Eslam Pourbasheer, Reza Aalizadeh, Amin Ebadi and Mohammad Reza Ganjali Pages 751 - 766 ( 16 )
Three-dimensional quantitative structure-activity relationship was developed for the series of compounds as malonyl-CoA decarboxylase antagonists (MCD) using the CoMFA and CoMSIA methods. The statistical parameters for CoMFA (q2=0.558, r2=0.841) and CoMSIA (q2= 0.615, r2 = 0.870) models were derived based on 38 compounds as training set in the basis of the selected alignment. The external predictive abilities of the built models were evaluated by using the test set of nine compounds. From obtained results, the CoMSIA method was found to have highly predictive capability in comparison with CoMFA method. Based on the given results by CoMSIA and CoMFA contour maps, some features that can enhance the activity of compounds as MCD antagonists were introduced and used to design new compounds with better inhibition activity.
3D-QSAR, chemometrics, CoMSIA, drug design, malonyl-CoA decarboxylase.
Department of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697, Tehran, Iran.