikolaev V.K., Feranchuk S.I., Drachev V.A. (1995). GeneBee-NET: Internet-based server for analyzing biopolymers structure. Biochemistry 60, 923-928.

18. Brown, E.M., Fedak, S.A., Woodard, C.J., Aurbach, G.D. (1976). Beta-Adrenergic receptor interactions. Direct comparison of receptor interaction and biological activity. J. Biol. Chem. 251, 1239-1246.

19. Brown, W.M., Faulon, J.-L., Sale, K. (2005). A Deterministic Algorithm for Constrained Enumeration of Transmembrane Protein Folds. Comp. Biol. Chem. 29, 143—150.

20. Brizzi, V., Francioli, M., Brufani, M., Filocamo, L., Bruni, G., Massarelli, P. (1999). Synthesis, binding affinity and selectivity of new beta 1- and beta 2-adrenoceptor blockers. Farmaco. 54, 713-720.

21. Buchete, N.V., Straub, J.E., Thirumalai, D. (2004). Orientational potentials extracted from protein structures improve native fold recognition. Protein Sci. 13, 862—874.

22. Bujnicki, J.M., Elofsson, A., Fischer, D., Rychlewski, L. (2001). Structure prediction meta server. Bioinformatics 17, 750-751.

23. Chambers, J.J., Nichols, D.E. (2002). A homology-based model of the human 5-HT2A receptor derived from an in silico activated G-protein coupled receptor. J. Comput. Aided Mol.Des. 16,511-520.

24. Chou, K.-C. (2005). Prediction of G-protein Receptor Classes. J. Proteome Res. 4, 14131418.

25. Chugunov, A.O., Novoseletsky, V.N., Arseniev, A.S., Efremov, R.G. (2007). A novel method for packing quality assessment of transmembrane alpha-helical domains in proteins. Biochemistry (Mosc.) 72, 293-300.

26. Cieplak, M., Hoang, T.X., Robbins, M.O. (2002). Folding and stretching in a Go-like model of titin. Proteins 49, 114-124.

27. Clark, M., Cramer, R.D., van Opdenbosch, N. (1989). Validation of the general-purpose TRIPOS 5.2 force field. J. Comput. Cliem. 10, 982-1012.

28. Connolly, M.L. (1983). Solvent-accessible surfaces of proteins and nucleic acids. Science 221, 709-713.

29. Contreras-Moreira, B., Ezkurdia, I., Tress, M.L., Valencia, A. (2005). Empirical limits for template-based protein structure prediction: the CASP5 example. FEBS Lett. 579, 1203— 1207.

30. Costanzi, S. (2008). On the applicability of GPCR homology models to computer-aided drug discovery: a comparison between in silico and crystal structures of the beta2-adrenergic receptor. J Med Chem. 51, 2907-2914.

31. Cozzetto, D., Giorgetti, A., Raimondo, D., Tramontano, A. (2008). The evaluation of protein structure prediction results. Mol Biotechnol. 39, 1-8.

32. Dallanoce, C., Frigerio, F., De Amici, M„ Dorsch, S., Klotz, K.N., De Micheli, C. (2007). Novel chiral isoxazole derivatives: synthesis and pharmacological characterization at human beta-adrenergic receptor subtypes. Bioorg Med Chetn. 15, 2533-2543.

33. Donnelly, D., Findlay, J. B., Blundell, T. L. (1994). The evolution and structure of aminergic G protein-coupled receptors. Receptors Channels 2, 61—78.

34. Efremov, R.G., Chugunov, A.O., Pyrkov, T.V., Priestle, J.P., Arseniev, A.S., Jacoby, E. (2007). Molecular lipophilicity in protein modeling and drug design. Cttrr. Med. Chetn. 14, 393^115.

35. Efremov, R.G., Nolde, D.E., Konshina, A.G., Syrtcev, N.P., Arseniev, A.S. (2004). Peptides and proteins in membranes: what can we learn via computer simulations? Curr. Med. Chetn. 11,2421-2442.

36. Eilers, M., Shekar, S.C., Shieh, T., Smith, S.O., Fleming, P.J. (2000). Internal packing of helical membrane proteins. Proc. Natl. Acad. Sci. U. S. A. 97, 5796-5801.

37. Essen, L., Siegert, R., Lehmann, W.D., Oesterlielt, D. (1998). Lipid patches in membrane protein oligomers: crystal structure of the bacteriorhodopsin-lipid complex Proc.Natl.Acad.Sci. USA 95, 11673-11678.

