Modeling of interactions between xenobiotics and cytochrome P450 (CYP) enzymes

Frontiers in Pharmacology

Volumn 6, Issue MAY, 2015, Pages

  Raunio, Hannu ^a  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

Author keywords

Biotransformations; CYP P450s; Docking studies; In silico modeling; QSAR; Xenobiotics

Indexed keywords

AMFEBUTAMONE; AMODIAQUINE; CAFFEINE; COUMARIN; CYCLOPHOSPHAMIDE; CYTOCHROME P450; CYTOCHROME P450 1A2; CYTOCHROME P450 2A6; CYTOCHROME P450 2B6; CYTOCHROME P450 2C19; CYTOCHROME P450 2C8; CYTOCHROME P450 2C9; CYTOCHROME P450 2D6; CYTOCHROME P450 2E1; CYTOCHROME P450 3A4; DICLOFENAC; EFAVIRENZ; ETHOXYRESORUFIN; FLURBIPROFEN; LIDOCAINE; MELATONIN; OMEPRAZOLE; PACLITAXEL; REPAGLINIDE; ROSIGLITAZONE; THEOPHYLLINE; TIZANIDINE; TOLBUTAMIDE; UNINDEXED DRUG; XENOBIOTIC AGENT;

CATALYSIS; CHEMICAL INTERACTION; COMPUTER MODEL; DRUG EXCRETION; DRUG METABOLISM; ENZYME INHIBITION; HUMAN; IN VITRO STUDY; LIGAND BINDING; MOLECULAR DOCKING; NONHUMAN; OUTCOME ASSESSMENT; PREDICTION; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REVIEW; RISK ASSESSMENT; TOXICITY TESTING;

EID: 84930650069     PISSN: None     EISSN: 16639812     Source Type: Journal    
DOI: 10.3389/fphar.2015.00123     Document Type: Review

References (109)

1. Adams S. 2010. Molecular similarity and xenobiotic metabolism. University of Cambridge, Cambridge.
2. Bessems JG, Loizou G, Krishnan K, Clewell HJ 3rd, Bernasconi C, Bois F, Coecke S, Collnot EM, Diembeck W, Farcal LR, Geraets L, Gundert-Remy U, Kramer N, Küsters G, Leite SB, Pelkonen OR, Schröder K, Testai E, Wilk-Zasadna I, and Zaldívar-Comenges JM. PBTK modelling platforms and parameter estimation tools to enable animal-free risk assessment: recommendations from a joint EPAA-EURL ECVAM ADME workshop. Regul Toxicol Pharmacol (2014) 68:119-139.
3. Boyer S, Arnby CH, Carlsson L, Smith J, Stein V, and Glen RC. Reaction site mapping of xenobiotic biotransformations. J Chem Inf Model (2007) 47:583-590.
4. Boyer S, and Zamora I. New methods in predictive metabolism. J Comput Aided Mol Des (2002) 16: 403-413.
5. Brändén G, Sjögren T, Schnecke V, and Xue Y. Structure-based ligand design to overcome CYP inhibition in drug discovery projects. Drug Discov Today (2014) 19:905-911.
6. Campagna-Slater V, Pottel J, Therrien E, Cantin LD, and Moitessier N. Development of a computational tool to rival experts in the prediction of sites of metabolism of xenobiotics by P450s. J Chem Inf Model (2012) 52:2471-2483.
7. Carosati E. Modelling cytochromes P450 binding modes to predict P450 inhibition, metabolic stability and isoform selectivity. Drug Discov Today Technol (2013) 10(1):e167-175.
8. Coecke S, Pelkonen O, Leite SB, Bernauer U, Bessems JG, Bois FY, Gundert-Remy U, Loizou G, Testai E, and Zaldívar JM. Toxicokinetics as a key to the integrated toxicity risk assessment based primarily on non-animal approaches. Toxicol In Vitro (2013) 27:1570-1577.
9. Cronin MTD, and Madden JC. In silico toxicology-Principles and applications. Cambridge, UK: RSC Publishing (2010). 669 p.
