ArticlePharmaceutics2021
In Silico Prediction of Drug-Drug Interactions Mediated by Cytochrome P450 Isoforms.
Article in Pharmaceutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 26 citations in OpenAlex.
- Computational Prediction of the Severity of Adverse Drug Reactions Caused by Drug-Drug Interactions.Pharmaceuticals (Basel, Switzerland) · 2026Article
- CLC-Pred Synergy: Web Application for Predicting Pairwise Drug Combinations with Synergistic Activity Against NCI60 Cancer Cell Lines.International journal of molecular sciences · 2026Article
- Integrating state-space modeling, parameter estimation, deep learning, and docking techniques in drug repurposing: a case study on COVID-19 cytokine storm.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Design, Synthesis, Biological Evaluation, and In Silico Studies of Novel Multitarget Cinnamic Acid Hybrids.Molecules (Basel, Switzerland) · 2025Article
- Delineating CYP2C19-mediated Interactions: Network Pharmacology Investigation of Ilaprazole and ClopidogrelCurrent drug discovery technologies · 2025Article
- Oxidative Stress Induced by Antivirals: Implications for Adverse Outcomes During Pregnancy and in Newborns.Antioxidants (Basel, Switzerland) · 2024Review
- Utility of sustainable ratio derivative spectrophotometry for the concurrent assay of synergistic repurposed drugs for COVID-19 infections; Insilico pharmacokinetics proof.BMC chemistry · 2024Article
- Computational drug-drug interaction prediction mediated by CYP450 isoforms of Ilaprazole coadministered with clopidogrel.Future science OA · 2024Article
- DoE-assisted HPLC method development and validation of enzalutamide and repaglinide in rat plasma.Bioanalysis · 2024Article
- Machine learning to predict metabolic drug interactions related to cytochrome P450 isozymes.Journal of cheminformatics · 2022Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.