3D-QSAR (CoMFA, CoMSIA) and molecular docking studies of natural flavonoid derivatives to explore structural requirements for MCF-7 cell line inhibition. (2017)

• Record Type: Journal Article
• Authors: Gunda, Shravan Kumar; Gummi, Manasa Reddy; Mohmed, Jaheer; Shaik, Ayub
• Is Part Of: International journal of computational biology and drug design. Volume 10:Number 3(2017)
• Page Start: 264
• Page End: 285
• Publication Date: 2017
• Subjects: flavonoids -- MCF-7 -- CoMFA -- comparative molecular field analysis -- CoMSIA -- comparative molecular similarity indices analysis -- molecular docking; Computational biology -- Periodicals; Drugs -- Design -- Periodicals; 570.285
• Languages: English
• ISSNs: 1756-0756

Abstract

In the present study, molecular modelling studies have been reported on a series of natural flavonoid derivatives to analyse structure activity relationship studies of MCF-7 inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA)-based QSAR methods. Eighty-four compounds were used as training set to establish the model and 20 compounds were used as external test set to validate these models. The generated models exhibited good statistical results such as q 2, r 2 . CoMFA analysis yielded the q 2 of 0.765 and r 2 of 0.968 with five components. CoMSIA model generated using steric, electrostatic, hydrophobic, donor and acceptor fields with q 2 value of 0.592 and r 2 value of 0.932 with six components was found to be the optimal model among the various models generated. According to contour map results, we have recommended the critical sites for modification in structure which will be useful in designing potent compounds with improved activity.