In silico prediction of cytochrome P450-mediated drug metabolism

Combinatorial Chemistry and High Throughput Screening

Volumn 14, Issue 5, 2011, Pages 388-395

  Zhang, Tao ^a   Chen, Qi ^a   Li, Li ^a   Liu, Limin Angela ^a   Wei, Dong Qing ^a  

^a Shanghai Jiao Tong University   (China)

Author keywords

Computational methods; CYP; Data and structure based prediction; Metabolism

Indexed keywords

CYTOCHROME P450; CYTOCHROME P450 1A2; CYTOCHROME P450 2C9; CYTOCHROME P450 2D6; CYTOCHROME P450 3A4; FLURBIPROFEN;

ARTICLE; COMPUTER MODEL; COMPUTER PREDICTION; DRUG ABSORPTION; DRUG DISTRIBUTION; DRUG EFFICACY; DRUG EXCRETION; DRUG METABOLISM; DRUG SAFETY; ENZYME STRUCTURE; PRIORITY JOURNAL; PROTEIN INTERACTION;

COMPUTER SIMULATION; CYTOCHROME P-450 ENZYME SYSTEM; DRUG DISCOVERY; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; HIGH-THROUGHPUT SCREENING ASSAYS; PHARMACEUTICAL PREPARATIONS;

EID: 79955743124     PISSN: 13862073     EISSN: None     Source Type: Journal    
DOI: 10.2174/138620711795508412     Document Type: Article

References (92)

