Computational Modelling Strategies for Exploring Triazolopyridazine PIM1 Kinase Inhibitors as Anticancer Agents

Abstract

Background: 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.

Aim: 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.

Methods: In this study, association allying the structural properties and biological activity was undertaken using 3DQSAR 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 the predicted correlation coefficient (r² _pred) was obtained as 0.7878.

Results: The molecular docking analysis demonstrated that the analogs under analysis occupied the active site of the PIM-1 kinase receptor and interactions with Lys67 in the catalytic region, Asp186 in the DFG motif, and Glu171 were noticed with numerous compounds.

Discussion: Furthermore, the molecular dynamics simulation study stated that the ligand portrayed strong conformational stability within the active site of PIM-1 kinase protein, forming two hydrogen bonds until 100 ns, respectively.

Conclusion: 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.

Keywords: 3D QSAR; PIM-1 kinase; PLS analysis; molecular docking; molecular dynamics; prostate cancer..