Abstract
A large number of computational methodologies have been used to predict, and thus help explain, the metabolism catalysed by the enzymes of the cytochrome P450 superfamily (P450s). A summary of the methodologies and resulting models is presented. This shows that investigations so far have focused on just a few of the many P450s, mainly those that are involved in drug metabolism. The models have evolved from simple comparisons of known substrates to more elaborate models requiring considerable computer power. These help to explain and, more importantly, predict the involvement of P450s in the metabolism of specific compounds.
Keywords: cytochrome p450, pharmacophore models, comparative models, homology models, drug metabolism
Current Topics in Medicinal Chemistry
Title: In Silico Methods for Predicting Ligand Binding Determinants of Cytochromes P450
Volume: 4 Issue: 16
Author(s): Marcel J. de Groot, Stewart B. Kirton and Michael J. Sutcliffe
Affiliation:
Keywords: cytochrome p450, pharmacophore models, comparative models, homology models, drug metabolism
Abstract: A large number of computational methodologies have been used to predict, and thus help explain, the metabolism catalysed by the enzymes of the cytochrome P450 superfamily (P450s). A summary of the methodologies and resulting models is presented. This shows that investigations so far have focused on just a few of the many P450s, mainly those that are involved in drug metabolism. The models have evolved from simple comparisons of known substrates to more elaborate models requiring considerable computer power. These help to explain and, more importantly, predict the involvement of P450s in the metabolism of specific compounds.
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Cite this article as:
de Groot J. Marcel, Kirton B. Stewart and Sutcliffe J. Michael, In Silico Methods for Predicting Ligand Binding Determinants of Cytochromes P450, Current Topics in Medicinal Chemistry 2004; 4 (16) . https://dx.doi.org/10.2174/1568026043387061
DOI https://dx.doi.org/10.2174/1568026043387061 |
Print ISSN 1568-0266 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4294 |
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