The discovery of potential tumor necrosis factor alpha converting enzyme inhibitors via implementation of K Nearest Neighbor QSAR analysis

Tumor necrosis factor-alpha converting enzyme (TACE) is considered as a pro-inflammatory cytokine which catalyzes the formation of TNF-α from membrane bound TNF-α precursor protein. It has important role in various pathological diseases such as inflammation, anorexia, rheumatoid arthritis, cancer and viral replication. Despite the reporting of a variety of TACE inhibitors of diverse chemical scaffolds whether peptide, peptide-like compounds or others, the bioavailability and pharmacokinetic problems are reflected strongly on its clinical effectiveness. In this effort we employed a novel combination of k-nearest neighbor QSAR modeling to select the best critical ligand-TACE contacts capable of elucidation of TACE inhibitory bioactivity among a long list of inhibitors. The recurrence of one valid pharmacophore hypothesis among the successful models emerged the pharmacophore to be used as 3D search queries to screen the National Cancer Institute's structural database for new TACE inhibitors. Eight potent TACE inhibitors were discovered with inhibition percentage exceeding 50% at 100 μM inhibitor concentration.