10. Cruciani G, Baroni M, Benedetti P, Goracci L, and Fortuna CG. Exposition and reactivity optimization to predict sites of metabolism in chemicals. Drug Discov Today Technol (2013) 10(1):e155-165.
11. Cruciani G, Carosati E, De Boeck B, Ethirajulu K, Mackie C, Howe T, and Vianello R. MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist. J Med Chem (2005) 48:6970-6979.
12. Cruciani G, Valeri A, Goracci L, Pellegrino RM, Buonerba F, and Baroni M. Flavin monooxygenase metabolism: why medicinal chemists should matter. J Med Chem (2014) 57:6183-6196.
13. Cumming JG, Davis AM, Muresan S, Haeberlein M, and Chen H. Chemical predictive modelling to improve compound quality. Nat Rev Drug Discov (2013) 12:948-962.
14. Danielson ML, Desai PV, Mohutsky MA, Wrighton SA, and Lill MA. Potentially increasing the metabolic stability of drug candidates via computational site of metabolism prediction by CYP2C9: The utility of incorporating protein flexibility via an ensemble of structures. Eur J Med Chem (2011) 46:3953-3963.
15. de Groot MJ, Ackland MJ, Horne VA, Alex AA, and Jones BC. Novel approach to predicting P450-mediated drug metabolism: development of a combined protein and pharmacophore model for CYP2D6. J Med Chem (1999a) 42:1515-24.
16. de Groot MJ, Ackland MJ, Horne VA, Alex AA, and Jones BC. 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 (1999b) 42:4062-4070.
17. de Groot MJ, Alex AA, and Jones BC. Development of a combined protein and pharmacophore model for cytochrome P450 2C9. J Med Chem (2002) 45:1983-1993.
18. de Groot MJ, Wakenhut F, Whitlock G, and Hyland R. Understanding CYP2D6 interactions. Drug Discov Today (2009) 14:964-972.
19. DeLisle RK, Otten J, and Rhodes S. In silico modeling of P450 substrates, inhibitors, activators, and inducers. Comb Chem High Throughput Screen (2011) 14:396-416.
20. Di L, Feng B, Goosen TC, Lai Y, Steyn SJ, Varma MV, and Obach RS. A perspective on the prediction of drug pharmacokinetics and disposition in drug research and development. Drug Metab Dispos (2013) 41:1975-1993.
21. Dong D, Wu B, Chow D, Hu M. Substrate selectivity of drug-metabolizing cytochrome P450s predicted from crystal structures and in silico modeling. Drug Metab Rev. 2012;44(2):192-208.
22. Fontana E, Dansette PM, and Poli SM. Cytochrome P450 enzymes mechanism based inhibitors: common sub-structures and reactivity. Curr Drug Metab (2005) 6:413-454.
23. Gonzalez FJ, Coughtrie M, and Tukey RH. "Drug metabolism". In: Brunton LL. Chabner B, Knollman B, editors. Goodman & Gilmans's The Pharmacological Basis of Therapeutics. 12th Edition, New York: McGraw-Hill (2011). p. 123-143.
24. Guengerich FP, and Munro AW. Unusual cytochrome P450 enzymes and reactions. J Biol Chem (2013) 288:17065-17073.
25. Hasegawa K, Koyama M, and Funatsu K. Quantitative prediction of regioselectivity toward cytochrome P450/3A4 using machine learning approaches. Mol Inf (2010) 29:243-249.
26. Houston JB. Prediction of human pharmacokinetics 645 in 2013 and beyond. Drug Metab Dispos (2013) 41:1973-1974.
27. Hritz J, de Ruiter A, and Oostenbrink C. Impact of plasticity and flexibility on docking results for cytochrome P450 2D6: a combined approach of molecular dynamics and ligand docking. J Med Chem (2008) 51:7469-7477.
28. Huang TW, Zaretzki J, Bergeron C, Bennett KP, and Breneman CM. DR-predictor: incorporating flexible docking with specialized electronic reactivity and machine learning techniques to predict CYP652 mediated sites of metabolism. J Chem Inf Model (2013) 53:3352-3366.