38. Eyre, T.A., Partridge, L., Thornton, J.M. (2004). Computational analysis of a-helical membrane protein structure: implications for the prediction of 3D structural models. Protein Eng. Des. Sel. 17, 613-624.

39. Ewing T.J., Makino S„ Skillman A.G., Kuntz I.D. (2001). DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases. J. Comput. Aided. Mol. Des. 15, 411-428.

40. Fauchere J.L., Quaredon P., Kaetterer L. (1998). Estimating and representing hydrophobicity potential. J. Mol. Graphics 6, 203-206.

41. Finkelstein A. (1997). Protein structure: what is it possible to predict now? Curr. Opin. Struct. Biol. 7, 60-71.

42. Fiser, A., Sali, A. (2003). Modeller: generation and refinement of homology-based protein structure models. Methods Enzymol. 374, 461-491.

43. Fleishman, S.J., Ben-Tal, N. (2006). Progress in structure prediction of a-helical membrane proteins. Curr. Opin. Struct. Biol. 16, 496-504.

44. Fleishman, S.J., Harrington, S., Friesner, R.A., Honig, B., Ben-Tal, N. (2004). An automatic method for predicting transmembrane protein structures using cryo-EM and evolutionary data. Biophys. J. 87, 3448-3459.

45. Fleishman, S.J., Unger, V.M., Ben-Tal, N. (2006). Transmembrane protein structures without X-rays. Trends Biochem. Sci. 31, 106-113.

46. Foord, F.M. (2002). Receptor Classification: Post Genome. Curr. Opin. Pharm. 2, 561—566.

47. Furet, P., Sele, A., Cohen, N.C. (1988). 3D molecular lipophilicity potential profiles: a new tool in molecular modeling. J. Mol. Graphics 6, 182-189.

48. Gaillard, P., Carrupt, P.A., Testa, B., Boudon, A. (1994). Molecular lipophilicity potential, a tool in 3D QSAR: method and applications. J. Comput. Aided. Mol. Des. 8, 83-96.

49. Ghose, A.K., Viswanadhan, V.N., Wendoloski, J.J. (1998). Prediction of hydrophobic (lipophilic) properties of small organic molecules using fragmental methods: an analysis of ALOGP and CLOGP methods. J. Phys. Chem. 102, 3762-3772.

50. Gieldoii, A, Kazmierkiewicz, R, Slusarz, R, Ciarkowski, J. (2001). Molecular modeling of interactions of the non-peptide antagonist YM087 with the human vasopressin Via, V2 receptors and with oxytocin receptors. J Comput Aided Mol Des. 15, 1085-1104.

51. Ginalski, K. (2006). Comparative modeling for protein structure prediction. Curr. Opin. Struct. Biol. 16, 172-177.

52. Guex, N., Peitsch, M.C. (1997). SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modeling. Electrophoresis 18, 2714-2723.

53. Hallmen, C., Wiese, M. (2006). Molecular dynamics simulation of the human adenosine A3 receptor: agonist induced conformational changes of Trp243. J. Comput. Aided. Mol. Des. 20, 673-84.

54. He, Y., Nikulin, V.I., Vansal, S.S., Feller, D.R., Miller, D.D. (2000). Synthesis and human beta-adrenoceptor activity of l-(3,5-diiodo-4- methoxybenzyl)-1,2,3,4-tetrahydroisoquinolin-6-ol derivatives in vitro. J. Med. Chem. 43, 591—598.

55. Heiden, W., Moeckel, G., Brickmann, J. (1993). A new approach to the display of local lipophilicity/hydrophilicity mapped on molecular surfaces. J. Comput. Aided. Mol. Des. 7, 503-514.

56. Henderson, R., Baldwin, J. M., Ceska, T. A., Zemlin, F., Beckmann, E., Downing, K. H. (1990). Model for the Structure of Bacteriorhodopsin Based on High-Resolution Electron Cryo-Microscopy. J. Mol. Biol. 212, 899-929.

57. 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.

58. Herzyk, P., Hubbard, R. E. (1998). Combined biophysical and biochemical information confirms arrangement of transmembrane helices visible from the three-dimensional map of frog rhodopsin. J. Mol. Biol. 281, 741-754.

59. Hillisch, A., Pineda, L.F., Hilgenfeld, R. (2004). Utility of Homology Models in the Drug Discovery Process. Drug Discov. Today 9, 659-669.

