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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MDPI AG
2021-04-01
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| Series: | Pharmaceutics |
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| Online Access: | https://www.mdpi.com/1999-4923/13/4/538 |
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| author | Alexander V. Dmitriev Anastassia V. Rudik Dmitry A. Karasev Pavel V. Pogodin Alexey A. Lagunin Dmitry A. Filimonov Vladimir V. Poroikov |
| author_facet | Alexander V. Dmitriev Anastassia V. Rudik Dmitry A. Karasev Pavel V. Pogodin Alexey A. Lagunin Dmitry A. Filimonov Vladimir V. Poroikov |
| author_sort | Alexander V. Dmitriev |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T12:23:19Z |
| format | Article |
| id | doaj.art-859be6f3d7664ecf89e76b3f8d5e9002 |
| institution | Directory Open Access Journal |
| issn | 1999-4923 |
| language | English |
| last_indexed | 2024-03-10T12:23:19Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Pharmaceutics |
| spelling | doaj.art-859be6f3d7664ecf89e76b3f8d5e90022023-11-21T15:17:49ZengMDPI AGPharmaceutics1999-49232021-04-0113453810.3390/pharmaceutics13040538In Silico Prediction of Drug–Drug Interactions Mediated by Cytochrome P450 IsoformsAlexander V. Dmitriev0Anastassia V. Rudik1Dmitry A. Karasev2Pavel V. Pogodin3Alexey A. Lagunin4Dmitry A. Filimonov5Vladimir V. Poroikov6Laboratory of Structure-Function Based Drug Design, Department of Bioinformatics, Institute of Biomedical Chemistry, Pogodinskaya Str. 10, bldg. 8, 119121 Moscow, RussiaLaboratory of Structure-Function Based Drug Design, Department of Bioinformatics, Institute of Biomedical Chemistry, Pogodinskaya Str. 10, bldg. 8, 119121 Moscow, RussiaLaboratory of Structure-Function Based Drug Design, Department of Bioinformatics, Institute of Biomedical Chemistry, Pogodinskaya Str. 10, bldg. 8, 119121 Moscow, RussiaLaboratory of Structure-Function Based Drug Design, Department of Bioinformatics, Institute of Biomedical Chemistry, Pogodinskaya Str. 10, bldg. 8, 119121 Moscow, RussiaLaboratory of Structure-Function Based Drug Design, Department of Bioinformatics, Institute of Biomedical Chemistry, Pogodinskaya Str. 10, bldg. 8, 119121 Moscow, RussiaLaboratory of Structure-Function Based Drug Design, Department of Bioinformatics, Institute of Biomedical Chemistry, Pogodinskaya Str. 10, bldg. 8, 119121 Moscow, RussiaLaboratory of Structure-Function Based Drug Design, Department of Bioinformatics, Institute of Biomedical Chemistry, Pogodinskaya Str. 10, bldg. 8, 119121 Moscow, RussiaDrug–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.https://www.mdpi.com/1999-4923/13/4/538drug interactionDDIcomputational predictionin silicoQSARdrug metabolism |
| spellingShingle | Alexander V. Dmitriev Anastassia V. Rudik Dmitry A. Karasev Pavel V. Pogodin Alexey A. Lagunin Dmitry A. Filimonov Vladimir V. Poroikov In Silico Prediction of Drug–Drug Interactions Mediated by Cytochrome P450 Isoforms Pharmaceutics drug interaction DDI computational prediction in silico QSAR drug metabolism |
| title | In Silico Prediction of Drug–Drug Interactions Mediated by Cytochrome P450 Isoforms |
| title_full | In Silico Prediction of Drug–Drug Interactions Mediated by Cytochrome P450 Isoforms |
| title_fullStr | In Silico Prediction of Drug–Drug Interactions Mediated by Cytochrome P450 Isoforms |
| title_full_unstemmed | In Silico Prediction of Drug–Drug Interactions Mediated by Cytochrome P450 Isoforms |
| title_short | In Silico Prediction of Drug–Drug Interactions Mediated by Cytochrome P450 Isoforms |
| title_sort | in silico prediction of drug drug interactions mediated by cytochrome p450 isoforms |
| topic | drug interaction DDI computational prediction in silico QSAR drug metabolism |
| url | https://www.mdpi.com/1999-4923/13/4/538 |
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