Predictive Modeling of Phenylpiperazine Derivatives for Renin Inhibition.

Abstract

The renin–angiotensin–aldosterone system is the well established endocrine system having significant role in preserving hemodynamic stability. Renin is secreted from the juxtaglomerular cells of the kidney. Phenylpiperazine derivatives have been reported as human renin inhibitor. To perform predictive QSAR modeling for 27 phenylpiperazine derivatives as renin enzyme inhibitors. The IC50 values for purified human renin were taken as biological activity. Physicochemical properties were calculated on Dragon software, version 5.5. Hierarchical Multiple Regression was performed to obtain quantitative structure--activity relationship model which again validated internally and externally. The selected best QSAR model was having the correlation coefficient (R2) of 0.843, predicted correlation coefficient (R2pred) of 0.867. The predictive ability of the selected model was established by leaving one-out cross-validation. Different Rm2 matrices were also calculated to validate the model externally. The quantitative structure activity relationship study indicates that CIC2, BIC2 and R7v descriptors have a very important role in renin enzyme and ligand interaction. The developed model can be applied to design new effective renin enzyme inhibitors.