Exploring 3D-QSAR for Ketolide Derivatives as Antibacterial Agents Using CoMFA and CoMSIA

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:

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.

Cite this article as:

Song Qiu-Ling, Sun Ping-Hua and Chen Wei-Min, Exploring 3D-QSAR for Ketolide Derivatives as Antibacterial Agents Using CoMFA and CoMSIA, Letters in Drug Design & Discovery 2010; 7 (3) . https://dx.doi.org/10.2174/157018010790596641