Quantitative Structure Activity Relationships in Drug Metabolism

Kamaldeep   K.   Chohan; Stuart   W.   Paine; Nigel   J.   Waters

doi:10.2174/156802606778108960

Abstract

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.

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

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