1. Sirois, S.; Hatzakis, G.; Wei, D.Q.; Du, Q.S.; Chou, K.C. Assessment of chemical libraries for their druggability. Comput. Biol. Chem., 2005, 29(1), 55-67. (Pubitemid 40146367)
2. Myers, P.L. Will combinatorial chemistry deliver real medicines? Curr. Opin. Biotechnol., 1997, 8(6), 701-707. (Pubitemid 27517246)
3. Bajorath, J. Integration of virtual and high-throughput screening. Nat. Rev. Drug Discov., 2002, 1(11), 882-894. (Pubitemid 37361583)
4. Mayr, L.M.; Bojanic, D. Novel trends in high-throughput screening. Curr. Opin. Pharmacol., 2009, 9(5), 580-588.
5. van de Waterbeemd, H.; Gifford, E. ADMET in silico modelling: towards prediction paradise? Nat. Rev. Drug Discov., 2003, 2(3), 192-204.
6. Baranczewski, P.; Stanczak, A.; Sundberg, K.; Svensson, R.; Wallin, A.; Jansson, J.; Garberg, P.; Postlind, H. Introduction to in vitro estimation of metabolic stability and drug interactions of new chemical entities in drug discovery and development. Pharmacol Rep, 2006, 58(4), 453-472. (Pubitemid 44383272)
7. Kennedy, T. Managing the drug discovery/development interface. Drug Discov. Today, 1997, 2(10), 436-444. (Pubitemid 27387353)
8. Keldenich, J. Measurement and prediction of oral absorption. Chem. Biodivers., 2009, 6(11), 2000-2013.
9. Hou, T.; Li, Y.; Zhang, W.; Wang, J. Recent developments of in silico predictions of intestinal absorption and oral bioavailability. Comb. Chem. High Throughput Screen., 2009, 12(5), 497-506.
10. Dahan, A.; Miller, J.M.; Amidon, G.L. Prediction of solubility and permeability class membership: Provisional BCS Classification of the World's Top Oral Drugs. AAPS J, 2009, 11(4), 740-746.
11. Akamatsu, M.; Fujikawa, M.; Nakao, K.; Shimizu, R. In silico prediction of human oral absorption based on QSAR analyses of PAMPA permeability. Chem. Biodivers., 2009, 6(11), 1845-1866.
12. Moda, T.L.; Montanari, C.A.; Andricopulo, A.D. Hologram QSAR model for the prediction of human oral bioavailability. Bioorg. Med. Chem., 2007, 15(24), 7738-7745. (Pubitemid 47575914)
13. Berellini, G.; Springer, C.; Waters, N.J.; Lombardo, F. In silico prediction of volume of distribution in human using linear and nonlinear models on a 669 compound data set. J. Med. Chem., 2009, 52(14), 4488-4495.
14. Sui, X.; Sun, J.; Wu, X.; Li, H.; Liu, J.; He, Z. Predicting the volume of distribution of drugs in humansCurrent drug metabolism. Curr. Drug Metab., 2008, 9(6), 574-580. (Pubitemid 352025189)
15. Kokate, A.; Li, X.; Williams, P.J.; Singh, P.; Jasti, B.R. In silico pediction of drug permeability across buccal mucosa. Pharm. Res., 2009, 26(5), 1130-1139.
16. Paix O. P.; Gouveia, L.F.; Morais, J.A.G. Prediction of drug distribution within bloodEuropean journal of pharmaceutical sciences. Eur. J. Pharm. Sci., 2009, 36(4-5), 544-554.
17. Vedani, A.; Smiesko, M. In silico toxicology in drug discoveryconcepts based on three-dimensional models. Altern. Lab Anim., 2009, 37(5), 477-496.
18. Luo, G.; Johnson, S.; Hsueh, M.M.; Zheng, J.; Cai, H.; Xin, B.; Chong, S.; He, K.; Harper, T.W. In silico prediction of biliary excretion of drugs in rats based on physicochemical properties. Drug Metab. Dispos., 2010, 38(3), 422-430.
19. Gao, H.; Yao, L.; Mathieu, H.W.; Zhang, Y.; Maurer, T.S.; Troutman, M.D.; Scott, D.O.; Ruggeri, R.B.; Lin, J. In silico modeling of nonspecific binding to human liver microsomes. Drug Metab. Dispos., 2008, 36(10), 2130-2135.
20. Wang, J. F.; Zhang, C. C.; Yan, J. Y.; Chou, K. C.; Wei, D. Q. Molecular Modeling of CYP Proteins and its Implication for Personal Drug Design. Automation in Proteomics and Genomics: An Engineering Case-Based Approach-Wiley. Molecular Modeling of CYP Proteins and its Implication for Personal Drug Design;Wiley: Hoboken, United States, 2009.
