QSAR studies on pyrrolidine amides derivatives as DPP-IV inhibitors for type 2 diabetes

A large series of pyrrolidine amides derivatives as DPP-IV inhibitors was subjected to quantitative structure–activity relationship (QSAR) analysis. These 248 geometrical structures were constructed and optimized at the HF/6-31G* level of theory by the Gaussian program. The 2D–QSAR model was developed from a training set consisting of 186 compounds by the minimum redundancy maximum relevance–sequential floating back–support vector regression method with a good determination coefficient: the squared correlation coefficient ( R train 2 = 0.867) and the tenfold cross-validation squared correlation coefficient ( q train-CV 2 = 0.669). The QSAR model was then tested using an external test set consisting of 62 compounds and provided a satisfactory external predictive ability ( R test 2 = 0.666). 2D–QSAR model is robust and reliable when compared with 3D–QSAR techniques for the analogous compounds. According to the QSAR analysis, the electronic effect plays an important role for the substituents of the pyrrolidine and carbon rings. The study would serve as a guideline in designing more potent and selective drugs against type 2 diabetes.