%0 Journal Article
%T Target Profile Prediction and Practical Evaluation of a Biginelli-Type Dihydropyrimidine Compound Library
%A Petra Schneider
%A Katharina Stutz
%A Ladina Kasper
%A Sarah Haller
%A Michael Reutlinger
%A Felix Reisen
%A Tim Geppert
%A Gisbert Schneider
%J Pharmaceuticals
%D 2011
%I MDPI AG
%R 10.3390/ph4091236
%X We present a self-organizing map (SOM) approach to predicting macromolecular targets for combinatorial compound libraries. The aim was to study the usefulness of the SOM in combination with a topological pharmacophore representation (CATS) for selecting biologically active compounds from a virtual combinatorial compound collection, taking the multi-component Biginelli dihydropyrimidine reaction as an example. We synthesized a candidate compound from this library, for which the SOM model suggested inhibitory activity against cyclin-dependent kinase 2 (CDK2) and other kinases. The prediction was confirmed in an in vitro panel assay comprising 48 human kinases. We conclude that the computational technique may be used for ligand-based in silico pharmacology studies, off-target prediction, and drug re-purposing, thereby complementing receptor-based approaches.
%K combinatorial chemistry
%K drug design
%K in silico pharmacology
%K kinase inhibitor
%K multi-component reaction
%K self-organizing map
%U http://www.mdpi.com/1424-8247/4/9/1236