Structure prediction of eukaryotic elongation factor-2 kinase and identification of the binding mechanisms of its inhibitors: homology modeling, molecular docking, and molecular dynamics simulation

Abstract

Protein kinases emerged as one of the most successful families of drug targets due to their increased activity and involvement in mediating critical signal transduction pathways in cancer cells. Recent evidence suggests that eukaryotic elongation factor 2 kinase (eEF-2K) is a potential therapeutic target for treating some highly aggressive solid cancers, including lung, pancreatic and triple-negative breast cancers. Thus, several compounds have been developed for the inhibition of the enzyme activity, but they are not sufficiently specific and potent. Besides, the crystal structure of this kinase remains unknown. Hence, the functional organization and regulation of eEF-2K remain poorly characterized. For this purpose, we constructed a homology model of eEF-2K and then used docking methodology to better understanding the binding mechanism of eEF-2K with 58 compounds that have been proposed as existing inhibitors. The results of this analysis were compared with the experimental results and the compounds effective against eEF-2K were determined against eEF-2K as a result of both studies. And finally, molecular dynamics (MD) simulations were performed for the stability of eEF-2K with these compounds. According to these study defined that the binding mechanism of eEF-2K with inhibitors at the molecular level and elucidated the residues of eEF-2K that play an important role in enzyme selectivity and ligand affinity. This information may lead to new selective and potential drug molecules to be for inhibition of eEF-2K.

Communicated by Ramaswamy H. Sarma

Keywords:

• Protein kinases
• eEF-2K
• homology modeling
• molecular docking
• molecular dynamics simulation

Acknowledgements

Sincere thanks to Assoc. Prof. Dr. Bülent Özpolat contributes for information in the introduction part of this study. The numerical calculations reported in this abstract were performed at TUBITAK ULAKBIM, High Performance and Grid Computing Center (TRUBA resources).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was financially supported by The Scientific and Technological Research Council of Turkey TUBITAK (project no: 215S008).