Unraveling the molecular mechanism of benzothiophene and benzofuran scaffold-merged compounds binding to anti-apoptotic Myeloid cell leukemia 1

Abstract

Myeloid cell leukemia 1 (Mcl1), is an antiapoptotic member of the Bcl-2 family proteins, has gained considerable importance due to its overexpression activity prevents the oncogenic cells to undergo apoptosis. This overexpression activity of Mcl1 eventually develops strong resistance to a wide variety of anticancer agents. Therefore, designing novel inhibitors with potentials to elicit higher binding affinity and specificity to inhibit Mcl1 activity is of greater importance. Thus, Mcl1 acts as an attractive cancer target. Despite recent experimental advancement in the identification and characterization of benzothiophene and benzofuran scaffold-merged compounds, the molecular mechanisms of their binding to Mcl1 are yet to be explored. The current study demonstrates an integrated approach – pharmacophore-based 3D-QSAR, docking, molecular dynamics (MD) simulation and free-energy estimation – to access the precise and comprehensive effects of current inhibitors targeting Mcl1 together with its known activity values. The pharmacophore – ANRRR.240 – based 3D-QSAR model from the current study provided high confidence (R²=0.9154, Q²=0.8736 and RMSE = 0.3533) values. Furthermore, the docking correctly predicted the binding mode of highly active compound 42. Additionally, the MD simulation for docked complex under explicit-solvent conditions together with free-energy estimation exhibited stable interaction and binding strength over the time period. Also, the decomposition analysis revealed potential energy contributing residues – M231, M250, V253, R265, L267 and F270 – to the complex stability. Overall, the current investigation might serve as a valuable insight, either to (i) improve the binding affinity of the current compounds or (ii) discover new generation anticancer agents that can effectively downregulate Mcl1 activity.

Communicated by Ramaswamy H. Sarma

Keywords:

• Myeloid cell leukemia 1
• merged compounds
• molecular dynamics simulations
• binding free energy estimation
• pharmacophore-based 3D-QSAR model

Acknowledgements

MP gratefully acknowledge the use of bioinformatics infrastructure facility supported by Biocenter Finland, CSC-IT Center for Science (Project AA1268 and 2000461) for computational facility, Dr Jukka Lehtonen for the IT support and Dr Sabarinathan Radhakrishnan, Institute for Research in Biomedicine, Barcelona, Spain, for the MD analysis script. The authors specially thank Professor Mark Johnson, Åbo Akademi University, for providing the lab facility.

Disclosure statement

No potential conflict of interest was reported by the authors.