60. Hooft, R.W.W., Vriend, G., Sander, C., Abola, E.E. (1996). Errors in protein structures. Nature 381, 272.

61. Horn, F., Weare, J., Beukers, M.W., Horsch, S., Bairoch, A., Chen, W., Edvardsen, O., Campagne, F., Vriend, G. (1998). GPCRDB: an information system for G-protein-coupled receptors. Nucleic Acids Res. 26, 277-281.

62. Insightll, Release 2000, Accelrys, San Diego, CA, 2002.

63. Jaakola, V.P., Griffith, M.T., Hanson, M.A., Cherezov, V., Chien. E.Y., Lane, J.R., Ijzerman, A.P., Stevens, R.C. (2008). The 2.6 angstrom crystal structure of a human A2A adenosine receptor bound to an antagonist. Science 322, 1211—1217.

64. Jain A.N. (2006). Scoring functions for protein-ligand docking. Curr. Protein Pept. Sci. 7, 407-420.

65. Jayasinghe, S., Hristova, K., White, S.H. (2001). Energetics, stability, and prediction of transmembrane helices. J. Mol. Biol. 312, 927-934.

66. Jones, G., Willett, P., Glen, R.C. (1995). Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. J. Mol. Biol. 245, 43-53.

67. Jorgensen, W.L. (2004). The Many Roles of Computation in Drug Discovery. Science 303, 1813-1818.

68. Kabsch, W., Sander, C. (1983). Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers. 22, 2577—2637.

69. Kim, D.E., Chivian, D., Baker, D. (2004). Protein structure prediction and analysis using the Roberta server. Nucleic Acids Res. 32, W526-W531.

70. Kitchen, D.B., Decornez, H., Furr, J.R., Bajorath, J. (2004). Docking and scoring in virtual screening for drug discovery: methods and applications. Nat. Rev. Drug Discov. 3, 935^49.

71. Klabunde, T., Hessler, G. (2002). Drug Design Strategies for Targeting G-Protein-Coupled Receptors. Chembiochem 10, 928-944.

72. Klepeis, J.L., Lindorff-Larsen, K., Dror, R.O., Shaw, D.E. (2009). Long-timescale molecular dynamics simulations of protein structure and function. Curr. Opin. Struct. Biol. 19, 120— 127.

73. Kobilka, B., Schertler, G.F. (2008). New G-protein-coupled receptor crystal structures: insights and limitations. Trends Pharmacol. Sci. 29, 79-83.

74. Kolb, P., Rosenbaum, D.M., Irwin, J.J., Fung, J.J., Kobilka, B.K., Shoichet, B.K. (2009). Structure-based discovery of beta2-adrenergic receptor ligands. Proc. Natl. Acad. Sei. USA 106, 6843-6848.

75. Kolbe, M., Besir, H., Essen, L.O., Oesterlielt, D. (2000). Structure of the light-driven chloride pump halorhodopsin at 1.8 A resolution. Science 288, 1390-1396

76. Labrid, C., Rocher, I., Guery, O. (1989). Structure-activity relationships as a response to the pharmacological differences in beta-receptor ligands. Am. J. Hypertens. 2, 245S-251S.

77. Lands, A.M., Arnold, A., MacAuliff, J.P., Brown, T.G. (1967). Differentiation of receptor systems activated by sympathomimetic amines. Nature 214, 597-598.

78. Law, R.J., Capener, C., Baaden, M., Bond, P.J., Campbell, J., Patargias, G., Arinaminpathy, Y., Sansom, M.S. (2005). Membrane protein structure quality in molecular dynamics simulation. J. Mol. Graph. Model. 24, 157—165.

79. Lefkowitz, R.J. (2004). Historical Review: A Brief History and Personal Retrospective of Seven-Transmembrane Receptors. Trends Pharmacol. Sei. 25, 413^22.

80. Lesk, A.M., Chothia, C. (1986). The Response of Protein Structures to Amino-Acid Sequence Changes. Philos. Trans. R. Soc. Lond. Biol. Sei. 317, 345-356.

81. Lin, S.W., Imamoto, Y., Fukada, Y., Shichida, Y., Yoshizawa, T., Mathies, R.A. (1994). What makes red visual pigments red? A resonance Raman microprobe study of retinal chromophore structure in iodopsin. Biochemistry 33, 2151-2160.

