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Open AccessArticle

Target Profile Prediction and Practical Evaluation of a Biginelli-Type Dihydropyrimidine Compound Library

Swiss Federal Institute of Technology (ETH), Department of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences, Wolfgang-Pauli-Str. 10, CH-8093 Zurich, Switzerland
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These authors contributed equally to this work.
Pharmaceuticals 2011, 4(9), 1236-1247; https://doi.org/10.3390/ph4091236
Received: 26 August 2011 / Revised: 13 September 2011 / Accepted: 16 September 2011 / Published: 20 September 2011
(This article belongs to the Special Issue Advances in Drug Design)
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. View Full-Text
Keywords: combinatorial chemistry; drug design; in silico pharmacology; kinase inhibitor; multi-component reaction; self-organizing map combinatorial chemistry; drug design; in silico pharmacology; kinase inhibitor; multi-component reaction; self-organizing map
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Schneider, P.; Stutz, K.; Kasper, L.; Haller, S.; Reutlinger, M.; Reisen, F.; Geppert, T.; Schneider, G. Target Profile Prediction and Practical Evaluation of a Biginelli-Type Dihydropyrimidine Compound Library. Pharmaceuticals 2011, 4, 1236-1247.

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