RESUMO
The large number of small organic compounds now available for drug-lead screening has led to numerous methods for classifying molecular similarity and diversity, the aim being to restore a balance between the quantity and drug-like quality of compounds in small-molecule libraries. Whereas structural and physicochemical attributes continue to be emphasized in compound selection for drug-lead screening, chemoproteomics--the use of biological information to guide chemistry--offers a highly efficient alternative to small-molecule characterization that can accelerate drug discovery in the post-genomic era.
Assuntos
Indústria Farmacêutica/tendências , Preparações Farmacêuticas/química , Proteoma , Bases de Dados Factuais , Desenho de FármacosRESUMO
We used protein affinity fingerprints to discover structurally novel inhibitors of cyclooxygenase-1 (COX-1) by screening a selected number of compounds, thus providing an alternative to extensive screening. From the affinity fingerprints of 19 known COX-1 inhibitors, a computational model for COX-1 inhibition was constructed and used to select candidate inhibitors from our compound library to be tested in the COX-1 assay. Subsequent refinement of the model by including affinity fingerprints of inactive compounds identified three molecules that were more potent than ibuprofen, a commonly used COX-1 inhibitor. These compounds are structurally distinct from those used to build the model and were discovered by testing only 62 library compounds. The discovery of these leads demonstrates the efficiency with which affinity fingerprints can identify novel bioactive chemotypes from known drugs.