82. Lindahl, E., Hess, B., van der Spoel, D. (2001). GROMACS 3.0: A package for molecular simulation and trajectoiy analysis. J. Mol. Mod. 7, 306-317.

83. Lindahl, E., Sansom, M.S. (2008). Membrane proteins: molecular dynamics simulations. Curr. Opin. Struct. Biol. 18, 425-431.

84. Lomize, M.A., Lomize, A.L., Pogozheva, I.D., Mosberg, H.I. (2006). OPM: Orientations of Proteins in Membranes database. Bioinformatics 22, 623-625.

85. Louis, S.N., Nero, T.L., Iakovidis, D., Coiagrande, F.M., Jackman, G.P., Louis, W.J. (1999). beta(l)- and beta(2)-Adrenoceptor antagonist activity of a series of para-substituted N-isopropylphenoxypropanolamines. Eur. J. Med. Chem. 34, 919-937.

86. Louis, S.N., Rezmann-Vitti, L.A., Nero, T.L., Iakovidis, D., Jackman, G.P., Louis, W.J. (2002). CoMFA analysis of the human beta(l)-adrenoceptor binding affinity of a series of phenoxypropanolamines. Eur. J. Med. Chem. 37, 111—125.

87. De Los Angeles, J.E., Nikulin, V.I., Shams, G., Konkar, A.A., Mehta, R., Feller, D.R., Miller, D.D. (1996). Iodinated analogs of trimetoquinol as highly potent and selective beta 2-adrenoceptor ligands. J. Med. Chem. 39, 3701-3711.

88. Lundstrom, K. (2005). Structural genomics of GPCRs. Trends Biotechnol. 2, 103-110.

89. Luthy, R., Bowie, J.U., Eisenberg, D. (1992). Assessment of protein models with three-dimensional profiles. Nature 356, 83—85.

90. Manalan, A.S., Besch, H.R., Watanabe, A.M., (1981). Characterization of 3H.(+/-) carazolol binding to beta-adrenergic receptors, Circ.Res. 49, 326-336.

91. Mannhold, R., (2005). The impact of lipophilicity in drug research: a case report on beta-blockers. Mini Rev. Med. Chem. 5, 197-205.

92. Marrink, S. J., A. E. Mark. (2003). Molecular dynamics simulation of the formation, structure, and dynamics of small phospholipid vesicles. J. Am. Chem. Soc. 125, 1523315242.

93. Marrink, S. J., de Vries, A. H., Mark, A. E. (2004). Coarse Grained Model for Semiquantitative Lipid Simulations. J. Phys. Chem. B. 108, 750-760.

94. Marrink, S. J., Risselada H. J., Yefimov S., Tieleman D. P., de Vries A. H. (2007). The MARTINI Force Field: Coarse Grained Model for Biomolecular Simulations. J. Phys. Chem. B. 111,7812-7824.

95. Marti-Renom, M.A., Stuart, A.C., Fiser, A., Sanchez, R., Melo, F., Sali, A. (2000). Comparative protein structure modeling of genes and genomes. Annu. Rev. Biophys. Biomol. Struct. 29, 291-325.

96. Mehler, E.L., Periole, X., Hassan, S.A., Weinstein, H. (2002). Key issues in the computational simulation of GPCR function: representation of loop domains. J. Comput. AidedMol. Des. 16, 841-53.

97. Miller, M.A. (2002). Chemical Database Techniques in Drug Discovery. Nat. Rev. Drug Disc. 1, 223-227.

98. Molecular Simulations Inc. Insightll. (2000). User Guide. MSI, San Diego, CA.

99. Muller-Plathe, F. (2002). Coarse-graining in polymer simulation: from the.atomistic to the mesoscopic scale and back. Cliem. Phys. Chem. 3, 755-769.

100. Nikiforovich, G.V., Galaktionov, S., Balodis, J., Marshall, G.R. (2001) Novel approach to computer modeling of seven-helical transmembrane proteins: current progress in the test case of bacteriorhodopsin. Acta Biochim Pol. 48, 53-64.

101. Nikiforovich, G.V., Marshall, G.R. (2003). Three-dimensional model for meta-II rhodopsin, an activated G-protein-coupled receptor. Biochemistry 42, 9110-9120.

102. Ohlson, T., Wallner, B., Elofsson, A. (2004). Profile-profile methods provide improved fold-recognition: a study of different profile-profile alignment methods. Proteins 57, 188— 197.

