Xu Min, Bi Yiling, Zhu Mengyuan, Li Minyong
Emergency Department, Jiangxi Provincial General Hospital of Chinese People's Armed Police Forces, Nanchang, Jiangxi 330001, China
Protein Pept Lett. 2013 Jul 1;20(7):802-7. doi: 10.2174/0929866511320070010.
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.
SecA ATP酶在细菌内膜和分泌多肽及蛋白质的转运过程中起着关键作用，因此是新型抗菌药物设计的理想靶点。在此，我们采用一种与序列比对无关的方法构建了定量构效关系（QSAR）模型。训练集得到的最优模型具有统计学意义，其交叉验证回归系数（q2）值为0.40，相关系数（r2）值为0.89。这些结果表明，该三维定量构效关系（3D-QSAR）模型可用于指导新型SecA抑制剂的开发。