21. Lewis, D.F.V.; Ito, Y.; Goldfarb, P.S. Structural modelling of the human drug-metabolizing cytochromes P450Current medicinal chemistry. Curr. Med. Chem., 2006, 13(22), 2645-2652. (Pubitemid 44364142)
22. Shaik, S.; Kumar, D.; de Visser, S.P.; Altun, A.; Thiel, W. Theoretical Perspective on the Structure and Mechanism of Cytochrome P450 Enzymes. Chem. Rev., 2005, 105(6), 2279-2328. (Pubitemid 40947949)
23. Harrelson, J.P.; Atkins, W.M.; Nelson, S.D. Multiple-ligand binding in CYP2A6: Probing mechanisms of cytochrome P450 cooperativity by assessing substrate dynamics. Biochemistry, 2008, 47(9), 2978-2988. (Pubitemid 351328851)
24. Niwa, T.; Murayama, N.; Yamazaki, H. Heterotropic cooperativity in oxidation mediated by cytochrome P450. Curr. Drug Metab., 2008, 9(5), 453-462. (Pubitemid 352025198)
25. Davydov, D.R.; Halpert, J.R. Allosteric P450 mechanisms: multiple binding sites, multiple conformers or both? Expert. Opin. Drug Metab. Toxicol., 2008, 4(12), 1523-1535.
26. Lafite, P.; André, F.; Zeldin, D.C.; Dansette, P.M.; Mansuy, D. Unusual regioselectivity and active site topology of human cytochrome P450 2J2. Biochemistry, 2007, 46(36), 10237-10247.
27. Bikádi, Z.; Hazai, E. In silico description of differential enantioselectivity in methoxychlor O-demethylation by CYP2C enzymes. Biochim. Biophys. Acta, 2008, 1780(9), 1070-1079.
28. Kemp, C.A.; Maréchal, J.D.; Sutcliffe, M.J. Progress in cytochrome P450 active site modeling. Arch. Biochem. Biophys., 2005, 433(2), 361-368. (Pubitemid 39592790)
29. Wang, J.F.; Wei, D.Q. Role of structural bioinformatics and traditional Chinese medicine databases in pharmacogenomics. Pharmacogenomics, 2009, 10(8), 1213-1215.
30. de Graaf, C.; Vermeulen, N.P.E.; Feenstra, K.A. Cytochrome P450 in silico: an integrative modeling approach. J. Med. Chem., 2005, 48(8), 2725-2755. (Pubitemid 40548088)
31. Wang, J. F.; Zhang, C. C.; Chou, K. C.; Wei, D. Q. Structure of cytochrome P450s and personalized drug. Curr. Med. Chem., 2009, 16(2), 232-244.
32. Sun, H.; Scott, D.O. Structure-based drug metabolism predictions for drug design. Chem. Biol. Drug Des., 2010, 75(1), 3-17.
33. Czodrowski, P.; Kriegl, J.M.; Scheuerer, S.; Fox, T. Computational approaches to predict drug metabolismExpert opinion on drug metabolism & toxicology. Expert. Opin. Drug Metab. Toxicol., 2009, 5(1), 15-27.
34. Afzelius, L.; Arnby, C.H.; Broo, A.; Carlsson, L.; Isaksson, C.; Jurva, U.; Kjellander, B.; Kolmodin, K.; Nilsson, K.; Raubacher, F. State-of-the-art tools for computational site of metabolism predictions: Comparative analysis, mechanistical insights, and future applications. Drug Metab. Rev., 2007, 39(1), 61-86.
35. De Graaf, C.; Pospisil, P.; Pos, W.; Folkers, G.; Vermeulen., N.P.E. Binding mode prediction of cytochrome p450 and thymidine kinase protein- ligand complexes by consideration of water and rescoring in automated docking. J. Med. Chem., 2005, 48(7), 2308-2318. (Pubitemid 40516425)
36. de Graaf, C.; Oostenbrink, C.; Keizers, P.H.J.; van der Wijst, T.; Jongejan, A.; Vermeulen, N.P.E. Catalytic site prediction and virtual screening of cytochrome P450 2D6 substrates by consideration of water and rescoring in automated docking. J. Med. Chem., 2006, 49(8), 2417-2430.
37. De Rienzo, F.; Fanelli, F.; Menziani, M.C.; De Benedetti, P.G. Theoretical investigation of substrate specificity for cytochromes P450 IA2, P450 IID6 and P450 IIIA4. J. Comput. Aided Mol. Des., 2000, 14(1), 93-116. (Pubitemid 30103825)
38. Wei, D.Q.; Wang, J.F.; Chen, C; Li, Y; Chou, K.C. Molecular modeling of two CYP2C19 SNPs and its implications for personalized drug design. Protein Pept. Lett., 2008, 15(1), 27-32. (Pubitemid 351206472)
