Quantitative Structure–Activity Relationships and Docking Studies of Calcitonin Gene‐Related Peptide Antagonists

Defining the role of calcitonin gene‐related peptide in migraine pathogenesis could lead to the application of calcitonin gene‐related peptide antagonists as novel migraine therapeutics. In this work, quantitative structure–activity relationship modeling of biological activities of a large range of calcitonin gene‐related peptide antagonists was performed using a panel of physicochemical descriptors. The computational studies evaluated different variable selection techniques and demonstrated shuffling stepwise multiple linear regression to be superior over genetic algorithm‐multiple linear regression. The linear quantitative structure–activity relationship model revealed better statistical parameters of cross‐validation in comparison with the non‐linear support vector regression technique. Implementing only five peptide descriptors into this linear quantitative structure–activity relationship model resulted in an extremely robust and highly predictive model with calibration, leave‐one‐out and leave‐20‐out validation R2 of 0.9194, 0.9103, and 0.9214, respectively. We performed docking of the most potent calcitonin gene‐related peptide antagonists with the calcitonin gene‐related peptide receptor and demonstrated that peptide antagonists act by blocking access to the peptide‐binding cleft. We also demonstrated the direct contact of residues 28–37 of the calcitonin gene‐related peptide antagonists with the receptor. These results are in agreement with the conclusions drawn from the quantitative structure–activity relationship model, indicating that both electrostatic and steric factors should be taken into account when designing novel calcitonin gene‐related peptide antagonists.