Lead Optimization Using Matched Molecular Pairs: Inclusion of Contextual Information for Enhanced Prediction of hERG Inhibition, Solubility, and Lipophilicity

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• 作者：George Papadatos ; Muhammad Alkarouri ; Valerie J. Gillet ; Peter Willett ; Visakan Kadirkamanathan ; Christopher N. Luscombe ; Gianpaolo Bravi ; Nicola J. Richmond ; Stephen D. Pickett ; Jameed Hussain ; John M
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2010
• 出版时间：October 25, 2010
• 年：2010
• 卷：50
• 期：10
• 页码：1872-1886
• 全文大小：685K
• 年卷期：v.50,no.10(October 25, 2010)
• ISSN：1549-960X

文摘

Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the effect of a substructural transformation on a molecular property is independent of the context (i.e., the local structural environment in which that transformation occurs). Experiments with large sets of hERG, solubility, and lipophilicity data demonstrate that the inclusion of contextual information can enhance the predictive power of MMP analyses, with significant trends (both positive and negative) being identified that are not apparent when using conventional, context-independent approaches.