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3D-QSAR Analysis of SecA Inhibitors
LI Minyong * #,ZHU mengyuan
School of Pharmacy, Shandong University, Jinan 250012
*Correspondence author
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Funding: This work was supported by grants from the PhD Programs Foundation of Ministry of Education of China （No.No. 20090131120080), Shandong Natural Science Foundation）
Opened online:31 January 2013
Accepted by: none
Citation: LI Minyong,ZHU mengyuan.3D-QSAR Analysis of SecA Inhibitors[OL]. [31 January 2013] http://en.paper.edu.cn/en_releasepaper/content/4516260
 
 
SecA ATPase plays a crucial role in translocation of membrane and secreted polypeptides and proteins in bacteria and therefore a perfect target for novel antimicrobial drug design. Herein, we generated QSAR models with an alignment-independent method. The optimum model obtained for the training set was statistically significant with cross-validation regression coefficient (q2) value of 0.40 and correlation coefficient (r2) value of 0.89. These results suggest that this 3D-QSAR model can be used to guide the development of new SecA inhibitors.
Keywords:Medicinal chemistry; SecA inhibitors; 3D-QSAR
 
 
 

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