Drug-drug interaction prediction using PASS

References

• C. Kennedy, L. Brewer, and D. William, Drug interactions, Medicine (Baltimore) 44 (2016), pp. 422–426. doi:10.1016/j.mpmed.2016.04.015.
   Google Scholar
• A.V. Lyubimov (ed.), Encyclopedia of Drug Metabolism and Interactions, John Wiley & Sons, Inc., Hoboken, NJ, 2012.
   Google Scholar
• A.V. Dmitriev, A.A. Lagunin, D.А. Karasev, A.V. Rudik, P.V. Pogodin, D.A. Filimonov, and V.V. Poroikov, Prediction of drug-drug interactions related to inhibition or induction of drug-metabolizing enzymes, Curr. Top. Med. Chem. 19 (2019), pp. 319–336. doi:10.2174/1568026619666190123160406.
   PubMed Web of Science ®Google Scholar
• C.W. Yap, Y. Xue, H. Li, Z.R. Li, C.Y. Ung, L.Y. Han, C.J. Zheng, Z.W. Cao, and Y.Z. Chen, Prediction of compounds with specific pharmacodynamic, pharmacokinetic or toxicological property by statistical learning methods, Mini Rev. Med. Chem. 6 (2006), pp. 449–459. doi:10.2174/138955706776361501.
   PubMed Web of Science ®Google Scholar
• S. Ekins, J.E. Polli, P.W. Swaan, and S.H. Wright, Computational modeling to accelerate the identification of substrates and inhibitors for transporters that affect drug disposition, Clin. Pharmacol. Ther. 92 (2012), pp. 661–665. doi:10.1038/clpt.2012.164.
   PubMed Web of Science ®Google Scholar
• Physiologically based pharmacokinetic analyses — format and content. Guidance for industry. URL: https://www.fda.gov/media/101469/download (Accessed July, 2019).
   Google Scholar
• A.V. Zakharov, A.A. Lagunin, D.A. Filimonov, and V.V. Poroikov, Quantitative prediction of antitarget interaction profiles for chemical compounds, Chem. Res. Toxicol. 25 (2012), pp. 2378–2385. doi:10.1021/tx300247r.
   PubMed Web of Science ®Google Scholar
• D.V. Ivashchenko, A.V. Rudik, A.A. Poloznikov, S.V. Nikulin, V.V. Smirnov, A.G. Tonevitsky, E.A. Bryun, and D.A. Sychev, Which cytochrome P450 metabolizes phenazepam? Step by step in silico, in vitro, and in vivo studies, Drug Metab. Pers. Ther. 33 (2018), pp. 65–73. doi:10.1515/dmpt-2017-0036.
   PubMedGoogle Scholar
• A.A. Lagunin, T.A. Gloriozova, A.V. Dmitriev, N.E. Volgina, and V.V. Poroikov, Computer evaluation of drug interactions with P-gGlycoprotein, Bull. Exp. Biol. Med. 154 (2013), pp. 521–524. doi:10.1007/s10517-013-1992-9.
   PubMed Web of Science ®Google Scholar
• Y. Borodina, A. Sadym, D. Filimonov, V. Blinova, A. Dmitriev, and V. Poroikov, Predicting biotransformation potential from molecular structure, J. Chem. Inf. Comput. Sci. 43 (2003), pp. 1636–1646. doi:10.1021/ci034078l.
   PubMedGoogle Scholar
• Y. Borodina, A. Rudik, D. Filimonov, N. Kharchevnikova, A. Dmitriev, V. Blinova, and V. Poroikov, A new statistical approach to predicting aromatic hydroxylation sites. Comparison with model-based approaches, J. Chem. Inf. Comput. Sci. 44 (2004), pp. 1998–2009. doi:10.1021/ci049834h.
   PubMedGoogle Scholar
• A.V. Rudik, A.V. Dmitriev, A.A. Lagunin, D.A. Filimonov, and V.V. Poroikov, Prediction of reacting atoms for the major biotransformation reactions of organic xenobiotics, J. Cheminform. 8 (2016), pp. 68. doi:10.1186/s13321-016-0183-x.
   PubMed Web of Science ®Google Scholar
• O. Tarasova, A. Rudik, A. Dmitriev, A. Lagunin, D. Filimonov, and V. Poroikov, QNA-based prediction of sites of metabolism, Molecules 22 (2017), pp. E2123. doi:10.3390/molecules22122123.
   PubMed Web of Science ®Google Scholar
• A. Rudik, A. Dmitriev, A. Lagunin, D. Filimonov, and V. Poroikov, SOMP: Web server for in silico prediction of sites of metabolism for drug-like compounds, Bioinformatics 31 (2015), pp. 2046–2048. doi:10.1093/bioinformatics/btv087.
   PubMed Web of Science ®Google Scholar
• A.V. Rudik, V.M. Bezhentsev, A.V. Dmitriev, D.S. Druzhilovskiy, A.A. Lagunin, D.A. Filimonov, and V.V. Poroikov, MetaTox: Web application for predicting structure and toxicity of xenobiotics’ metabolites, J. Chem. Inf. Model. 57 (2017), pp. 638–642. doi:10.1021/acs.jcim.7b00086.
