Venetoclax analogs as promising anticancer therapeutics via targeting Bcl-2 protein: in-silico drug discovery study

Abstract

B-cell lymphoma 2 (Bcl-2) protein plays a vital role in enhancing malignant cell survival by alleviating programmed cell death. Therefore, Bcl-2 protein has been identified as a charming druggable target for cancer treatment. Venetoclax has enticed considerable attention as a potential Bcl-2 inhibitor. Herein, in-silico computations were executed to search for new venetoclax analogs against the Bcl-2 protein. A library involving 4112 was collected, prepared, and virtually screened against Bcl-2 protein using AutoDock Vina1.1.2 software. Promising analogs in complex with Bcl-2 protein were further submitted to molecular dynamics (MD) simulations, pursued by binding energy computations using the MM-GBSA approach. Compared to venetoclax (ΔG_binding = −51.2 kcal/mol), PubChem-873-158-83 and PubChem-148-422-478 demonstrated greater binding affinities with Bcl-2 protein throughout 100 ns MD simulations with ΔG_binding values of −69.1 and −62.4 kcal/mol, respectively. Structural and energetical analyses unveiled good stabilization of the identified analogs complexed with Bcl-2 protein over the MD course. The pharmacokinetic features of the two identified analogs were anticipated and unveiled the oral bioavailability of these compounds. Further in-vitro/in-vivo biological evaluations around these compounds could assist in identifying anticancer leads towards Bcl-2 protein.

Communicated by Ramaswamy H. Sarma

Keywords:

• Bcl-2
• venetoclax analogs
• molecular docking
• pharmacokinetic features
• MD simulations

Acknowledgement

This research work was funded by institutional fund projects under no. (IFP-A-2022-2-5-19). Therefore, the authors gratefully acknowledge technical and financial support from the Ministry of Education and the University of Hafr Al Batin, Saudi Arabia.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data presented in this study are available in the supplementary material.

Author contributions

Conceptualization, N.M.A., and M.A.A.I.; Data curation, N.M.A.; Formal analysis, N.M.A., K.S.A. and A.A.A.; Investigation, D.B., and E.I.F.I.; Methodology, N.M.A., and A.A.A.; Project administration, N.M.A., and M.A.A.I.; Resources, N.M.A., and M.A.A.I.; Software, M.A.A.I.; Supervision, M.A.A.I.; Visualization, N.M.A., K.S.A., A.A.A., D.B., and E.I.F.I.; Writing—original draft, N.M.A.; Writing—review & editing, K.S.A., A.A.A., D.B., E.I.F.I., and M.A.A.I. All authors have read and agreed to the published version of the manuscript.