A new quantitative structure-activity relationship model for Angiotensin-converting enzyme inhibitory dipeptides based on integrated descriptors

Angiotensin-converting enzyme (ACE) inhibitory peptides derived from food proteins have been widely reported for hypertension treatment. In this paper, a benchmark dataset containing 141 unique ACE inhibitory dipeptides was constructed through database mining and quantitative structure–activity relationships (QSAR) study was carried out to predict half-inhibitory concentration (IC50) of ACE activity. 16 descriptors were tested and the model generated by G-scale descriptor showed the best predictive performance with the coefficient of determination (R²) and cross-validated R² (Q²) of 0.6692 and 0.6220, respectively. For most other descriptors, R² were ranging from 0.52-0.68 and Q² were ranging from 0.48-0.61. A complex model combining all 16 descriptors was carried out and variable selection was performed in order to further improve the prediction performance. The quality of model using integrated descriptors (R2 0.7340±0.0038, Q² 0.7151±0.0019) was better than that of G-scale. An in-depth study of variabl...