In Silico Prediction of Drug-Drug Interactions Mediated by Cytochrome P450 Isoforms

Drug-drug interactions (DDIs) can cause drug toxicities, reduced pharmacological effects, and adverse drug reactions. Studies aiming to determine the possible DDIs for an investigational drug are part of the drug discovery and development process and include an assessment of the DDIs potential media...

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Main Authors: Alexander V. Dmitriev (Author), Anastassia V. Rudik (Author), Dmitry A. Karasev (Author), Pavel V. Pogodin (Author), Alexey A. Lagunin (Author), Dmitry A. Filimonov (Author), Vladimir V. Poroikov (Author)
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Published: MDPI AG, 2021-04-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Alexander V. Dmitriev  |e author 
700 1 0 |a Anastassia V. Rudik  |e author 
700 1 0 |a Dmitry A. Karasev  |e author 
700 1 0 |a Pavel V. Pogodin  |e author 
700 1 0 |a Alexey A. Lagunin  |e author 
700 1 0 |a Dmitry A. Filimonov  |e author 
700 1 0 |a Vladimir V. Poroikov  |e author 
245 0 0 |a In Silico Prediction of Drug-Drug Interactions Mediated by Cytochrome P450 Isoforms 
260 |b MDPI AG,   |c 2021-04-01T00:00:00Z. 
500 |a 10.3390/pharmaceutics13040538 
500 |a 1999-4923 
520 |a Drug-drug interactions (DDIs) can cause drug toxicities, reduced pharmacological effects, and adverse drug reactions. Studies aiming to determine the possible DDIs for an investigational drug are part of the drug discovery and development process and include an assessment of the DDIs potential mediated by inhibition or induction of the most important drug-metabolizing cytochrome P450 isoforms. Our study was dedicated to creating a computer model for prediction of the DDIs mediated by the seven most important P450 cytochromes: CYP1A2, CYP2B6, CYP2C19, CYP2C8, CYP2C9, CYP2D6, and CYP3A4. For the creation of structure-activity relationship (SAR) models that predict metabolism-mediated DDIs for pairs of molecules, we applied the Prediction of Activity Spectra for Substances (PASS) software and Pairs of Substances Multilevel Neighborhoods of Atoms (PoSMNA) descriptors calculated based on structural formulas. About 2500 records on DDIs mediated by these cytochromes were used as a training set. Prediction can be carried out both for known drugs and for new, not-yet-synthesized substances. The average accuracy of the prediction of DDIs mediated by various isoforms of cytochrome P450 estimated by leave-one-out cross-validation (LOO CV) procedures was about 0.92. The SAR models created are publicly available as a web resource and provide predictions of DDIs mediated by the most important cytochromes P450. 
546 |a EN 
690 |a drug interaction 
690 |a DDI 
690 |a computational prediction 
690 |a in silico 
690 |a QSAR 
690 |a drug metabolism 
690 |a Pharmacy and materia medica 
690 |a RS1-441 
655 7 |a article  |2 local 
786 0 |n Pharmaceutics, Vol 13, Iss 4, p 538 (2021) 
787 0 |n https://www.mdpi.com/1999-4923/13/4/538 
787 0 |n https://doaj.org/toc/1999-4923 
856 4 1 |u https://doaj.org/article/859be6f3d7664ecf89e76b3f8d5e9002  |z Connect to this object online.