103. Okada, T., Sugihara, M., Bondar, A.N., Elstner, M., Entel, P., Buss, V. (2004). The retinal conformation and its environment in rhodopsin in light of a new 2.2 A crystal structure.J. Mol. Biol. 342, 571-583.

104. Palczewski, K., Kumasaka, T., Hon, T., Behnke, C.A., Motoshima, H., Fox, B.A., Le Trong, I., Teller, D.C., Okada, T., Stenkamp, R.E., Yamamoto, M., Miyano, M. (2000). Crystal Structure of Rhodopsin: A G-Protein-Coupled Receptor. Science 289, 739-745.

105. Palczewski, K. (2006). G-Protein-Coupled Receptor Rhodopsin. Annu. Rev. Biochem. 75, 743-767.

106. Pappu, R.V., Marshall, G.R., Ponder, J.W. (1999). A Potential Smoothing Algorithm Accurately Predicts Transmembrane Helix Packing. Nat. Struct. Biol. 6, 50-55.

107. Park, J., Teichmann, S.A., Hubbard, T., Chothia, C. (1997). Intermediate sequences increase the detection of homology between sequences. J. Mol. Biol. 273, 349—354.

108. Park, J.B. (2005). N-coumaroyldopamine and N-caffeoyldopamine increase cAMP via beta 2-adrenoceptors in myelocytic U937 cells. FASEB J. 19, 497-502.

109. Patrick G.L. An Introduction to Medicinal Chemistry, Oxford University Press Inc., New York, 2005, Third Edition.

110. Pearson, W.R. (1990). Rapid and Sensitive Sequence Comparison with FASTP and FASTA. Methods Enzymol. 183, 63-98.

111. Periole, X., Huber, T., Marrink, S.J., Sakmar, T.P. (2007). G protein-coupled receptors self-assemble in dynamics simulations of model bilayers. J. Am. Chem. Soc. 129, 10126-10132.

112. Pierce, K.L., Premont, R.T., Lefkowitz, R.J. (2002). Seven-Transmembrane Receptors. Nat. Rev. Mol. Cell. Biol. 3, 639-650.

113. Pilpel, Y„ Ben-Tal, N., Lancet, D. (1999). kPROT: a knowledge-based scale for the propensity of residue orientation in transmembrane segments. Application to membrane protein structure prediction. J. Mol. Biol. 294, 921-935.

114. Pliego-Pastrana, P., and M. D. Carbajal-Tinoco. (2003). Effective pair potentials between protein amino acids. Phys. Rev. E. 68:011903.

115. Pogozheva, I.D., Lomize, A.L., Mosberg, H.I. (1997). The Transmembrane 7-a-Bundle of Rhodopsin: Distance Geometry Calculations with Hydrogen Bonding Constraints. Biophys. J. 72, 1963-1985.

116. Pogozheva, I.D., Przydzial, M.J., Mosberg, H.I. (2005). Homology modeling of opioid receptor-ligand complexes using experimental constraints. AAPSJ. 7, E434-E448.

117. Press William H., Teukolsky Saul A., Vetterling William T., Flannery Brian P. Numerical Recipes in FORTRAN. 2nd ed. Cambridge University Press, 1992, p. 640.

118. Pyrkov, T.V., Efremov, R.G. (2007). A Fragment-Based Scoring Function to Re-rank ATP Docking Results Int. J. Mol. Sci. 8, 1083-1094.

119. Pyrkov, T.V., Kosinsky, Y.A., Arseniev, A.S., Priestle, J.P., Jacoby, E., Efremov, R.G.2007). Docking of ATP to Ca-ATPase: considering protein domain motions. J. Chem. Inf. Model. 47, 1171-1181.

120. Pyrkov, T.V., Priestle, J.P., Jacoby, E., Efremov, R.G. (2008). Ligand-specilic scoring functions: improved ranking of docking solutions. SAR OSAR Environ Res. 19, 91-99.

121. Pyrkov, T.V., Chugunov, A.O., Krylov, N.A., Nolde, D.E., Efremov, R.G. (2009). PLATINUM: a web tool for analysis of hydrophobic/hydrophilic organization of biomolecular complexes. Bioinformatics 25, 1201-1202.

122. Reddy, Ch.S. et al. (2006). Homology modelling of membrane protein: a critical assessment. Comput. Biol. Chem. 30, 120-126.

