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Protein & Peptide Letters


ISSN (Print): 0929-8665
ISSN (Online): 1875-5305

Alignment-independent QSAR Analysis of SecA Inhibitors

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

Volume 20, Issue 7, 2013

Page: [802 - 807] Pages: 6

DOI: 10.2174/0929866511320070010

Price: $65


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.

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

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