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Virtual screening using binary kernel discrimination: analysis of pesticide data.

David J Wilton·Robert F Harrison·Peter Willett·John Delaney·Kevin Lawson·Graham Mullier
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Abstract

This paper discusses the use of binary kernel discrimination (BKD) for identifying potential active compounds in lead-discovery programs. BKD was compared with established virtual screening methods in a series of experiments using pesticide data from the Syngenta corporate database. It was found to be superior to methods based on similarity searching and substructural analysis but inferior to a support vector machine. Similar conclusions resulted from application of the methods to a pesticide data set for which categorical activity data were available.

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AlgorithmsComputer SimulationDatabases as TopicDrug DesignPesticidesStructure-Activity RelationshipJournal ArticleResearch Support, Non-U.S. Gov't

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David J Wilton, Robert F Harrison, Peter Willett, John Delaney, Kevin Lawson, Graham Mullier. Virtual screening using binary kernel discrimination: analysis of pesticide data.. https://doi.org/10.1021/ci050397w

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