Letters in Drug Design & Discovery

G. Perry
University of Texas
San Antonio, TX
USA
Email: lddd@benthamscience.org

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

Author(s): Qiu-Ling Song, Ping-Hua Sun, Wei-Min Chen.

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.

Keywords: 3D-QSAR, CoMFA, CoMSIA, Ketolide, Antibacterial activity

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Article Details

VOLUME: 7
ISSUE: 3
Year: 2010
Page: [149 - 159]
Pages: 11
DOI: 10.2174/157018010790596641
Price: $58