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Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual Screening by Using a New Deep-Learning Classifier
[Image: see text] 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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8895463/ https://www.ncbi.nlm.nih.gov/pubmed/35104412 http://dx.doi.org/10.1021/acs.jafc.2c00237 |
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author | Guttman, Yelena Kerem, Zohar |
author_facet | Guttman, Yelena Kerem, Zohar |
author_sort | Guttman, Yelena |
collection | PubMed |
description | [Image: see text] 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. |
format | Online Article Text |
id | pubmed-8895463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-88954632022-03-07 Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual Screening by Using a New Deep-Learning Classifier Guttman, Yelena Kerem, Zohar J Agric Food Chem [Image: see text] 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. American Chemical Society 2022-02-01 2022-03-02 /pmc/articles/PMC8895463/ /pubmed/35104412 http://dx.doi.org/10.1021/acs.jafc.2c00237 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Guttman, Yelena Kerem, Zohar Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual Screening by Using a New Deep-Learning Classifier |
title | Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual
Screening by Using a New Deep-Learning Classifier |
title_full | Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual
Screening by Using a New Deep-Learning Classifier |
title_fullStr | Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual
Screening by Using a New Deep-Learning Classifier |
title_full_unstemmed | Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual
Screening by Using a New Deep-Learning Classifier |
title_short | Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual
Screening by Using a New Deep-Learning Classifier |
title_sort | dietary inhibitors of cyp3a4 are revealed using virtual
screening by using a new deep-learning classifier |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8895463/ https://www.ncbi.nlm.nih.gov/pubmed/35104412 http://dx.doi.org/10.1021/acs.jafc.2c00237 |
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