123. Rees, D.C., DeAntonio, L., Eisenberg, D. (1989). Hydrophobic organization of membrane proteins. Science 245, 510-513.

124. Reynolds, K.A., Katritch, V., Abagyan, R. (2009). Identifying conformational changes of the beta(2) adrenoceptor that enable accurate prediction of ligand/receptor interactions and screening for GPCR modulators. J. Comput.-AidedMol. Des. 23, 273—288.

125. Röhl, C.A., Strauss, C.E., Misura, K.M., Baker, D. (2004). Protein structure prediction using Rosetta. Methods Enzymol. 383, 66—93.

126. Schertier, G.F., Hargrave, P.A. (1995). Projection structure of frog rhodopsin in two crystal forms. Proc. Natl. Acad. Sei. U. S. A. 92, 11578-11582.

127. Schneider, G., Fechner, U. (2005). Computer-Based De Novo Design of Drug-Like Molecules. Nat. Rev. Drug Disc. 4, 640-663.

128. Schöneberg, T., Schulza, A., Biebermannb, H., Hermsdorf, T., Römplera, IL, Sangkuhl, K. (2004). Mutant G-protein-Coupled Receptors as a Cause of Human Diseases. Pharmacol. Ther. 104, 173-206.

129. Schrödinger, LLC, New York, NY, 2007; Maestro, version 8.0; software available at http://www.schrodinger.com.

130. Schrödinger, LLC, New York, NY, 2007; Glide, version 4.5; software available at http://www.schrodinger.com.

131. Schrödinger, LLC, New York, NY, 2007; CombiGlide, version 1.5; software available at http://www.sclirodinger.com.

132. Schueler-Furman, O., Wang, C., Bradley, P., Misura, K., Baker, D. (2005). Progress in Modeling of Protein Structures and Interactions. Science 310, 638-642.

133. Schuettelkopf, A.W., van Aalten, D.M.F. (2004). PRODRG a tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallographica D60, 1355-1363.

134. Shelley, J. C., Shelley, M. Y„ Reeder, R. C., Bandyopadhyay, S., Moore, P. B., Klein, M. L. (2001). Simulations of phospholipids using a coarse grain model. J. Phys. Chem. B. 105, 9785-9792.

135. Shieh, T., Han, M., Sakmar, T.P., Smith, S.O. (1997). The steric trigger in rhodopsin activation. J. Mol. Biol. 269, 373-384.

136. Shimamura, T., Hiraki, K., Takahashi, N., Hori, T., Ago, H., Masuda, K., Takio, K., Ishiguro, M., Miyano, M. (2008). Crystal structure of squid rhodopsin with intracellularly extended cytoplasmic region. J. Biol. Chem. 283, 17753-17756.

137. Schneider, G., Fechner, U. (2005). Computer-based de novo design of drug-like molecules. Nat. Rev. DrugDiscov. 4, 649-663.

138. Shoichet, B.K. (2004). Virtual Screening of Chemical Libraries. Nature 432, 962-965.

139. Soderhall, J.A., Polymeropoulos, E.E., Paulini, K., Giinther, E., Kiihne, R. (2005). Antagonist and agonist binding models of the human gonadotropin-releasing hormone receptor. Biochem. Biophys. Res. Commun. 333, 568-582.

140. Sorgen, P.L., Hu, Y., Guan, L., Kaback, H.R., Girvin, M.E. (2002). An approach to membrane protein structure without crystals. Proc. Natl. Acad. Sci. U. S. A. 99, 14037— 14040.

141. Strader, C.D., Sigal, I.S., Candelore, M.R., Rands, E., Hill, W.S., Dixon, R.A. (1988). Conserved aspartic acid residues 79 and 113 of the beta-adrenergic receptor have different roles in receptor function. J. Biol. Chem. 263, 10267-10271.

142. Strader, C.D., Sigal, I.S., Dixon, R.A. (1989). Structural basis of beta-adrenergic receptor function. FASEB J. 3, 1825-1832.

143. Strahs, D., Weinstein, H. (1997). Comparative modeling and molecular dynamics studies of the delta, kappa and mu opioid receptors. Protein Eng. 10, 1019-1038.

144. Suryanarayana, S., Kobilka, B.K. (1993). Amino acid substitutions at position 312 in the seventh hydrophobic segment of the beta 2-adrenergic receptor modify ligand-binding specificity. Mol. Pharmacol. 44, 111—114.