   PubMed Web of Science ®Google Scholar
• A.V. Rudik, A.V. Dmitriev, V.M. Bezhentsev, A.A. Lagunin, D.A. Filimonov, and V.V. Poroikov, Prediction of metabolites of epoxidation reaction in MetaTox, SAR QSAR Environ. Res. 28 (2017), pp. 833–842. doi:10.1080/1062936X.2017.1399165.
   PubMed Web of Science ®Google Scholar
• A. Dmitriev, A. Rudik, D. Filimonov, A. Lagunin, P. Pogodin, V. Dubovskaja, V. Bezhentsev, S. Ivanov, D. Druzhilovsky, O. Tarasova, and V. Poroikov, Integral estimation of xenobiotics’ toxicity with regard to their metabolism in human organism, Pure Appl. Chem. 89 (2017). doi:10.1515/pac-2016-1205.
   Web of Science ®Google Scholar
• A.V. Zakharov, E.V. Varlamova, A.A. Lagunin, A.V. Dmitriev, E.N. Muratov, D. Fourches, V.E. Kuz’min, V.V. Poroikov, A. Tropsha, and M.C. Nicklaus, QSAR modeling and prediction of drug-drug interactions, Mol. Pharm. 13 (2016), pp. 545–556. doi:10.1021/acs.molpharmaceut.5b00762.
   PubMedGoogle Scholar
• P.D. Hansten, J.R. Horn, and T.K. Hazlet, ORCA: Operational classification of drug interactions, J. Am. Pharm. Assoc. (Wash) 41 (2001), pp. 161–165.
   PubMedGoogle Scholar
• P.D. Hansten and J.R. Horn (eds.), The Top 100 Drug Interactions: A Guide to Patient Management, Createspace Independent Pub, Scotts Valley, CA, 2017.
   Google Scholar
• J.H. Lee, S. Basith, M. Cui, B. Kim, and S. Choi, In silico prediction of multiple-category classification model for cytochrome P450 inhibitors and non-inhibitors using machine-learning method, SAR QSAR Environ. Res. 28 (2017), pp. 863–874. doi:10.1080/1062936X.2017.1399925.
   PubMed Web of Science ®Google Scholar
• D.S. Druzhilovskiy, A.V. Rudik, D.A. Filimonov, T.A. Gloriozova, A.A. Lagunin, A.V. Dmitriev, P.V. Pogodin, V.I. Dubovskaya, S.M. Ivanov, O.A. Tarasova, V.M. Bezhentsev, K.A. Murtazalieva, M.I. Semin, I.S. Maiorov, A.S. Gaur, G.N. Sastry, and V.V. Poroikov, Computational platform Way2Drug: From the prediction of biological activity to drug repurposing, Rus. Chem. Bull. 66 (2017), pp. 1832–1841. doi:10.1007/s11172-017-1954-x.
   Web of Science ®Google Scholar
• K.A. Murtazalieva, D.S. Druzhilovskiy, R.K. Goel, G.N. Sastry, and V.V. Poroikov, How good are publicly available web services that predict bioactivity profiles for drug repurposing? SAR QSAR Environ. Res. 28 (2017), pp. 843–862. doi:10.1080/1062936X.2017.1399448.
   PubMed Web of Science ®Google Scholar
• D. Filimonov, V. Poroikov, and Y.B.T. Gloriozova, Chemical similarity assessment through multilevel neighborhoods of atoms: Definition and comparison with the other descriptors, J. Chem. Inf. Comput. Sci. 39 (1999), pp. 666–670. doi:10.1021/ci980335o.
   Google Scholar
• V.V. Poroikov, D.A. Filimonov, Y.V. Borodina, A.A. Lagunin, and A. Kos, Robustness of biological activity spectra predicting by computer program PASS for noncongeneric sets of chemical compounds, J. Chem. Inf. Comput. Sci. 40 (2000), pp. 1349–1355.
   PubMedGoogle Scholar
• D.A. Filimonov and V.V. Poroikov, Probabilistic approach in activity prediction, in Chemoinformatics Approaches to Virtual Screening, A. Varnek and A.R. Tropsha, eds., RSC Publishing, Cambridge, UK, 2008, pp. 182–216.
   Google Scholar
• R.A. Masamrekh, A.V. Kuzikov, Y.I. Haurychenka, K.A. Shcherbakov, A.V. Veselovsky, D.A. Filimonov, A.V. Dmitriev, M.G. Zavialova, A.A. Gilep, T.V. Shkel, N.V. Strushkevich, S.A. Usanov, A.I. Archakov, and V.V. Shumyantseva, In vitro interactions of abiraterone, erythromycin and CYP3A4: Implications for drug-drug interactions, Fundam. Clin. Pharmacol. (2019), Epub ahead of print. doi: 10.1111/fcp.12497.
   PubMed Web of Science ®Google Scholar