Structure-based identification of potential inhibitors of ribosomal protein S6 kinase 1, targeting cancer therapy: a combined docking and molecular dynamics simulations approach

Abstract

Ribosomal protein S6 kinase 1 (S6K1), commonly known as P70-S6 kinase 1 (p70S6), is a key protein kinase involved in cellular signaling pathways that regulate cell growth, proliferation, and metabolism. Its significant role is reported in the PIK3/mTOR signaling pathway and is associated with various complex diseases, including diabetes, obesity, and different types of cancer. Due to its involvement in various physiological and pathological conditions, S6K1 is considered as an attractive target for drug design and discovery. One way to target S6K1 is by developing small molecule inhibitors that specifically bind to its ATP-binding site, preventing its activation and thus inhibiting downstream signaling pathways necessary for cell growth and survival. In this study, we have conducted a multitier virtual screening of a pool of natural compounds to identify potential S6K1 inhibitors. We performed molecular docking on IMPPAT 2.0 library and selected top hits based on their binding affinity, ligand efficiency, and specificity towards S6K1. The selected hits were further assessed based on different filters of drug-likeliness where two compounds (Hecogenin and Glabrene) were identified as potential leads for S6K1 inhibition. Both compounds showed appreciable affinity, ligand efficiency and specificity towards S6K1 binding pocket, drug-like properties, and stable protein-ligand complexes in molecular dynamics (MD) simulations. Finally, our study has suggested that Hecogenin and Glabrene can be potential S6K1 inhibitors which are presumably implicated in the therapeutic management of associated diseases such as diabetes, obesity, and varying types of cancer.

Communicated by Ramaswamy H. Sarma

Keywords:

• Ribosomal protein S6 kinase 1
• natural compounds
• drug discovery
• molecular dynamics simulation
• anticancer therapy

Acknowledgements

The authors acknowledge and extend their appreciation to the Researchers Supporting Project Number (RSPD2023R709), King Saud University, Riyadh, Saudi Arabia for funding this study.

Authors’ contributions

T.M. and A.A.: Conceptualization. A.A.: methodology. M.S.K.: software. Y.M., M.N.S., and D.K.Y.: validation. N.F.: formal analysis. T.M. and Y.M.: investigation. D.K.Y.: resources. A.A.: data curation. A.A. and Y.M.: writing—original draft preparation. T.M. and D.K.Y.: writing—review and editing. A.N.: visualization. S.F.A., A.N., and D.K.Y.: supervision. S.F.A. and D.K.Y.: project administration. S.F.A. and A.N.: funding acquisition. All authors have read and agreed to the published version of the manuscript.

Data availability statement

The information supporting this study’s findings is available in this article.

Disclosure statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Additional information

Funding

This work was supported by Researchers Supporting Project Number (RSPD2023R709), King Saud University, Riyadh, Saudi Arabia.