39. Vasanthanathan, P; Hritz, J; Taboureau, O; Olsen, L; J rgensen, FS; Vermeulen, NPE; Oostenbrink, C. Virtual screening and prediction of site of metabolism for cytochrome P450 1A2 ligands. J. Chem. Inf. Model, 2009, 49(1), 43-52.
40. Locuson, C.W.; Gannett, P.M.; Ayscue, R.; Tracy, T.S. Use of simple docking methods to screen a virtual library for heteroactivators of cytochrome P450 2C9. J. Med. Chem., 2007, 50(6), 1158-1165. (Pubitemid 46496316)
41. Kirton, S.B.; Murray, C.W.; Verdonk, M.L.; Taylor, R.D. Prediction of binding modes for ligands in the cytochromes P450 and other heme-containing proteins. Proteins, 2005, 58(4), 836-844. (Pubitemid 40271248)
42. Jones, G.; Willett, P.; Glen, R.C.; Leach, A.R.; Taylor, R. Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol., 1997, 267(3), 727-748. (Pubitemid 27170693)
43. Friesner, R.A.; Banks, J.L.; Murphy, R.B.; Halgren, T.A.; Klicic, J.J.; Mainz, D.T.; Repasky, M.P.; Knoll, E.H.; Shelley, M.; Perry, J.K. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem., 2004, 47(7), 1739-1749. (Pubitemid 38380917)
44. Corbeil, C.R.; Englebienne, P.; Moitessier, N. Docking ligands into flexible and solvated macromolecules. 1. Development and validation of FITTED 1.0. J. Chem. Inf. Model., 2007, 47(2), 435-449. (Pubitemid 46615946)
45. Wang, J. F.; Zhang, C. C.; Wei, D. Q. Docking and molecular dynamics studies on CYP2D6. Chin. Sci.. Bull., 2010, 55(18), 1877-1880.
46. Ito, Y.; Kondo, H.; Goldfarb, P.S.; Lewis, D.F.V. Analysis of CYP2D6 substrate interactions by computational methods. J. Mol. Graph. Model., 2008, 26(6), 947-956. (Pubitemid 350298014)
47. Wang, J.F.; Wei, D.Q.; Li, L; Zheng, S.Y.; Li, Y.X.; Chou, K.C. 3D structure modeling of cytochrome P450 2C19 and its implication for personalized drug design. Biochem. Biophys. Res. Commun., 2007, 355(2), 513-519. (Pubitemid 46282658)
48. Wang, J.F.; Yan, J.Y.; Wei, D.Q.; Chou, K.C. Binding of CYP2C9 with diverse drugs and its implications for metabolic mechanism. Med. Chem., 2009, 5(3), 263-270.
49. Harris, D. L.; Park, J. Y.; Gruenke, L.; Waskell, L. Theoretical study of the ligand-CYP2B4 complexes: Effect of structure on binding free energies and heme spin state. Proteins, 2004, 55(4), 895-914. (Pubitemid 38702949)
50. Shaik, S.; Cohen, S.; Wang, Y.; Chen, H.; Kumar, D.; Thiel, W. P450 Enzymes: Their structure, reactivity, and selectivity-modeled by QM/MM. Chem. Rev., 2010, 110(2), 949-1017.
51. Bathelt, C.M.; Mulholland, A.J.; Harvey, J.N. QM/MM modeling of benzene hydroxylation in human cytochrome P450 2C9. J Phys Chem. A, 2008, 112(50), 13149-13156.
52. Denisov, I.G.; Makris, T.M.; Sligar, S.G.; Schlichting, I. Structure and chemistry of cytochrome P450. Chem. Rev., 2005, 105(6), 2253-2278.
53. Fishelovitch, D.; Hazan, C.; Hirao, H.; Wolfson, H.J.; Nussinov, R.; Shaik, S. QM/MM study of the active species of the human cytochrome p450 3A4, and the influence thereof of the multiple substrate binding. J Phys. Chem. B., 2007, 111(49), 13822-13832.
54. Park, J.Y.; Harris, D. Construction and assessment of models of CYP2E1: predictions of metabolism from docking, molecular dynamics, and density functional theoretical calculations. J. Med. Chem., 2003, 46(9), 1645-1660. (Pubitemid 36444218)
55. Lewis, D.F.V. On the recognition of mammalian microsomal cytochrome P450 substrates and their characteristics:Towards the prediction of human p450 substrate specificity and metabolism. Biochem. Pharmacol.., 2000, 60(3), 293-306. (Pubitemid 30336626)
