Absorption, distribution, metabolism, excretion, and toxicity evaluation in drug discovery. 14. Prediction of human pregnane X receptor activators by using naive bayesian classification technique

Chemical Research in Toxicology

Volumn 28, Issue 1, 2015, Pages 116-125

  Shi, Huali ^a   Tian, Sheng ^a   Li, Youyong ^a   Li, Dan ^b   Yu, Huidong ^c   Zhen, Xuechu ^a   Hou, Tingjun ^a,b  

^a SOOCHOW UNIVERSITY   (China)

^b ZHEJIANG UNIVERSITY   (China)

^c Pharmatech Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALKANE DERIVATIVE; CELL NUCLEUS RECEPTOR; CHEMICAL COMPOUND; HALOGEN; HORMONE RECEPTOR STIMULATING AGENT; NITROGEN; PREGNANE X RECEPTOR; PREGNANE X RECEPTOR ACTIVATOR; UNCLASSIFIED DRUG; STEROID RECEPTOR;

ACCURACY; ARTICLE; BAYES THEOREM; CLASSIFICATION; DRUG ABSORPTION; DRUG DESIGN; DRUG DISTRIBUTION; DRUG EXCRETION; DRUG METABOLISM; DRUG SCREENING; EVALUATION STUDY; HYDROPHOBICITY; PHYSICAL CHEMISTRY; PREDICTION; RECEPTOR UPREGULATION; RELIABILITY; TOXICITY TESTING; CHEMICAL STRUCTURE; COMPUTER SIMULATION; DRUG DEVELOPMENT; HUMAN; METABOLISM; PROCEDURES; QUANTITATIVE STRUCTURE ACTIVITY RELATION;

BAYES THEOREM; COMPUTER SIMULATION; DRUG DISCOVERY; HUMANS; MODELS, MOLECULAR; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RECEPTORS, STEROID;

EID: 84922445961     PISSN: 0893228X     EISSN: 15205010     Source Type: Journal    
DOI: 10.1021/tx500389q     Document Type: Article

References (56)

