700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ ReadersThis Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
Check point kinase 1 (Chk1) is an important protein in the G2 phase required by cancer cells to maintain cell cycle and to prevent cell death. Accordingly, inhibitors of this kinase should have potent anti-cancer properties. Pharmacophoric space of 190 Chk1 inhibitors using seven diverse sets of inhibitors was explored to identify high-quality pharmacophores. Subsequently, genetic algorithm-based quantitative structure activity relationship (GA-QSAR) analysis was employed to select the best possible combination of pharmacophoric models and physicochemical descriptors that can explain bioactivity variation within the training inhibitors. Three successful orthogonal pharmacophores emerged in the optimum QSAR
equation (r2 152 = 0.54, r2 LOO= 0.52, F= 20.27, r2 PRESS against 38 test inhibitors = 0.50). The QSAR-selected pharmacophores were validated using receiver operating characteristic (ROC) curve analyses. Moreover, the QSAR-selected pharmacophores describe binding interactions comparable to those seen in crystallographic structures of bound ligands within Chk1 binding pocket. The three pharmacophoric models and associated QSAR equation were applied to screen the national cancer institute (NCI) list of compounds. The captured hits were tested in vitro and new anti-Chk1 hits were discovered.
Check point kinase 1, Ligand based analysis, Serine-threonine kinase, Anticancer, Anti-inflammatory