Selecting screening candidates for kinase and G protein-coupled receptor targets using neural networks.
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.
Manallack
David T
DT
Celltech R&D Ltd, Granta Park, Great Abington, Cambridge, CB1 6GS, UK. David.Manallack@denovopharma.com
Pitt
Will R
WR
Gancia
Emanuela
E
Montana
John G
JG
Livingstone
David J
DJ
Ford
Martyn G
MG
Whitley
David C
DC
D016208:Databases, Factual; D004353:Drug Evaluation, Preclinical / Q000706:statistics & numerical data; D019204:GTP-Binding Proteins / Q000378:metabolism; D066298:In Vitro Techniques; D016571:Neural Networks, Computer; D010770:Phosphotransferases / Q000187:drug effects*; D011956:Receptors, Cell Surface / Q000187:drug effects*
D011956:Receptors, Cell Surface; D010770:Phosphotransferases; D019204:GTP-Binding Proteins