Title: Exploring 3D-QSAR for Ketolide Derivatives as Antibacterial Agents Using CoMFA and CoMSIA
VOLUME: 7 ISSUE: 3
Author(s):Qiu-Ling Song, Ping-Hua Sun and Wei-Min Chen
Affiliation:Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, College of Pharmacy, Jinan University.
Keywords:3D-QSAR, CoMFA, CoMSIA, Ketolide, Antibacterial activity
Abstract: Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of ketolide derivatives as antibacterial agents. The 3D-QSAR models resulted from 42 molecules gave r2 cv values of 0.699 and 0.630, r2 values of 0.945 and 0.925. The predictive ability of CoMFA and CoMSIA, determined using a test set of 10 compounds, gave predictive correlation coefficients of 0.849 and 0.786, respectively. The results provided insight for predictive and diagnostic aspects of ketolide derivatives for better antibacterial activity.
