Design, one-pot synthesis, computational and biological evaluation of diaryl benzimidazole derivatives as MEK inhibitors

Abstract

MEK mutations are more common in various human malignancies, such as pancreatic cancer (70–90%), mock melanoma (50%), liver cancer (20–40%), colorectal cancer (25–35%), melanoma (15–20%), non-small cell lung cancer (10–20%) and basal breast cancer (1–5%). Considering the significance of MEK mutations in diverse cancer types, the rational design of the proposed compounds relies on the structural resemblance to FDA-approved MEK inhibitors like selumetinib and binimetinib. The compound under design features distinct substitutions at the benzimidazole moiety, specifically at positions 2 and 3, akin to the FDA-approved drugs, albeit differing in positions 5 and 6. Subsequent structural refinement was guided by key elements including the DFG motif, hydrophobic pocket and catalytic loop of the MEK protein. A set of 15 diverse diaryl benzimidazole derivatives (S1–S15) were synthesized via a one-pot approach and characterized through spectroscopic techniques, including MASS, IR, ¹H NMR and ¹³C NMR. In vitro anticancer activities of all the synthesized compounds were evaluated against four cancer cell lines, A375, HT −29, A431 and HFF, along with the standard drug trametinib. Molecular docking was performed for all synthesized compounds (S1–15), followed by 950 ns molecular dynamics simulation studies for the promising compounds S1, S5 and S15. The stability of these complexes was assessed by calculating the root-mean-square deviation, solvent accessible surface area and gyration radius relative to their parent structures. Additionally, free energy of binding calculations were performed. Based on the biological and computational results, S15 was the most potent compound and S1 and S5 are comparable to the standard drug trametinib.

Communicated by Ramaswamy H. Sarma

 

Keywords:

• MEK
• DFG
• hydrophobic
• catalytic loop
• molecular dynamics
• anticancer

Acknowledgments

The authors are thankful to DST-FIST, Central University of Punjab, Bathinda, for providing the necessary facilities to execute this manuscript. PP and MG acknowledged South Ural State University, Chelyabinsk, Russia under Priority 2030 program. JN thanks the University of Zagreb, University Computing Centre—SRCE, for granting access to the Isabella computer cluster, and the University of Rijeka for support through the Uniri-mladi-prirod-22-8 grant.

Disclosure statement

No potential conflict of interest was reported by the authors.

Authors’ contributions

Conceptualization: Pradeep Kumar; Synthesis, biology and computational studies and writing the manuscript: Teja Ram, Ankit Kumar Singh, Prateek Pathak, Jurica Novak; Sketching of figures and data interpretation: Ankit Kumar Singh, Prateek Pathak, Adarsh Kumar, Harshwardhan Singh, Jurica Novak; Writing, review and final editing of the manuscript: Maria Grishina and Pradeep Kumar.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.