1. Chawla, A., Repa, J. J., Evans, R. M., and Mangelsdorf, D. J. (2001) Nuclear receptors and lipid physiology: Opening the X-files Science 294, 1866-1870
2. Dybdahl, M., Nikolov, N. G., Wedebye, E. B., Jónsdóttir, S. Ó., and Niemelä, J. R. (2012) QSAR model for human pregnane X receptor (PXR) binding: Screening of environmental chemicals and correlations with genotoxicity, endocrine disruption and teratogenicity Toxicol. Appl. Pharmacol. 262, 301-309
3. Lehmann, J. M., McKee, D. D., Watson, M. A., Willson, T. M., Moore, J. T., and Kliewer, S. A. (1998) The human orphan nuclear receptor PXR is activated by compounds that regulate CYP3A4 gene expression and cause drug interactions J. Clin. Invest. 102, 1016
4. Jones, S. A., Moore, L. B., Shenk, J. L., Wisely, G. B., Hamilton, G. A., McKee, D. D., Tomkinson, N. C., LeCluyse, E. L., Lambert, M. H., and Willson, T. M. (2000) The pregnane X receptor: A promiscuous xenobiotic receptor that has diverged during evolution Mol. Endocrinol. 14, 27-39
5. Kliewer, S. A., Goodwin, B., and Willson, T. M. (2002) The nuclear pregnane X receptor: A key regulator of xenobiotic metabolism Endocr. Rev. 23, 687-702
6. Ekins, S. (2004) Predicting undesirable drug interactions with promiscuous proteins in silico Drug Discovery Today 9, 276-285
7. Xie, W., Uppal, H., Saini, S. P., Mu, Y., Little, J. M., Radominska-Pandya, A., and Zemaitis, M. A. (2004) Orphan nuclear receptor-mediated xenobiotic regulation in drug metabolism Drug Discovery Today 9, 442-449
8. Ekins, S., Chang, C., Mani, S., Krasowski, M. D., Reschly, E. J., Iyer, M., Kholodovych, V., Ai, N., Welsh, W. J., Sinz, M., Swaan, P. W., Patel, R., and Bachmann, K. (2007) Human pregnane X receptor antagonists and agonists define molecular requirements for different binding sites Mol. Pharmacol. 72, 592-603
9. Moore, L. B., Goodwin, B., Jones, S. A., Wisely, G. B., Serabjit-Singh, C. J., Willson, T. M., Collins, J. L., and Kliewer, S. A. (2000) St. John's wort induces hepatic drug metabolism through activation of the pregnane X receptor Proc. Natl. Acad. Sci. U.S.A. 97, 7500-7502
10. Moore, J. T. and Kliewer, S. A. (2000) Use of the nuclear receptor PXR to predict drug interactions Toxicology 153, 1-10
11. Ekins, S. and Erickson, J. A. (2002) A pharmacophore for human pregnane X receptor ligands Drug Metab. Dispos. 30, 96-99
12. Zimniak, P., Radominska, A., Zimniak, M., and Lester, R. (1988) Formation of three types of glucuronides of 6-hydroxy bile acids by rat liver microsomes J. Lipid. Res. 29, 183-190
13. Xie, W., Radominska-Pandya, A., Shi, Y., Simon, C. M., Nelson, M. C., Ong, E. S., Waxman, D. J., and Evans, R. M. (2001) An essential role for nuclear receptors SXR/PXR in detoxification of cholestatic bile acids Proc. Natl. Acad. Sci. U.S.A. 98, 3375-3380
14. Sinz, M., Wallace, G., and Sahi, J. (2008) Current industrial practices in assessing CYP450 enzyme induction: preclinical and clinical AAPS J. 10, 391-400
15. Knight, A. W., Little, S., Houck, K., Dix, D., Judson, R., Richard, A., McCarroll, N., Akerman, G., Yang, C., and Birrell, L. (2009) Evaluation of high-throughput genotoxicity assays used in profiling the US EPA ToxCast chemicals Regul. Toxicol. Pharmacol. 55, 188-199
16. Gao, Y. D., Olson, S. H., Balkovec, J. M., Zhu, Y., Royo, I., Yabut, J., Evers, R., Tan, E. Y., Tang, W., Hartley, D. P., and Mosley, R. T. (2007) Attenuating pregnane X receptor (PXR) activation: A molecular modelling approach Xenobiotica 37, 124-138
17. Ung, C. Y., Li, H., Yap, C. W., and Chen, Y. Z. (2007) In Silico Prediction of Pregnane X Receptor Activators by Machine Learning Approache Mol. Pharmacol. 71, 158-168
18. Khandelwal, A., Krasowski, M. D., Reschly, E. J., Sinz, M. W., Swaan, P. W., and Ekins, S. (2008) Machine learning methods and docking for predicting human pregnane X receptor activation Chem. Res. Toxicol. 21, 1457-1467
