Alignment-independent QSAR analysis of SecA inhibitors.
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.
Emergency Department, Jiangxi Provincial General Hospital of Chinese People's Armed Police Forces, Nanchang, Jiangxi 330001, China
Min
M
Xu
Yiling
Y
Bi
Mengyuan
M
Zhu
Minyong
M
Li
D000251:Adenosine Triphosphatases / Q000037:antagonists & inhibitors* / Q000737:chemistry / Q000378:metabolism; D000900:Anti-Bacterial Agents / Q000737:chemistry* / Q000378:metabolism / Q000494:pharmacology*; D001426:Bacterial Proteins / Q000037:antagonists & inhibitors* / Q000737:chemistry / Q000378:metabolism; D004791:Enzyme Inhibitors / Q000737:chemistry* / Q000378:metabolism / Q000494:pharmacology*; D026901:Membrane Transport Proteins / Q000737:chemistry / Q000378:metabolism; D008958:Models, Molecular; D015233:Models, Statistical; D011487:Protein Conformation; D021281:Quantitative Structure-Activity Relationship; D000069816:SEC Translocation Channels; D000081416:SecA Proteins
D000900:Anti-Bacterial Agents; D001426:Bacterial Proteins; D004791:Enzyme Inhibitors; D026901:Membrane Transport Proteins; D000069816:SEC Translocation Channels; D000251:Adenosine Triphosphatases; D000081416:SecA Proteins