145. Takeda, S„ Kadowaki, S„ Haga, T., Takaesu, H., Mitaku, S. (2002). Identification of G-protein-coupled receptor genes from the human genome sequence. FEBSLett. 520, 97-101.

146. Testa, B., Carrupt, P.A., Gaillard, P., Billois, F., Weber, P. (1996). Lipophilicity in molecular modeling. Pharm. Res. 13, 335-343.

147. Tozzini, V. (2005). Coarse-grained models for proteins. Curr. Opin. Struct. Biol. 15, 144150.

148. Tramontano, A. (2003). Comparative Modelling Techniques: Where are we? Comp. Fund. Genomics 4,402-405.

149. Tramontano, A., Morea, V. (2003). Assessment of homology-based predictions in CASP5. Proteins 53, 352-368.

150. Ubarretxena-Belandia, I., Engelman, D. M. (2001). Helical membrane proteins: diversity of functions in the context of simple architecture. Curr. Opin. Struct. Biol. 11, 370-376.

151. Ulmschneider, M.B., Sansom, M.S., Di Nola, A. (2005) Properties of integral membrane protein structures: derivation of an implicit membrane potential. Proteins 59, 252-265.

152. Ulmschneider, M.B., Sansom, M.S., Di Nola, A. (2006). Evaluating tilt angles of membrane-associated helices: comparison of computational and NMR techniques. Biophys J. 90, 1650— 1660.

153. UniProt Consortium. (2010). The Universal Protein Resource (UniProt) in 2010. Nucleic Acids Res. 38(Database issue), D142-8.

154. Vaidehi, T., Floriano, W.B., Trabanino, R., Hall, S.E., Freddolino, P., Choi, E.J., Zamanakos, G., Goddard III, W.A. (2002). Prediction of Structure and Function of G-Protein-Coupled Receptors. Proc. Natl. Acad. Sci. U. S. A. 99, 12622-12627.

155. Wallin, E., Tsukihara, T., Yoshikawa, S., von Heijne, G., Elofsson, A. (1997). Architecture of helix bundle membrane proteins: an analysis of cytochrome e oxidase from bovine mitochondria. Protein Sci. 6, 808—815.

156. Warne, A., Serrano-Vega, M.J., Baker, J.G., Moukhametzianov, R., Edwards,P.C., Henderson, R., Leslie, A.G.W., Tate, C.G., Schertler, G.F.X. (2008) Structure of the Beta 1-Adrenergic G Protein-Coupled Receptor. Nature 454, 486.

157. Weiland, G.A., Minneman, K.P., Molinoff, P.B. (1979). Fundamental difference between the molecular interactions of agonists and antagonists with the beta-adrenergic receptor. Nature 281, 114-117.

158. Wishart, D.S., Knox, C., Guo, A.C., Cheng, D., Shrivastava, S., Tzur, D., Gautam, B., Hassanali, M. (2008). DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res. 36, D901-906.

159. White, S.H. (2009). Biophysical dissection of membrane proteins. Nature 459, 344-346.

160. Wolf, S., Bockmann, M., Howeler, U., Schlitter, J., Gerwert, K. (2008). Simulations of a G protein-coupled receptor homology model predict dynamic features and a ligand binding site. FEBSLett. 582, 3335-3342.

161. Yarov-Yarovoy, V., Schonbrun, J., Baker, D. (2006). Multipass Membrane Protein Structure Prediction Using Rosetta. Proteins 62, 1010—1025.

162. Yang, X., Wang, Z., Dong, W., Ling, L., Yang, H., Chen, R. (2003). Modeling and docking of the three-dimensional structure of the human melanocortin 4 receptor. J. Protein Chem. 22, 335-344.

163. Zhang, Y., Devries, M.E., Skolnick, J. (2006). Structure modeling of all identified G-protein-coupled receptors in the human genome. PLoS Comput. Biol. 2, el3.

164. Zhang, Y., Skolnick, J. (2004). Automated structure prediction of weakly homologous proteins on a genomic scale. Proc. Natl. Acad. Sci. U. S. A. 101, 7594-7599.

165. Zhdanov, V.P., Kasemo, B. (2001). Folding of bundles of a-helices in solution, membranes, and adsorbed overlayers. Proteins 42, 481-494.

166. Zhou, J., Thorpe, I.F., Izvekov, S., Voth, G.A. (2007). Coarse-grained peptide modeling using a systematic multiscale approach. BiophysJ. 92, 4289-4303.