Computational investigation of imidazopyridine analogs as protein kinase B (Akt1) allosteric inhibitors by using 3D-QSAR, molecular docking and molecular dynamics simulations

Abstract

Protein kinase B (Akt1), which is a pivotal node in various cellular signaling pathways and up-regulated in many human tumors, has been regarded as a promising target to discover novel anticancer candidates. In this research, molecular modeling methods including molecular docking, three-dimensional quantitative structure–activity relationship (3 D-QSAR) and molecular dynamics (MD) simulation were applied on a series of Akt1 allosteric inhibitors to explore the structural requirements for their activities. Molecular docking study was performed to collect the binding mode of Akt1 with its inhibitors. Subsequently, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3 D-QSAR model. The Q² and R² values of the best CoMFA model were calculated as 0.612 and 0.992, while those for the best CoMSIA model were calculated as 0.595 and 0.991, which verified the accuracy of the models. Based on the contour maps, 15 novel Akt1 inhibitors were designed and all of them exhibited better predicted activities than the most active compound in the dataset. MD simulations were implemented to evaluate the stability of the complexes under physiological conditions and the results were congruent with molecular docking. Finally, binding free energy was calculated through molecular mechanics generalized born surface area (MM-GBSA) approach. The results were consistent with the bioactivities, which revealed that van der Waals and coulomb energy made the most contribution during the molecular binding process. In a word, our research provided a significant insight for further discovery of potent Akt1 allosteric inhibitors.

Graphical Abstract

Communicated by Ramaswamy H. Sarma

Keywords:

• Akt1
• 3D-QSAR
• molecular docking
• molecular dynamics simulations
• MM-GBSA

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was financially supported by National Natural Science Foundation of China (Grant No. 81872768, 81673323), LiaoNing Revitalization Talents Program (XLYC1807118) and Liaoning BaiQianWan Talents Program (2018).