29. Höltje HD, Sippl W, Rognan D, and Folkers G. Molecular Modelling-Basic Principles and Applications. Heidelberg: Wiley-VCH (2003).
30. Johnson EF, and Stout CD. Structural diversity of eukaryotic membrane cytochrome P450s. J Biol Chem (2013) 288:17082-17090.
31. Jones JP, Mysinger M, and Korzekwa KR. Computational models for cytochrome P450: a predictive electronic model for aromatic oxidation and hydrogen atom abstraction. Drug Metab Dispos (2002) 30:7-12.
32. Kalgutkar AS, Gardner J, Obach RS, Shaffer CL, Callegar E, Henne KR, Mutlib AE, Dalvie DK, Lee JS, Nakai Y, O'Donnell JP, Boer J, and Harriman SP. A comprehensive listing of bioactivation pathways of organic functional groups. Curr Drug Metab (2005) 6, 161-225.
33. Kamel A, and Harriman S. Inhibition of cytochrome P450 enzymes and biochemical aspects of mechanism-based inactivation (MBI). Drug Discov Today Technol (2013) 10(1):e177-89.
34. Khojasteh SC, Prabhu S, Kenny JR, Halladay JS, and Lu AYH. Chemical inhibitors of cytochrome P450 isoforms in human liver microsomes: a re-evaluation of P450 isoform selectivity. Eur J Drug Metab Pharmacokinet (2011) 36:1-16.
35. Kingsley LJ, Wilson GL, Essex ME, and Lill MA. Combining structure-and ligand-based approaches to improve site of metabolism prediction in CYP2C9 substrates. Pharm Res (2014) Sep 11. [Epub ahead of print].
36. Kirchmair J, Williamson MJ, Afzal AM, Tyzack JD, Choy AP, Howlett A, Rydberg P, and Glen RC. FAst MEtabolizer (FAME): A rapid and accurate predictor of sites of metabolism in multiple species by endogenous enzymes. J Chem Inf Model (2013) 53:2896-2907.
37. Kirchmair J, Williamson MJ, Tyzack JD, Tan L, Bond PJ, Bender A, and Glen RC. Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms. J Chem Inf Model (2012) 52:617-648.
38. Korhonen LE, Rahnasto M, Mähönen NJ, Wittekindt C, Poso A, Juvonen RO, and Raunio H. Predictive three-dimensional quantitative structure-activity relationship of cytochrome P450 1A2 inhibitors. J Med Chem (2005) 48:3808-3815.
39. Korhonen LE, Turpeinen M, Rahnasto M, Wittekindt C, Poso A, Pelkonen O, Raunio H, and Juvonen RO. New potent and selective cytochrome P450 2B6 (CYP2B6) inhibitors based on three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis. Br J Pharmacol (2007) 150:932-942.
40. Korzekwa KR, Jones JP, and Gillette JR. Theoretical studies on cytochrome P-450 mediated hydroxylation: a predictive model for hydrogen atom abstractions. J Am Chem Soc (1990) 112:7042-7046.
41. Lewis DF, and Ito Y. Human CYPs involved in drug metabolism: structures, substrates and binding affinities. Expert Opin Drug Metab Toxicol (2010) 6:661-674.
42. Leyh TS, Cook I, and Wang T. Structure, dynamics and selectivity in the sulfotransferase family. Drug Metab Rev (2013) 45:4230-34.
43. Long A. Drug metabolism in silico-the knowledge-based expert system approach. Historical perspectives and current strategies. Drug Discov Today Technol (2013) 10(1):e147-53.
44. Lonsdale R, Hoyle S, Grey DT, Ridder L, and Mulholland AJ. Determinants of reactivity and selectivity in soluble epoxide hydrolase from quantum mechanics/molecular mechanics modeling. Biochemistry (2012) 51:1774-1786.
