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Quantitative Structure Activity Relationships in Drug Metabolism

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This review of 61 references delineates contemporary computation quantitative structure activity relationship (QSAR) approaches that have been used to elucidate the molecular features that influence the binding and metabolism of a compound by the major phase 1 and phase 2 metabolising enzymes; Cytochrome P450 (CYP) and UDPglucuronosyltransferase (UGT), respectively. Contemporary studies are applying 2D and 3D QSAR, pharmacophore approaches and nonlinear techniques (for example: recursive partitioning, neural networks and support vector machines) to model drug metabolism. Furthermore, this review highlights some of the challenges and opportunities for future research; the need to develop global models for CYP and UGT metabolism and to extend QSAR for other important metabolising enzymes.

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Keywords: 3D QSAR; ADME models; Bayesian neural networks; CYP 2B1; UGT isoform

Document Type: Research Article

Affiliations: Department of Physical & Metabolic Sciences, AstraZeneca R&D Charnwood, Bakewell Road,Loughborough, Leicestershire LE11 5RH, United Kingdom.

Publication date: 01 August 2006

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