56. Wang, B.; Zhou, S.F. Synthetic and natural compounds that interact with human cytochrome P450 1A2 and implications in drug development. Curr. Med. Chem., 2009, 16(31), 4066-4218.
57. Freitas, R.F.; Bauab, R.L.; Montanari, C.A. Novel application of 2D and 3D-similarity searches to identify substrates among cytochrome P450 2C9, 2D6, and 3A4. J. Chem. Inf. Model, 2010, 50(1), 97-109.
58. de Groot, M.J.; Ekins, S. Pharmacophore modeling of cytochromes P450Advanced drug delivery reviews. Adv. Drug Deliv. Rev., 2002, 54(3), 367-383. (Pubitemid 34260959)
59. Ekins, S.; Iyer, M.; Krasowski, M.D.; Kharasch, E.D. Molecular characterization of CYP2B6 substrates. Curr. Drug Metab., 2008, 9(5), 363-373. (Pubitemid 352025191)
60. Vermeulen, N.P.E. Alternate Prediction of drug metabolism: the case of cytochrome P450 2D6. Curr. Top Med. Chem., 2003, 3(11), 1227-1239.
61. Sykes, M.J.; McKinnon, R.A.; Miners, J.O. Prediction of metabolism by cytochrome P450 2C9: Alignment and docking studies of a validated database of substrates. J. Med. Chem., 2008, 51(4), 780-791. (Pubitemid 351304687)
62. Singh, S.B.; Shen, L.Q.; Walker, M.J.; Sheridan, R.P. A model for predicting likely sites of CYP3A4-mediated metabolism on druglike molecules. J. Med. Chem., 2003, 46(8), 1330-1336. (Pubitemid 36512698)
63. Rydberg, P.; Gloriam, D.E.; Zaretzki, J.; Breneman, C.; Olsen, L. SMARTCyp: A 2D method for prediction of cytochrome P450-mediated drug metabolism. ACS Med. Chem. Lett., 2010, 1(3), 96-100.
64. de Groot, M.J.; Ackland, M.J.; Horne, V.A.; Alex, A.A.; Jones, B.C. A novel approach to predicting P450 mediated drug metabolism. CYP2D6 catalyzed N-dealkylation reactions and qualitative metabolite predictions using a combined protein and pharmacophore model for CYP2D6. J. Med. Chem., 1999, 42(20), 4062-4070. (Pubitemid 29483023)
65. Zamora, I.; Afzelius, L.; Crucianis, G. Predicting drug metabolism: a site of metabolism prediction tool applied to the cytochrome P450 2C9. J. Med. Chem., 2003, 46(12), 2313-2324. (Pubitemid 36637916)
66. Zhou, D.; Afzelius, L.; Grimm, S.W.; Andersson, T.B.; Zauhar, R.J.; Zamora, I. Comparison of methods for the prediction of the metabolic sites for CYP3A4-mediated metabolic reactions. Drug Metab. Dispos., 2006, 34(6), 976.
67. Cruciani, G.; Carosati, E.; De Boeck, B.; Ethirajulu, K.; Mackie, C.; Howe, T.; Vianello, R. MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist. J. Med. Chem., 2005, 48(22), 6970-6979. (Pubitemid 41533118)
68. de Groot, MJ; Ackland, MJ; Horne, VA; Alex, AA; Jones, BC. Novel approach to predicting P450-mediated drug metabolism: development of a combined protein and pharmacophore model for CYP2D6. J. Med. Chem., 1999, 42(9), 1515-1524. (Pubitemid 29226723)
69. Oh, W.S.; Kim, D.N.; Jung, J.; Cho, K.H.; No, K.T. New combined model for the prediction of regioselectivity in cytochrome P450/3A4 mediated metabolism. J. Chem. Inf. Model., 2008, 48(3), 591-601. (Pubitemid 351535427)
70. Jung, J.; Kim, N.D.; Kim, S.Y.; Choi, I.; Cho, K.H.; Oh, W.S.; Kim, D.N.; No, K.T. Regioselectivity prediction of CYP1A2-mediated phase I metabolism. J. Chem. Inf. Model., 2008, 48(5), 1074-1080.
71. Klopman, G.; Dimayuga, M.; Talafous, J. META. 1. A program for the evaluation of metabolic transformation of chemicals. J. Chem. Inf. Comput. Sci., 1994, 34(6), 1320-1325.
72. Kulkarni, S.A.; Zhu, J.; Blechinger, S. In silico techniques for the study and prediction of xenobiotic metabolism: a review. Xenobiotica, 2005, 35(10-11), 955-973. (Pubitemid 43068041)
73. Greene, N.; Judson, P.N.; Langowski, J.J.; Marchant, CA. Knowledge-based expert systems for toxicity and metabolism prediction: DEREK. SAR QSAR Environ. Res., 1999, 10(2), 299-314.