19. Kortagere, S., Chekmarev, D., Welsh, W. J., and Ekins, S. (2009) Hybrid scoring and classification approaches to predict human pregnane X receptor activators Pharm. Res. 26, 1001-1011
20. Chen, C.-N., Shih, Y.-H., Ding, Y.-L., and Leong, M. K. (2011) Predicting Activation of the Promiscuous Human Pregnane X Receptor by Pharmacophore Ensemble/Support Vector Machine Approach Chem. Res. Toxicol. 24, 1765-1778
21. Pan, Y., Li, L., Kim, G., Ekins, S., Wang, H., and Swaan, P. W. (2011) Identification and validation of novel human pregnane X receptor activators among prescribed drugs via ligand-based virtual screening Drug Metab. Dispos. 39, 337-344
22. Chen, S., He, N., Chen, W., Sun, F., Li, L., Deng, R., and Hu, Y. (2014) Molecular insights into the promiscuous interaction of human pregnane X receptor (hPXR) with diverse environmental chemicals and drug compounds Chemosphere 96, 138-145
23. Lewis, D., Jacobs, M., Dickins, M., and Lake, B. (2002) Quantitative structure-activity relationships for inducers of cytochromes P450 and nuclear receptor ligands involved in P450 regulation within the CYP1, CYP2, CYP3 and CYP4 families Toxicology 176, 51-57
24. Fang, H., Tong, W., Welsh, W. J., and Sheehan, D. M. (2003) QSAR models in receptor-mediated effects: The nuclear receptor superfamily J. Mol. Struct.: THEOCHEM 622, 113-125
25. Mankowski, D. C. and Ekins, S. (2003) Prediction of human drug metabolizing enzyme induction Curr. Drug Metab. 4, 381-391
26. Schuster, D. and Langer, T. (2005) The identification of ligand features essential for PXR activation by pharmacophore modeling J. Chem. Inf. Model. 45, 431-439
27. Stanley, L. A., Horsburgh, B. C., Ross, J., Scheer, N., and Wolf, C. R. (2006) PXR and CAR: Nuclear receptors which play a pivotal role in drug disposition and chemical toxicity Drug Metab. Rev. 38, 515-597
28. Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., Shindyalov, I. N., and Bourne, P. E. (2000) The Protein Data Bank Nucleic Acids Res. 28, 235-242
29. Lemaire, G., Benod, C., Nahoum, V., Pillon, A., Boussioux, A.-M., Guichou, J.-F. O., Subra, G., Pascussi, J.-M., Bourguet, W., Chavanieu, A., and Balaguer, P. (2007) Discovery of a highly active ligand of human pregnane X receptor: a case study from pharmacophore Modeling and virtual screening to "in vivo" biological activity Mol. Pharmacol. 72, 572-581
30. Evans, R. M. (1988) The steroid and thyroid hormone receptor superfamily Science 240, 889-895
31. Lemaire, G., Mnif, W., Pascussi, J. M., Pillon, A., Rabenoelina, F., Fenet, H., Gomez, E., Casellas, C., Nicolas, J. C., Cavailles, V., Duchesne, M. J., and Balaguer, P. (2006) Identification of new human pregnane X receptor ligands among pesticides using a stable reporter cell system Toxicol. Sci. 91, 501-509
32. Sinz, M., Kim, S., Zhu, Z., Chen, T., Anthony, M., Dickinson, K., and Rodrigues, A. D. (2006) Evaluation of 170 xenobiotics as transactivators of human pregnane X receptor (hPXR) and correlation to known CYP3A4 drug interactions Curr. Drug Metab. 7, 375-388
33. Ekins, S., Kholodovych, V., Ai, N., Sinz, M., Gal, J., Gera, L., Welsh, W. J., Bachmann, K., and Mani, S. (2008) Computational discovery of novel low micromolar human pregnane X receptor antagonists Mol. Pharmacol. 74, 662-672
34. di Masi, A., De Marinis, E., Ascenzi, P., and Marino, M. (2009) Nuclear receptors CAR and PXR: Molecular, functional, and biomedical aspects Mol. Aspects Med. 30, 297-343
35. Matter, H., Anger, L. T., Giegerich, C., Guessregen, S., Hessler, G., and Baringhaus, K.-H. (2012) Development of in silico filters to predict activation of the pregnane X receptor (PXR) by structurally diverse drug-like molecules Bioorg. Med. Chem. 20, 5352-5365
