Departamento de Farmacia, Universidad Cardenal Herrera-CEU, CEU Universities C/Ramón y Cajal s/n, 46115 Alfara del Patriarca, Valencia, Spain.
ESI International Chair@CEU-UCH, Departamento de Matemáticas, Física y Ciencias Tecnológicas, Universidad Cardenal Herrera-CEU, CEU Universities San Bartolomé 55, 46115 Alfara del Patriarca, Valencia, Spain.
Int J Mol Sci. 2021 May 29;22(11):5823. doi: 10.3390/ijms22115823.
The variability of methicillin-resistant (MRSA), its rapid adaptive response against environmental changes, and its continued acquisition of antibiotic resistance determinants have made it commonplace in hospitals, where it causes the problem of multidrug resistance. In this study, we used molecular topology to develop several discriminant equations capable of classifying compounds according to their anti-MRSA activity. Topological indices were used as structural descriptors and their relationship with anti-MRSA activity was determined by applying linear discriminant analysis (LDA) on a group of quinolones and quinolone-like compounds. Four extra equations were constructed, named DF, DF, DF and DF (DF was built in a previous study), all with good statistical parameters, such as Fisher-Snedecor F (>68 in all cases), Wilk's lambda (<0.13 in all cases), and percentage of correct classification (>94% in all cases), which allows a reliable extrapolation prediction of antibacterial activity in any organic compound. The results obtained clearly reveal the high efficiency of combining molecular topology with LDA for the prediction of anti-MRSA activity.
耐甲氧西林金黄色葡萄球菌（MRSA）的变异性、其对环境变化的快速适应能力以及对抗生素耐药决定因素的持续获取，使其在医院中普遍存在，导致了多重耐药问题。在这项研究中，我们使用分子拓扑学开发了几种判别方程，能够根据化合物的抗 MRSA 活性对其进行分类。拓扑指数被用作结构描述符，通过对一组喹诺酮类和类喹诺酮化合物应用线性判别分析（LDA），确定它们与抗 MRSA 活性的关系。构建了另外四个方程，分别命名为 DF、DF、DF 和 DF（DF 是在前一项研究中构建的），所有方程都具有良好的统计参数，如 Fisher-Snedecor F（所有情况下均大于 68）、Wilk's lambda（所有情况下均小于 0.13）和正确分类百分比（所有情况下均大于 94%），这允许对任何有机化合物的抗菌活性进行可靠的外推预测。所得结果清楚地表明，将分子拓扑学与 LDA 结合用于预测抗 MRSA 活性具有很高的效率。