45. Martikainen LE, Rahnasto-Rilla M, Neshybova S, Lahtela-Kakkonen M, Raunio H, and Juvonen RO. Interactions of inhibitor molecules with the human CYP2E1 enzyme active site. Eur J Pharm Sci (2012) 47:996-1005.
46. Mo SL, Zhou ZW, Yang LP, Wei MQ, and Zhou SF. New insights into the structural features and functional relevance of human cytochrome P450 2C9. Part I. Curr Drug Metab (2009a) 10:1075-1126.
47. Mo SL, Zhou ZW, Yang LP, Wei MQ, and Zhou SF. New insights into the structural features and functional relevance of human cytochrome P450 2C9. Part II. Curr Drug Metab (2009b) 10:1127-1150.
48. Nicolotti O, Benfenati E, Carotti A, Gadaleta D, Gissi A, Mangiatordi GF, and Novellino E. REACH and in silico methods: an attractive opportunity for medicinal chemists. Drug Discov Today 2014 Jul 3. pii: S1359-6446(14)00269-4. doi: 10.1016/j.drudis.2014.06.027. [Epub ahead of print].
49. Niwa T, and Yamazaki H. Comparison of cytochrome P450 2C subfamily members in terms of drug oxidation rates and substrate inhibition. Curr Drug Metab (2012) 13:1145-1159.
50. Ogilvie BW, Zhang D, Li W, Rodrgues D, Gipson AE, Hopsapple J, Toren P, and Parkinson A. Glucuronidation converts gemfibrozil to a potent, metabolism-dependent inhibitor of CYP2C8: implications for drug-drug interactions. Drug Met Disp (2006) 34:191-197.
51. Orr ST, Ripp SL, Ballard TE, Henderson JL, Scott DO, Obach RS, Sun H, and Kalgutkar AS. Mechanism-based inactivation (MBI) of cytochrome P450 enzymes: structure-activity relationships and discovery strategies to mitigate drug-drug interaction risks. J Med Chem (2012) 55:4896-933.
52. Park BK, Boobis A, Clarke S, Goldring CE, Jones D, Kenna JG, Lambert C, Laverty HG, Naisbitt DJ, Nelson S, Nicoll-Griffith DA, Obach RS, Routledge P, Smith DA, Tweedie DJ, Vermeulen N, Williams DP, Wilson ID, and Baillie TA. Managing the challenge of 716 chemically reactive metabolites in drug development. Nat Rev Drug Discov (2011) 10:292-306.
53. Park JY, and 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) 46:1645-1660.
54. Pelkonen O, Turpeinen M, Hakkola J, Honkakoski P, Hukkanen J, and Raunio H. Inhibition and induction of human cytochrome P450 enzymes: current status. Arch Toxicol (2008) 82:667-715.
55. Pelkonen O, Tolonen A, Korjamo T, Turpeinen M, and Raunio H. From known knowns to known unknowns: predicting in vivo drug metabolites. Bioanalysis (2009) 1:393-414.
56. Pelkonen O, Turpeinen M, and Raunio H. In vivo-in vitro-in silico pharmacokinetic modelling in drug development: current status and future directions. Clin Pharmacokinet (2011) 50:483-491.
57. Peyret T, and Krishnan K. QSARs for PBPK modelling of environmental contaminants. SAR QSAR Environ Res (2011) 22:129-169.
58. Porubsky PR, Meneely KM, and Scott EE. Structures of human cytochrome P-450 2E1. Insights into the binding of inhibitors and both small molecular weight and fatty acid substrates. J Biol Chem (2008) 283:33698-33707.
59. Prueksaritanont T, Chu X, Gibson C, Cui D, Yee KL, Ballard J, Cabalu T, and Hochman J. Drug-drug interaction studies: regulatory guidance and an industry perspective. AAPS J (2013) 15:629-45.
60. Ravna AW, and Sylte I. Homology modeling of transporter proteins (carriers and ion channels). Methods Mol Biol (2012) 857:281-299.
