Journal
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
Volume 22, Issue 6, Pages 507-517Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jmgm.2004.03.011
Keywords
UDP-glucuronosyltransferase; UGT; ADME; QSAR; QSMR; pharmacophore; metabolism; support vector machine; modelling
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Undesirable absorption, distribution, metabolism, excretion (ADME) properties are the cause of many drug development failures and this has led to the need to identify such problems earlier in the development process. this review highlights computational (in silico) approaches that have been used to identify the characteristics of ligands influencing molecular recognition and/or metabolism by the drug-metabolising. enzyme UDP-gucuronosyltransferase (UGT). Current studies applying pharmacophore elucidation, 2D-quantitative structure metabolism relationships (2D-QSMR), 3D-quantitative structure metabolism relationships (3D-QSMR), and non-linear pattern recognition techniques such as artificial neural networks and support vector machines for modelling metabolism by UGT are reported. An assessment of the utility of in silico approaches for the qualitative and quantitative prediction of drug glucuronidation parameters highlights the benefit of using multiple pharmacophores and also non-linear techniques for classification. Some of the challenges facing the development of generalisable models for predicting metabolism by UGT, including the need for screening of more diverse structures, are also outlined. (C) 2004 Elsevier Inc. All rights reserved.
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