Selecting screening candidates for Kinase and G protein-coupled receptor targets using neural networks

D. Manallack, W. Pitt, E. Gancia, J. Montana, D. Livingstone, M. Ford, David Whitley

Research output: Contribution to journalArticlepeer-review

Abstract

A series of neural networks has been trained, using consensus methods, to recognize compounds that act at biological targets belonging to specific gene families. The MDDR database was used to provide compounds targeted against gene families and sets of randomly selected molecules. BCUT parameters were employed as 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 technique was applied to purchasing compounds from external suppliers, and results from screening against one gene family demonstrated impressive abilities to predict the activity of the majority of known hit compounds.
Original languageEnglish
Pages (from-to)1256-1262
Number of pages7
JournalJournal of Chemical Information and Computer Sciences
Volume42
Issue number5
DOIs
Publication statusPublished - 2002

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