3D-QSAR analysis of MCD inhibitors by CoMFA and CoMSIA

Title:3D-QSAR analysis of MCD inhibitors by CoMFA and CoMSIA

Volume: 18 Issue: 8

Author(s): Eslam Pourbasheer, Reza Aalizadeh, Amin Ebadi and Mohammad Reza Ganjali

Affiliation:

Keywords: 3D-QSAR, chemometrics, CoMSIA, drug design, malonyl-CoA decarboxylase.

Abstract: 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.

Cite this article as:

Pourbasheer Eslam, Aalizadeh Reza, Ebadi Amin and Ganjali Reza Mohammad, 3D-QSAR analysis of MCD inhibitors by CoMFA and CoMSIA, Combinatorial Chemistry & High Throughput Screening 2015; 18 (8) . https://dx.doi.org/10.2174/1386207318666150803141738