36. Halgren, T. A. (1999) MMFF VI. MMFF94s option for energy minimization studies J. Comput. Chem. 20, 720-729
37. SYBYL molecular simulation package, Certara Inc., St. Louis, 2014, http://www.certara.com.
38. Ghose, A. K., Viswanadhan, V. N., and 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. A 102, 3762-3772
39. Tetko, I. V., Tanchuk, V. Y., Kasheva, T. N., and Villa, A. E. P. (2001) Estimation of aqueous solubility of chemical compounds using E-state indices J. Chem. Inf. Comput. Sci. 41, 1488-1493
40. Discovery Studio 3.1 Guide, Accelrys Inc., San Diego, 2012, http://www.accelrys.com.
41. Cruciani, C., Crivori, P., Carrupt, P. A., and Testa, B. (2000) Molecular fields in quantitative structure-permeation relationships: the VolSurf approach J. Mol. Struct.: THEOCHEM 503, 17-30
42. MOE molecular simulation package, Chemical Computing Group Inc., Montreal, Candada, 2010. http://www.chemcomp.com.
43. Ekins, S., Shimada, J., and Chang, C. (2006) Application of data mining approaches to drug delivery Adv. Drug Delivery Rev. 58, 1409-1430
44. Rogers, D., Brown, R. D., and Hahn, M. (2005) Using extended-connectivity fingerprints with Laplacian-modified Bayesian analysis in high-throughput screening follow-up J. Biomol. Screening 10, 682-686
45. Chen, L., Li, Y., Zhao, Q., Peng, H., and Hou, T. (2011) ADME evaluation in drug discovery. 10. Predictions of P-glycoprotein inhibitors using recursive partitioning and naive Bayesian classification techniques Mol. Pharmaceutics 8, 889-900
46. Cooper, J. A., Saracci, R., and Cole, P. (1979) Describing the Validity of Carcinogen Screening-Tests Br. J. Cancer 39, 87-89
47. Chen, L., Li, Y., Yu, H., Zhang, L., and Hou, T. (2012) Computational models for predicting substrates or inhibitors of P-glycoprotein Drug Discovery Today 17, 343-351
48. Tian, S., Wang, J., Li, Y., Xu, X., and Hou, T. (2012) Drug-likeness Analysis of Traditional Chinese Medicines: Prediction of Drug-likeness Using Machine Learning Approaches Mol. Pharmaceutics 9, 2875-2886
49. Wang, S., Li, Y., Wang, J., Chen, L., Zhang, L., Yu, H., and Hou, T. (2012) ADMET Evaluation in Drug Discovery. 12. Development of Binary Classification Models for Prediction of hERG Potassium Channel Blockage Mol. Pharmaceutics 9, 996-1010
50. Tian, S., Li, Y., Li, D., Xu, X., Wang, J., Zhang, Q., and Hou, T. (2013) Modeling Compound-Target Interaction Network of Traditional Chinese Medicines for Type II Diabetes Mellitus: Insight for Polypharmacology and Drug Design J. Chem. Inf. Model. 53, 1787-1803
51. Tian, S., Sun, H., Li, Y., Pan, P., Li, D., and Hou, T. (2013) Development and Evaluation of an Integrated Virtual Screening Strategy by Combining Molecular Docking and Pharmacophore Searching Based on Multiple Protein Structures J. Chem. Inf. Model. 53, 2743-2756
52. Wang, S., Li, Y., Xu, L., Li, D., and Hou, T. (2013) Recent Developments in Computational Prediction of hERG Blockage Curr. Top. Med. Chem. 13, 1317-1326
53. Hou, T. J., Wang, J. M., Zhang, W., and Xu, X. J. (2007) ADME evaluation in drug discovery. 6. Can oral bioavailability in humans be effectively predicted by simple molecular property-based rules? J. Chem. Inf. Model. 47, 460-463
54. Hou, T. J., Wang, J. M., Zhang, W., and Xu, X. J. (2007) ADME evaluation in drug discovery. 7. Prediction of oral absorption by correlation and classification J. Chem. Inf. Model. 47, 208-218
55. Hou, T. J., Wang, J. M., Zhang, W., Wang, W., and Xu, X. (2006) Recent advances in computational prediction of drug absorption and permeability in drug discovery Curr. Med. Chem. 13, 2653-2667
56. Hou, T. and Wang, J. (2008) Structure-ADME relationship: Still a long way to go? Expert Opin. Drug Metab. Toxicol. 4, 759-770