Letters in Drug Design & Discovery

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


3D-QSAR Study of Synthetic Furanones as Inhibitors of Quorum Sensing by Using CoMFA and CoMSIA Approach

Author(s): Ping-Hua Sun, Zhao-Qi Yang, Mao-Kang Li, Wei-Min Chen, Qian Liu, Xin-Sheng Yao.


3D-QSAR models of twenty six furanones as inhibitors of bacterial quorum sensing (QS) were established by using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The statistical results showed that the 3D-QSAR models derived from CoMFA were superior to those generated from CoMSIA. The optimal CoMFA model exhibited good cross-validated q2 and conventional r2 values at 0.639 and 0.992 respectively. The external test sets ( 2 pred r ) value of 0.56 further confirmed the predictive capacity of the resultant CoMFA models. A set of 3D contour plots based on the CoMFA models revealed that modifications at C2, C3 and C5 of the furanones may be valuable to improve the inhibition activities of QS. Results showed that both the steric and electrostatic factors should appropriately be taken into account in development of potent QS inhibitors.

Keywords: 3D-QSAR, CoMFA, CoMSIA, Quorum-Sensing, Furanones

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Article Details

Year: 2009
Page: [568 - 574]
Pages: 7
DOI: 10.2174/157018009789353437
Price: $58