PDF(Pubmed)
Abstract：
The structure-activity analysis (SAR) and machine learning were used to investigate potential anti-S. aureus agents in a faster method. In this study, 24 oxygenated benzene ring components with S. aureus inhibition capacity were confirmed by literature exploring and in-house experiments, and the SAR analysis suggested that the hydroxyl group position may affect the anti-S. aureus activity. The 2D-MLR-QSAR model with 9 descriptors was further evaluated as the best model among the 21 models. After that, hesperetic acid and 2-HTPA were further explored and evaluated as the potential anti-S. aureus agents screening in the natural product clustering library through the best QSAR model calculation. The antibacterial capacities of hesperetic acid and 2-HTPA had been investigated and proved the similar predictive pMIC value resulting from the QSAR model. Besides, the two novel components were able to inhibit the growth of S. aureus by disrupting the cell membrane through the molecular dynamics simulation (MD), which further evidenced by scanning electron microscopy (SEM) test and PI dye results. Overall, these results are highly suggested that QSAR can be used to predict the antibacterial agents targeting S. aureus, which provides a new paradigm to research the molecular structure-antibacterial capacity relationship.
摘要：
使用结构活性分析（SAR）和机器学习来研究潜在的抗S。一种更快的方法中的金黄色葡萄球菌试剂。在这项研究中,通过文献探索和内部实验证实了24种具有金黄色葡萄球菌抑制能力的含氧苯环组分，SAR分析表明，羟基位置可能会影响抗S。金黄色葡萄球菌活性。具有9个描述符的2D-MLR-QSAR模型被进一步评估为21个模型中的最佳模型。之后,橙皮酸和2-HTPA被进一步探索和评估为潜在的抗-S。通过最佳QSAR模型计算，在天然产物聚类库中筛选金黄色葡萄球菌制剂。研究了橙皮酸和2-HTPA的抗菌能力，并证明了QSAR模型产生的pMIC值相似。此外,通过分子动力学模拟（MD）破坏细胞膜，这两种新成分能够抑制金黄色葡萄球菌的生长，扫描电子显微镜（SEM）测试和PI染料结果进一步证明。总的来说,这些结果高度表明QSAR可用于预测针对金黄色葡萄球菌的抗菌剂，为分子结构与抗菌能力关系的研究提供了新的范式。
