Alignment-independent QSAR Analysis of SecA Inhibitors

Title:Alignment-independent QSAR Analysis of SecA Inhibitors

Volume: 20 Issue: 7

Author(s): Min Xu, Yiling Bi, Mengyuan Zhu and Minyong Li

Affiliation:

Keywords: SecA ATPase, inhibitors, antimicrobial drug, 3D-QSAR.

Abstract: 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 crossvalidation 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.

Cite this article as:

Xu Min, Bi Yiling, Zhu Mengyuan and Li Minyong, Alignment-independent QSAR Analysis of SecA Inhibitors, Protein & Peptide Letters 2013; 20 (7) . https://dx.doi.org/10.2174/0929866511320070010

DOI https://dx.doi.org/10.2174/0929866511320070010	Print ISSN 0929-8665
Publisher Name Bentham Science Publisher	Online ISSN 1875-5305