ArticleJournal of agricultural and food chemistry2022
Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual Screening by Using a New Deep-Learning Classifier.
Article in Journal of agricultural and food chemistry, 2022. 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.
- WildFood science & nutrition · 2026Article
- Effects of Crocus sativus and its active constituents on cytochrome P450: a review.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- The future of pharmaceuticals: Artificial intelligence in drug discovery and development.Journal of pharmaceutical analysis · 2025Review
- Identification of Food-Derived Electrophilic Chalcones as Nrf2 Activators Using Comprehensive Virtual Screening Techniques.Antioxidants (Basel, Switzerland) · 2025Article
- Effects of Berberis vulgaris, and its active constituent berberine on cytochrome P450: a review.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Review
- Design and investigation of interactions of novel peptide conjugates of purine and pyrimidine derivatives with EGFR and its mutant T790M/L858R: an in silico and laboratory study.Molecular diversity · 2024Article
- Relative synonymous codon usage and codon pair analysis of depression associated genes.Scientific reports · 2024Article
- NiScientific reports · 2023Article
- Computer-Aided (In Silico) Modeling of Cytochrome P450-Mediated Food-Drug Interactions (FDI).International journal of molecular sciences · 2022Review
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
CYP3A4 is the main human enzyme responsible for phase I metabolism of dietary compounds, prescribed drugs and xenobiotics, steroid hormones, and bile acids. The inhibition of CYP3A4 activity might impair physiological mechanisms, including the endocrine system and response to drug admission. Here, we aimed to discover new CYP3A4 inhibitors from food and dietary supplements. A deep-learning model was built that classifies compounds as either an inhibitor or noninhibitor, with a high specificity of 0.997. We used this classifier to virtually screen ∼60,000 dietary compounds. Of the 115 identified potential inhibitors, only 31 were previously suggested. Many herbals, as predicted here, might cause impaired metabolism of drugs, and endogenous hormones and bile acids. Additionally, by applying Lipinski's rules of five, 17 compounds were also classified as potential intestine local inhibitors. New CYP3A4 inhibitors predicted by the model, bilobetin and picropodophyllin, were assayed in vitro.
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Registered trials
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