Selecting Screening Candidates for Kinase and G Protein-Coupled Receptor Targets Using Neural Networks

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• 作者：David T. Manallack ; Will R. Pitt ; Emanuela Gancia ; John G. Montana ; David J. Livingstone ; Martyn G. Ford ; and David C. Whitley
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2002
• 出版时间：September 2002
• 年：2002
• 卷：42
• 期：5
• 页码：1256 - 1262
• 全文大小：113K
• 年卷期：v.42,no.5(September 2002)
• ISSN：1549-960X

文摘

A series of neural networks has been trained, using consensus methods, to recognize compounds that act atbiological targets belonging to specific gene families. The MDDR database was used to provide compoundstargeted against gene families and sets of randomly selected molecules. BCUT parameters were employedas input descriptors that encode structural properties and information relevant to ligand-receptor interactions.In each case, the networks identified over 80% of the compounds targeting a gene family. The techniquewas applied to purchasing compounds from external suppliers, and results from screening against one genefamily demonstrated impressive abilities to predict the activity of the majority of known hit compounds.