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.
Biomolecules. 2020 Sep 19;10(9):1343. doi: 10.3390/biom10091343.
In this study, molecular topology was used to develop several discriminant equations capable of classifying compounds according to their antibacterial activity. Topological indices were used as structural descriptors and their relation to antibacterial activity was determined by applying linear discriminant analysis (LDA) on a group of quinolones and quinolone-like compounds. Four equations were constructed, named DF1, DF2, DF3, and DF4, all with good statistical parameters such as Fisher-Snedecor's F (over 25 in all cases), Wilk's lambda (below 0.36 in all cases) and percentage of correct classification (over 80% in all cases), which allows a reliable extrapolation prediction of antibacterial activity in any organic compound. From the four discriminant functions, it can be extracted that the presence of sp carbons, ramifications, and secondary amine groups in a molecule enhance antibacterial activity, whereas the presence of 5-member rings, sp carbons, and sp oxygens hinder it. The results obtained clearly reveal the high efficiency of combining molecular topology with LDA for the prediction of antibacterial activity.
在这项研究中，分子拓扑学被用来开发几个判别方程，能够根据化合物的抗菌活性对其进行分类。拓扑指数被用作结构描述符，并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）来确定它们与抗菌活性的关系。构建了四个方程，分别命名为 DF1、DF2、DF3 和 DF4，它们都具有良好的统计参数，如 Fisher-Snedecor 的 F（所有情况下都超过 25）、Wilk 的 lambda（所有情况下都低于 0.36）和正确分类的百分比（所有情况下都超过 80%），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。从这四个判别函数中，可以提取出分子中存在 sp 碳原子、支链和仲胺基团可以增强抗菌活性，而存在 5 元环、sp 碳原子和 sp 氧原子则会阻碍抗菌活性。所得结果清楚地表明，将分子拓扑学与 LDA 结合用于预测抗菌活性的效率很高。
