title: Selecting compounds for focused screening using linear discriminant analysis and artificial neural networks.
abstract: Linear discriminant analysis and a committee of neural networks have been applied to recognise compounds that act at biological targets belonging to a specific gene family, protein kinases. The MDDR database was used to provide compounds targeted against this family and sets of randomly selected molecules. BCUT parameters were employed as input descriptors that encode structural properties and information relevant to ligand-receptor interactions. The technique was applied to purchasing compounds from external suppliers. These compounds achieved hit rates on a par with those achieved using known actives for related targets when tested for the ability to inhibit kinases at a single concentration. This approach is intended as one of a series of filters in the selection of screening candidates, compound purchases and the application of synthetic priorities to combinatorial libraries.
authors.affiliation: Centre for Molecular Design, IBBS, University of Portsmouth, King Henry Building, King Henry I St., Portsmouth PO1 2DY, UK. martyn.ford@port.ac.uk
authors.forename: M G
authors.initials: MG
authors.lastname: Ford
authors.forename: W R
authors.initials: WR
authors.lastname: Pitt
authors.forename: D C
authors.initials: DC
authors.lastname: Whitley
mesh_terms: D016208:Databases, Factual; D016002:Discriminant Analysis; D015195:Drug Design; D008024:Ligands; D016571:Neural Networks, Computer; D047428:Protein Kinase Inhibitors / Q000737:chemistry* / Q000378:metabolism
chemical_list: D008024:Ligands; D047428:Protein Kinase Inhibitors