61. Rahnasto M, Wittekindt C, Juvonen RO, Turpeinen M, Petsalo A, Pelkonen O, Poso A, Stahl G, Höltje HD, and Raunio H. Identification of inhibitors of the nicotine metabolising CYP2A6 enzyme-an in silico approach. Pharmacogenomics J (2008) 8:328-38.
62. Rahnasto MK, Raunio HA, Wittekindt C, Salminen KA, Leppänen J, Juvonen RO, Poso A, and Lahtela-Kakkonen MK. Identification of novel CYP2A6 inhibitors by virtual screening. Bioorg Med Chem (2011) 19:7186-7193.
63. Raunio H. In silico toxicology-non-testing methods. Front Pharmacol (2011);2:33.
64. Raunio H, and Rahnasto-Rilla M. CYP2A6: genetics, structure, regulation, and function. Drug Metabol Drug Interact (2012) 27:73-88.
65. Rendic S. Summary of information on human CYP enzymes: human P450 metabolism data. Drug Metab Rev (2002) 34:83-448.
66. Reynald RL, Sansen S, Stout CD, and Johnson EF. Structural characterization of human cytochrome P450 2C19: active site differences between P450s 2C8, 2C9, and 2C19. J Biol Chem (2012) 287:44581-44591.
67. Roncaglioni A, Toropov AA, Toropova AP, and Benfenati E. In silico methods to predict drug toxicity. Curr Opin Pharmacol (2013) 13:80280-80286.
68. Rostami-Hodjegan A. Physiologically based pharmacokinetics joined with in vitro-in vivo extrapolation of ADME: a marriage under the arch of systems pharmacology. Clin Pharmacol Ther (2012) 92:50-61.
69. Rowland M, Peck C, and Tucker G. Physiologically-based pharmacokinetics in drug development and regulatory science. Annu Rev Pharmacol Toxicol (2011) 51:45-73.
70. Rudik AV, Dmitriev AV, Lagunin AA, Filimonov DA, and Poroikov VV. Metabolism site prediction based on xenobiotic structural formulas and PASS prediction algorithm. J Chem Inf Model (2014) 54:498-507.
71. Rydberg P, Gloriam DE, Zaretzki J, Breneman C, and Olsen L. SMARTCyp: A 2D Method for Prediction of Cytochrome P450-Mediated Drug Metabolism. ACS Med Chem Lett (2010) 1:96-100.
72. Rydberg P, and Olsen L. Predicting drug metabolism by cytochrome P450 2C9: comparison with the 2D6 and 3A4 isoforms. ChemMedChem (2012) 7:1202-1209.
73. Rydberg P, and Olsen L. Ligand-Based Site of Metabolism Prediction for Cytochrome P450 2D6. ACS Med Chem Lett (2011) 3:69-73.
74. Rydberg P, Rostkowski M, Gloriam DE, and Olsen L. The contribution of atom accessibility to site of metabolism models for cytochromes P450. Mol Pharm (2013) 10:1216-1223.
75. Scholz S, Sela E, Blaha L, Braunbeck T, Galay-Burgos M, García-Franco M, Guinea J, Klüver N, Schirmer K, Tanneberger K, Tobor-Kaplon M, Witters H, Belanger S, Benfenati E, Creton S, Cronin MT, Eggen RI, Embry M, Ekman D, Gourmelon A, Halder M, Hardy B, Hartung T, Hubesch B, Jungmann D, Lampi MA, Lee L, Léonard M, Küster E, Lillicrap A, Luckenbach T, Murk AJ, Navas JM, Peijnenburg W, Repetto G, Salinas E, Schüürmann G, Spielmann H, Tollefsen KE, Walter-Rohde S, Whale G, Wheeler JR, and Winter MJ. A European perspective on alternatives to animal testing for environmental hazard identification and risk assessment. Regul Toxicol Pharmacol (2013) 67:506-530.
76. Sevior DK, Pelkonen O, and Ahokas JT. Hepatocytes: the powerhouse of biotransformation. Int J Biochem Cell Biol (2012) 44:257-261.
