Quantitative Structure Activity Relationships in Drug Metabolism

Title: Quantitative Structure Activity Relationships in Drug Metabolism

Volume: 6 Issue: 15

Author(s): Kamaldeep K. Chohan, Stuart W. Paine and Nigel J. Waters

Affiliation:

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

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.

Cite this article as:

Chohan K. Kamaldeep, Paine W. Stuart and Waters J. Nigel, Quantitative Structure Activity Relationships in Drug Metabolism, Current Topics in Medicinal Chemistry 2006; 6 (15) . https://dx.doi.org/10.2174/156802606778108960