74. Tarcsay, á; Kiss, R.; Keser, G.M. Site of metabolism prediction on cytochrome P450 2C9: a knowledge-based docking approach. J. Comput. Aided Mol. Des., 2010, 24(5), 399-408.
75. Smith, J.; Stein, V. SPORCalc: A development of a database analysis that provides putative metabolic enzyme reactions for ligand-based drug design. Comput. Biol. Chem., 2009, 33(2), 149-159.
76. Long, A.; Walker, J. D. Quantitative structure-activity relationships for predicting metabolism and modeling cytochrome P450 enzyme activities. Environ. Toxicol. Chem., 2003, 22(8), 1894-1899. (Pubitemid 37337313)
77. Arimoto, R. Computational models for predicting interactions with cytochrome p450 enzyme. Curr. Top Med. Chem., 2006, 6(15), 1609-1618. (Pubitemid 44313416)
78. Li, H.; Sun, J.; Fan, X.; Sui, X.; Zhang, L.; Wang, Y.; He, Z. Considerations and recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction. J. Comput. Aided Mol. Des., 2008, 22(11), 843-855.
79. Dudek, A.Z.; Arodz, T.; Galvez, J. Computational methods in developing quantitative structure-activity relationships (QSAR): a review. Comb. Chem. High Throughput Screen., 2006, 9(3), 213-228.
80. Livingstone, DJ. The characterization of chemical structures using molecular properties. A survey. J. Chem. Inf. Comput. Sci., 2000, 40(2), 195-209.
81. Zheng, M.; Luo, X.; Shen, Q.; Wang, Y.; Du, Y.; Zhu, W.; Jiang, H. Site of metabolism prediction for six biotransformations mediated by cytochromes P450. Bioinformatics, 2009, 25(10), 1251-1258.
82. Kontijevskis, A.; Komorowski, J.; Wikberg, J.E.S. Generalized proteochemometric model of multiple cytochrome P450 enzymes and their inhibitors. J. Chem. Inf. Model, 2008, 48(9), 1840-1850.
83. Butina, D.; Segall, M.D.; Frankcombe, K. Predicting ADME properties in silico: methods and models. Drug Discov. Today, 2002, 7(11), S83-S88. (Pubitemid 34603635)
84. Burton, J.; Ijjaali, I.; Petitet, F.; Michel, A.; Vercauteren, D. P. Virtual screening for cytochromes p450: successes of machine learning filters. Comb. Chem. High Throughput Screen., 2009, 12(4), 369-382.
85. Terfloth, L.; Bienfait, B.; Gasteiger, J. Ligand-based models for the isoform specificity of cytochrome P450 3A4, 2D6, and 2C9 substrates. J. Chem. Inf. Model., 2007, 47(4), 1688-1701. (Pubitemid 47210071)
86. Vasanthanathan, P.; Taboureau, O.; Oostenbrink, C.; Vermeulen, N. P. E.; Olsen, L.; J rgensen, F. S. Classification of cytochrome P450 1A2 inhibitors and noninhibitors by machine learning techniques. Drug Metab. Dispos., 2009, 37(3), 658-664.
87. Burton, J.; Danloy, E.; Vercauteren, D. P. Fragment-based prediction of cytochromes P450 2D6 and 1A2 inhibition by recursive partitioning. SAR QSAR Environ. Res., 2009, 20(3), 185-205.
88. Sheridan, R. P.; Korzekwa, K. R.; Torres, R. A.; Walker, M. J. Empirical regioselectivity models for human cytochromes P450 3A4, 2D6, and 2C9. J. Med. Chem., 2007, 50(14), 3173-3184. (Pubitemid 47065966)
89. Leong, M. K.; Chen, Y. M.; Chen, T. H. Prediction of human cytochrome P450 2B6-substrate interactions using hierarchical support vector regression approach. J. Comput. Chem., 2009, 30(12), 1899-1909.
90. Norinder, U.; Bergstroem, C. A. S. Prediction of ADMET properties. ChemMedChem, 2006, 1(9), 920-937. (Pubitemid 44448790)
91. Roy, P. P.; Paul, S.; Mitra, I.; Roy, K. On two novel parameters for validation of predictive QSAR models. Molecules, 2009, 14, 1660-1701.
92. Stjernschantz, E.; Vermeulen, N. P. E.; Oostenbrink, C. Computational prediction of drug binding and rationalisation of selectivity towards cytochromes P450Expert opinion on drug metabolism & toxicology. Expert Opin. Drug Metab. Toxicol., 2008, 4(5), 513-527. (Pubitemid 351890736)