Department of Pharmaceutical Technology, Faculty of Pharmacy, Nicolaus Copernicus University, Jurasza 2, 85-094 Bydgoszcz, Poland.
Institute of Computing Science, Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland.
Int J Mol Sci. 2021 Jul 27;22(15):7997. doi: 10.3390/ijms22157997.
This paper presents the results of structure-activity relationship (SAR) studies of 140 3,3'-(α,ω-dioxaalkan)bis(1-alkylimidazolium) chlorides. In the SAR analysis, the dominance-based rough set approach (DRSA) was used. For analyzed compounds, minimum inhibitory concentration (MIC) against strains of and was determined. In order to perform the SAR analysis, a tabular information system was formed, in which tested compounds were described by means of condition attributes, characterizing the structure (substructure parameters and molecular descriptors) and their surface properties, and a decision attribute, classifying compounds with respect to values of MIC. DRSA allows to induce decision rules from data describing the compounds in terms of condition and decision attributes, and to rank condition attributes with respect to relevance using a Bayesian confirmation measure. Decision rules present the most important relationships between structure and surface properties of the compounds on one hand, and their antibacterial activity on the other hand. They also indicate directions of synthesizing more efficient antibacterial compounds. Moreover, the analysis showed differences in the application of various parameters for Gram-positive and Gram-negative strains, respectively.
本文介绍了 140 种 3,3'-(α,ω-二氧杂烷)双(1-烷基咪唑𬭩)氯化物的结构-活性关系 (SAR) 研究结果。在 SAR 分析中，使用了基于优势的粗糙集方法 (DRSA)。对于分析的化合物，测定了它们对 和 菌株的最小抑菌浓度 (MIC)。为了进行 SAR 分析，形成了一个表格信息系统，其中测试化合物通过描述结构的条件属性(亚结构参数和分子描述符)及其表面性质，并通过决策属性进行分类，以确定 MIC 值的化合物。DRSA 允许从描述化合物的条件和决策属性的数据中归纳决策规则，并使用贝叶斯确认度量对条件属性进行相关性排序。决策规则展示了化合物的结构和表面性质与其抗菌活性之间的重要关系。它们还表明了合成更有效抗菌化合物的方向。此外，该分析表明，对于革兰氏阳性和革兰氏阴性菌株，分别应用各种参数的方向存在差异。
