3D-QSAR and molecular docking studies on pyrazolopyrimidine derivatives as glycogen synthase kinase-3β inhibitors

Abstract

Glycogen synthase kinase-3 (GSK-3), a serine/threonine kinase, is a fascinating enzyme with diverse biological actions in intracellular signaling systems, making it an emerging target for diseases such as diabetes mellitus, cancer, chronic inflammation, bipolar disorders and Alzheimer's disease. It is important to inhibit GSK-3 selectively and the net effect of the GSK-3 inhibitors thus should be target specific, over other phylogenetically related kinases such as CDK-2. In the present work, we have carried out three-dimensional quantitative structure activity relationship (3D-QSAR) studies on novel class of pyrazolopyrimidine derivatives as GSK-3 inhibitors reported to have improved cellular activity. Docked conformation of the most active molecule in the series, which shows desirable interactions in the receptor, was taken as template for alignment of the molecules. Statistically significant CoMFA and CoMSIA models were generated using 49 molecules in training set. By applying leave-one-out (LOO) cross-validation study, r cv 2 values of 0.53 and 0.48 for CoMFA and CoMSIA, respectively and non-cross-validated ( r ncv 2 ) values of 0.98 and 0.92 were obtained for CoMFA and CoMSIA models, respectively. The predictive ability of CoMFA and CoMSIA models was determined using a test set of 12 molecules which gave predictive correlation coefficients ( r pred 2 ) of 0.47 and 0.48, respectively, indicating good predictive power. Based upon the information derived from CoMFA and CoMSIA contour maps, we have identified some key features that explain the observed variance in the activity and have been used to design new pyrazolopyrimidine derivatives. The designed molecules showed better binding affinity in terms of estimated docking scores with respect to the already reported systems; hence suggesting that newly designed molecules can be more potent and selective towards GSK-3β inhibition.