Computational modelling strategies in exploring triazolopyridazine PIM1 kinase inhibitors as anticancer agents.

Abstract

PIM (Proviral Integration site for Moloney Murine Leukemia virus) kinases are members of the class of kinase family serine/ threonine kinases, which play a crucial role in cancer development. As there is no drug in the market against PIM-1, kinase has transpired as a budding and captivating target for discovering new anticancer agents targeting PIM-1 kinase. The current research pondered the development of new PIM-1 kinase inhibitors by applying a ligand-based and structure-based drug discovery approach involving 3D QSAR, molecular docking, and dynamics simulation. In this study, association allying the structural properties and biological activity was undertaken using 3D-QSAR analysis. The 3D-QSAR model was generated with the help of 35 compounds from which the best model manifested an appreciated cross-validation coefficient (q2) of 0.8866 and conventional correlation coefficient (r2) of 0.9298, respectively and predicted correlation coefficient (r2 pred) was obtained as 0.7878. The molecular docking analysis demonstrated that the analogs under analysis occupied the active site of PIM-1 kinase receptor and interactions with Lys67 in the catalytic region, Asp186 in the DFG motif, and Glu171 were noticed with numerous compounds. Furthermore, the molecular dynamics simulation study stated that the ligand portrayed the strong conformational stability within the active site of PIM-1 kinase protein, forming of two hydrogen bonds until 100 ns, respectively. Overall outcomes of the study revealed that applications of the ligand-based drug discovery approach and structure-based drug discovery strategy conceivably applied to discovering new PIM-1 kinase inhibitors as anticancer agents.