Multi-combined 3D-QSAR, docking molecular and ADMET prediction of 5-azaindazole derivatives as LRRK2 tyrosine kinase inhibitors.

Abstract

The enzyme Leucine-rich repeat kinase 2 (LRRK2) has become a target of therapeutic interest in Parkinson research.Athree-dimensional quantitative structure-activity relationships(3D-QSAR) study was performed on twenty six azaindazole derivatives as LRRK2 inhibitorsobtained using rigid body alignment (Distill). CoMFA and CoMSIA model shave achieved high activity-descriptor relationship efficiency of 96% and 93% as shown by the regression-coefficient (R2=0.961 and 0.933) and were found statistically significant with cross validated coefficient (Q2CV= 0.625 and 0.554), respectively.3D-QSAR models were externally validated by a test set of sixbioactive compounds showing satisfactory predicted correlation coefficient (R2pred) of 0.865 and 0.853 for CoMFA and CoMSIA models, respectively. Besides, Y-randomization test was also performed to ensure the robustness of the obtained3D-QSAR models. This study provides valuable clues to design new compounds against LRRK2. Docking studies suggested that the ligand (new designed compound C2) has more potential than the ligand of reference 4K4 and confirm the obtained results from 3D-QSAR studies. Furthermore, the newly designed compounds and ligand of reference 4K4 were analyzed for their ADMET properties and drug likeness. These results would be of great help in leading optimization for developing new anti-Parkinson drug. Communicated by Ramaswamy H. Sarma.