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Updated: May 17, 2026

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
Alignment-independent QSAR analysis of SecA inhibitors
Min Xu1, Yiling Bi, Mengyuan Zhu
1Emergency Department, Jiangxi Provincial General Hospital of Chinese People's Armed Police Forces, Nanchang, Jiangxi 330001, China
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 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.
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