77. Sevrioukova IF, and Poulos TL. Understanding the mechanism of cytochrome P450 3A4: recent advances and remaining problems. Dalton Trans (2013) 42:3116-3126.
78. Shah MB, Pascual J, Zhang Q, Stout CD, and Halpert JR. Structures of cytochrome P450 2B6 bound to 4-benzylpyridine and 4-(4-nitrobenzyl)pyridine: insight into inhibitor binding and rearrangement of active site side chains. Mol Pharmacol (2011) 80:1047-1055.
79. Shaik S, Cohen S, Wang Y, Chen H, Kumar D, and Thiel W. P450 enzymes: their structure, reactivity, and selectivity-modeled by QM/MM calculations. Chem Rev (2010) 110:949-1017.
80. Sheridan RP, Korzekwa KR, Torres RA, and Walker MJ. Empirical regioselectivity models for human cytochromes P450 3A4, 2D6, and 2C9. J Med Chem (2007) 50:3173-3184.
81. Singh SB, Shen LQ, Walker MJ, and Sheridan RP. A 787 model for predicting likely sites of CYP3A4-mediated metabolism on drug-like molecules. J Med Chem (2003) 46:1330-1336.
82. Sorich MJ, Smith PA, Miners JO, Mackenzie PI, and McKinnon RA. Recent advances in the in silico modelling of UDP glucuronosyltransferase substrates. Curr Drug Metab (2008) 9:60-69.
83. Sridhar J, Liu J, Foroozesh M, and Stevens CL. Insights on cytochrome P450 enzymes and inhibitors obtained through QSAR studies. Molecules (2012) 17:9283-92305.
84. Stepan AF, Walker DP, Bauman J, Price DA, Baillie TA, Kalgutkar AS, and Aleo MD. Structural alert/reactive metabolite concepts as applied in medicinal chemistry to mitigate the risk of idiosyncratic drug toxicity: a perspective based on the critical examination of trends in the top 200 drugs marketed in the United States. Chem Res Toxicol (2011) 24:1345-1410.
85. Stjernschantz E, Vermeulen NPE, and Oostenbrink C. Computational prediction of drug binding and rationalisation of selectivity towards cytochromes P450. Expert Opin Drug Metab Toxicol (2008) 4:513-527.
86. Sullivan KM, Manuppello JR, and Willett CE. Building on a solid foundation: SAR and QSAR as a fundamental strategy to reduce animal testing. SAR QSAR Environ Res (2014) 25:357-65.
87. Tani N, Juvonen RO, Raunio H, Fashe M, Leppänen J, Zhao B, Tyndale RF, and Rahnasto-Rilla M. Rational design of novel CYP2A6 inhibitors. Bioorg Med Chem (2014) Oct 13;22(23):6655-6664. doi: 10.1016/j.bmc.2014.10.001. [Epub ahead of print].
88. Tarcsay A, Kiss R, and Keseru GM. Site of metabolism prediction on cytochrome P450 2C9: a knowledge-based docking approach. J Comput Aided Mol Des (2010) 24:399-408.
89. Testa B, Pedretti A, and Vistoli G. Reactions and enzymes in the metabolism of drugs and other xenobiotics. Drug Discov Today (2012) 17:549-560.
90. Tornio A, Filppula AM, Kailari O, Neuvonen M, Nyrönen TH, Tapaninen T, Neuvonen PJ, Niemi M, and Backman JT. Glucuronidation converts clopidogrel to a strong time-dependent inhibitor of CYP2C8: a phase II metabolite as a perpetrator of drug-drug interactions. Clin Pharm Ther (2014) 4:498-507.
91. Turpeinen M, and Zanger UM. Cytochrome P450 2B6: function, genetics, and clinical relevance. Drug Metabol Drug Interact (2012) 27:185-197.
92. Toshimoto K, Wakayama N, Kusama M, Maeda K, Sugiyama Y, and Akiyama Y. In silico prediction of major drug clearance pathways by support vector machines with feature-selected descriptors. Drug Metab Dispos (2014) 42:1811-1819.
