Application of support vector machines to in silico prediction of cytochrome p450 enzyme substrates and inhibitors
Autor: | C W, Yap, Y, Xue, Z R, Li, Y Z, Chen |
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Rok vydání: | 2006 |
Předmět: |
chemistry.chemical_classification
biology In silico Cytochrome P450 Computational Biology General Medicine Computational biology Pharmacology Substrate Specificity chemistry.chemical_compound Enzyme Cytochrome p450 enzyme chemistry Cytochrome P-450 Enzyme System Drug Design Drug Discovery biology.protein Animals Cytochrome P-450 Enzyme Inhibitors Humans Cytochrome p450 isoenzymes Enzyme Inhibitors Xenobiotic Drug toxicity Drug metabolism |
Zdroj: | Current topics in medicinal chemistry. 6(15) |
ISSN: | 1568-0266 |
Popis: | Cytochrome P450 enzymes are responsible for phase I metabolism of the majority of drugs and xenobiotics. Identification of the substrates and inhibitors of these enzymes is important for the analysis of drug metabolism, prediction of drug-drug interactions and drug toxicity, and the design of drugs that modulate cytochrome P450 mediated metabolism. The substrates and inhibitors of these enzymes are structurally diverse. It is thus desirable to explore methods capable of predicting compounds of diverse structures without over-fitting. Support vector machine is an attractive method with these qualities, which has been employed for predicting the substrates and inhibitors of several cytochrome P450 isoenzymes as well as compounds of various other pharmacodynamic, pharmacokinetic, and toxicological properties. This article introduces the methodology, evaluates the performance, and discusses the underlying difficulties and future prospects of the application of support vector machines to in silico prediction of cytochrome P450 substrates and inhibitors. |
Databáze: | OpenAIRE |
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