Machine Learning Models to Predict Cytochrome P450 2B6 Inhibitors and Substrates-Reference-Cited by-同舟云学术

Machine Learning Models to Predict Cytochrome P450 2B6 Inhibitors and Substrates

Published:2023-07-12 Issue:8 Volume:36 Page:1332-1344
ISSN:0893-228X
Container-title:Chemical Research in Toxicology
language:en
Short-container-title:Chem. Res. Toxicol.

Author:

Li Longqiang¹,Lu Zhou¹,Liu Guixia¹^ORCID,Tang Yun¹^ORCID,Li Weihua¹^ORCID

Affiliation:

1. Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China

Funder

National Key Research and Development Program of China

Shanghai Municipal Education Commission

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Toxicology,General Medicine

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.3c00065

Reference61 articles.

1. Comprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries

2. CypReact: A Software Tool for in Silico Reactant Prediction for Human Cytochrome P450 Enzymes

3. Reactions and enzymes in the metabolism of drugs and other xenobiotics

4. Classification of Cytochrome P450 Inhibitors and Noninhibitors Using Combined Classifiers

5. Predictive Models for Cytochrome P450 Isozymes Based on Quantitative High Throughput Screening Data

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