Assessing the binding affinity of a selected class of DPP4 inhibitors using chemical descriptor-based multiple linear regression

Abstract

The activity of a selected class of DPP4 inhibitors was preliminarily assessed using chemical descriptors derived AM1 optimized geometries. Using multiple linear regression model, it was found that ?E0, LUMO energy, area, molecular weight and ?H0 are the significant descriptors that can adequately assess the binding affinity of the compounds. The derived multiple linear regression (MLR) model was validated using rigorous statistical analysis. The preliminary model suggests that bulky and electrophilic inhibitors are desired.

Keywords

• dpp4 inhibitors
• am1
• chemical descriptors
• multiple linear regression