title: Quantitative structure activity relationships in drug metabolism.
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 UDP-glucuronosyltransferase (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.
authors.affiliation: Department of Physical & Metabolic Sciences, AstraZeneca R&D Charnwood, Bakewell Road, Loughborough, Leicestershire LE11 5RH, UK. Kamaldeep.Chohan@ astrazeneca.com
authors.forename: Kamaldeep K
authors.initials: KK
authors.lastname: Chohan
authors.forename: Stuart W
authors.initials: SW
authors.lastname: Paine
authors.forename: Nigel J
authors.initials: NJ
authors.lastname: Waters
mesh_terms: D000818:Animals; D003577:Cytochrome P-450 Enzyme System / Q000378:metabolism*; D014453:Glucuronosyltransferase / Q000378:metabolism*; D006801:Humans; D008658:Inactivation, Metabolic; D021281:Quantitative Structure-Activity Relationship
chemical_list: D003577:Cytochrome P-450 Enzyme System; D014453:Glucuronosyltransferase