93. Tyzack JD, Mussa HY, Williamson MJ, Kirchmair J, and Glen RC. Cytochrome P450 site of metabolism prediction from 2D topological fingerprints using GPU accelerated probabilistic classifiers. J Cheminform (2014) 6:29. doi: 10.1186/1758-2946-6-29. eCollection 2014.
94. Tyzack JD, Williamson MJ, Torella R, and Glen RC. Prediction of cytochrome P450 xenobiotic metabolism: tethered docking and reactivity derived from ligand molecular orbital analysis. J Chem Inf Model (2013) 53:1294-1305.
95. Vasanthanathan P, Hritz J, Taboureau O, Olsen L, Jørgensen FS, Vermeulen NP, and Oostenbrink C. Virtual screening and prediction of site of metabolism for cytochrome P450 1A2 ligands. J Chem Inf Model (2009) 49:43-52.
96. Vedani A, Dobler M, Hu Z, and Smieško M. OpenVirtualToxLab-A platform for generating and exchanging in silico toxicity data. Toxicol Lett (2014) Sep 17. pii: S0378-4274(14)01327-7. doi: 10.1016/j.toxlet.2014.09.004. [Epub ahead of print].
97. Wang B, Yang LP, Zhang XZ, Huang SQ, Bartlam M, and Zhou SF. New insights into the structural characteristics and functional relevance of the human cytochrome P450 2D6 enzyme. Drug Metab Rev (2009) 41:573-643.
98. Xiaoping L, Zhong F, and Tan X. Cytochrome P450 2C8 and drug metabolism. Curr Top Med Chem (2013) 13:2241-2253.
99. Yamazoe Y, Ito K, and Yoshinari K. Construction of a CYP2E1-template system for prediction of the metabolism on both site and preference order. Drug Metab Rev (2011) 43:409-439.
100. Yano JK, Hsu MH, Griffin KJ, Stout CD, and Johnson EF. Structures of human microsomal cytochrome P450 2A6 complexed with coumarin and methoxsalen. Nat Struct Mol Biol (2005) 12:822-823.
101. Zamora I, Afzelius L, and Cruciani G. Predicting drug metabolism: a site of metabolism prediction tool applied to the cytochrome P450 2C9. J Med Chem (2003) 46:2313-2324.
102. Zamora I, Fontaine F, Serra B, and Plasencia G. High-throughput, computer assisted, specific MetID. A revolution for drug discovery. Drug Discov Today Technol (2013) 10(1):e199-205.
103. Zaretzki J, Bergeron C, Rydberg P, Huang TW, Bennett KP, and Breneman CM. RS-predictor: a new tool for predicting sites of cytochrome P450-mediated metabolism applied to CYP 3A4. J Chem Inf Model (2011) 51:1667-1689.
104. Zaretzki J, Matlock M, and Swamidass SJ. XenoSite: accurately predicting CYP-mediated sites of metabolism with neural networks. J Chem Inf Model (2013) 53:3373-3383.
105. Zaretzki J, Rydberg P, Bergeron C, Bennett KP, Olsen L, and Breneman CM. RS-Predictor models augmented with SMARTCyp reactivities: robust metabolic regioselectivity predictions for nine CYP isozymes. J Chem Inf Model (2012) 52:1637-1659.
106. Zheng M, Luo X, Shen Q, Wang Y, Du Y, Zhu W, and Jiang H. Site of metabolism prediction for six biotransformations mediated by cytochromes P450. Bioinformatics (2009) 25:1251-1258.
107. Zhou SF. Drugs behave as substrates, inhibitors and inducers of human cytochrome P450 3A4. Curr Drug Metab (2008) 9:310-322.
108. Zhou SF, Wang B, Yang LP, and Liu JP. Structure, function, regulation and polymorphism and the clinical significance of human cytochrome P450 1A2. Drug Metab Rev (2010) 42:268-354.
109. Zientek MA, and Youdim K. Reaction phenotyping: advances in the experimental strategies used to characterize the contribution of drug-metabolizing enzymes. Drug Metab Dispos (2015) 43:163-181.