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Molecular Topology for the Discovery of New Broad-Spectrum Antibacterial Drugs

机译:用于发现新型广谱抗菌药物的分子拓扑

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摘要

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 sp3 carbons, ramifications, and secondary amine groups in a molecule enhance antibacterial activity, whereas the presence of 5-member rings, sp2 carbons, and sp2 oxygens hinder it. The results obtained clearly reveal the high efficiency of combining molecular topology with LDA for the prediction of antibacterial activity.
机译:在该研究中,分子拓扑结构用于开发几种能够根据其抗菌活性进行分类化合物的判别方程。用作结构描述符的拓扑指数,并通过在一组喹诺酮和喹诺酮样化合物上施加线性判别分析(LDA)来确定它们与抗菌活性的关系。构建了四个方程,命名为DF1,DF2,DF3和DF4,所有内容都具有良好的统计参数,如Fisher-Snedecor的F(在所有情况下超过25个),Wilk的Lambda(在所有情况下低于0.36)和正确分类的百分比(结束在所有情况下80%),允许任何有机化合物中的抗菌活性的可靠外推预测。从四个判别功能中,可以提取分子中的SP3碳,后源和仲胺基团的存在增强抗菌活性,而5-成员环,SP2碳和SP2氧气阻碍了它。得到的结果清楚地揭示了与LDA进行分子拓扑的高效率以预测抗菌活性。

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