Computational investigation of binding mechanism of substituted pyrazinones targeting corticotropin releasing factor-1 receptor deliberated for anti-depressant drug design

摘要

In spite of various research investigations towards anti-depressant drug discovery program, no one drug has not yet launched last 20 years. Corticotropin-releasing factor-1 (CRF-1) is one of the most validated targets for the development of antagonists against depression, anxiety and post-traumatic stress disorders. Various research studies suggest that pyrazinone based CRF-1 receptor antagonists were found to be highly potent and efficacious. In this research investigation, we identified the pharmacophore and binding pattern through 2D and 3D-QSAR and molecular docking respectively. Molecular dynamics studies were also performed to explore the binding pattern recognition. We establish the relationship between activity and pharmacophoric features to design new potent compounds. The best 2D-QSAR model was generated through multiple linear regression method with r2 value of 0.97 and q2 value of 0.89. Also 3D-QSAR model was obtained through k-nearest neighbor molecular field analysis method with q2 value of 0.52 and q2_ se value of 0.36. Molecular docking and binding energy were also evaluated to define binding patterns and pharmacophoric groups, including (i) hydrogen bond with residue Asp284, Glu305 and (ii) p-p stacking with residue Trp9. Compound 11i has the highest binding affinity compared to reference compounds, so this compound could be a potent drug for stress related disorders. Most of the compounds, including reference compounds were found within acceptable range of physicochemical parameters. These observations could be provided the leads for the design and optimization of novel CRF-1 receptor antagonists.