Quantitative Structure Activity Relationships Study of Soluble Epoxide Hydrolase Inhibitors Using MLR, ANN, CoMFA and CoMSIA Methods

Abstract

AbstractSoluble epoxide hydrolase (sEH), a member of the α/β hydrolase fold family, catalyzes the hydrolysis of epoxy eicosatrienoic acids to vicinal diol which are involved in the regulation of blood pressure and inflammation. In this study, 2D and 3D‐QSAR analysis of novel N,N′‐disubstituted urea derivatives as sEH inhibitors were performed by stepwise multiple linear regressions (SW‐MLR), stepwise artificial neural networks (SW‐ANN), Comparative Molecular Field Analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). It was found that SW‐MLR model with r2 of 0.954 for the training set and r2 of 0.876 for the test set were more favorable than model established by CoMFA method with r2=0.983, r2pred=0.602 and CoMSIA with r2=0.987, r2pred=0.751 in 3D‐QSAR. In addition, obtaining models were validated by cross validation with cut off value of q2> 0.5. These developed models could be a useful guideline to design and predict the activity of novel compounds with enhanced sEH inhibitory activities.