In silico binding mechanism prediction of benzimidazole based corticotropin releasing factor-1 receptor antagonists by quantitative structure activity relationship, molecular docking and pharmacokinetic parameters calculation

Abstract

Despite the various research efforts toward the treatment of stress-related disorders, the drug has not yet launched last 20 years. Corticotropin releasing factor-1 receptor antagonists have been point of great interest in stress-related disorders. In the present study, we have selected benzazole scaffold-based compounds as corticotropin releasing factor-1 antagonists and performed 2D and 3D QSAR studies to identify the structural features to elucidating the binding mechanism prediction. The best 2D QSAR model was obtained through multiple linear regression method with r ² value of .7390, q ² value of .5136 and pred_r ² (predicted square correlation coefficient) value of .88. The contribution of 2D descriptor, T_2_C_1 was 60% (negative contribution) and 4pathClusterCount was 40.24% (positive contribution) in enhancing the activity. Also 3D QSAR model was statistically significant with q ² value of .9419 and q ²_se (standard error of internal validation) value of .19. Statistical parameters results prove the robustness and significance of both models. Further, molecular docking and pharmacokinetic analysis was performed to explore the scope of investigation. Docking results revealed that the all benzazole compounds show hydrogen bonding with residue Asn283 and having same hydrophobic pocket (Phe286, Leu213, Ile290, Leu287, Phe207, Arg165, Leu323, Tyr327, Phe284, and Met206). Compound B14 has higher activity compare to reference molecules. Most of the compounds were found within acceptable range for pharmacokinetic parameters. This work provides the extremely useful leads for structural substituents essential for benzimidazole moiety to exhibit antagonistic activity against corticotropin releasing factor-1 receptors.

Keywords:

• CRF-1 receptor antagonists
• QSAR
• molecular docking
• binding energy
• ADME

Acknowledgments

The authors are thankful to Centre for Human Genetics & Molecular Medicine, Central University of Punjab for providing computational facilities to accomplish this research work.