Development of a robust QSAR model to predict the affinity of pyrrolidine analogs for dipeptidyl peptidase IV (DPP- IV)

Abstract

QSAR analysis using multiple linear regression and partial least squares methods were conducted on a data set of 47 pyrrolidine analogs acting as DPP IV inhibitors. The QSAR models generated (both MLR and PLS) were robust with statistically significant s, F, r, r² and r² (CV) values. The analysis helped to ascertain the role of shape flexibility index, Ipso atom E-state index and electrostatic parameters like dipole moment, in determining the activity of DPP IV inhibitors. In addition to QSAR modeling, Lipinski’s rule of five was also employed to check the pharmacokinetic profile of DPP IV inhibitors. Since none of the compounds violated the Lipinski’s rule of five indicating that the DPP IV inhibitors reported herein have sound pharmacokinetic profile and can be considered as potential drug candidates for diabetes mellitus Type II.

Keywords::

• Dipeptidyl Peptidase IV (DPP IV)
• QSAR
• TSAR
• MLR
• PLS
• anti-diabetic agents

Acknowledgements

Authors are thankful to the Vice Chancellor, Prof. Aditya Shastri, Banasthali University, Rajasthan for providing necessary facilities to complete this work.

Declaration of interest

The authors report no conflict of interest.