首页> 外文期刊>European Journal of Medicinal Chemistry: Chimie Therapeutique >Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors.
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Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors.

机译:细菌NorA外排泵抑制剂的胡椒碱类似物的定量结构活性关系(QSAR)。

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摘要

Quantitative structure activity relationship (QSAR) analysis of piperine analogs as inhibitors of efflux pump NorA from Staphylococcus aureus has been performed in order to obtain a highly accurate model enabling prediction of inhibition of S. aureus NorA of new chemical entities from natural sources as well as synthetic ones. Algorithm based on genetic function approximation method of variable selection in Cerius2 was used to generate the model. Among several types of descriptors viz., topological, spatial, thermodynamic, information content and E-state indices that were considered in generating the QSAR model, three descriptors such as partial negative surface area of the compounds, area of the molecular shadow in the XZ plane and heat of formation of the molecules resulted in a statistically significant model with r(2)=0.962 and cross-validation parameter q(2)=0.917. The validation of the QSAR models was done by cross-validation, leave-25%-out and external test set prediction. The theoretical approach indicates that the increase in the exposed partial negative surface area increases the inhibitory activity of the compound against NorA whereas the area of the molecular shadow in the XZ plane is inversely proportional to the inhibitory activity. This model also explains the relationship of the heat of formation of the compound with the inhibitory activity. The model is not only able to predict the activity of new compounds but also explains the important regions in the molecules in quantitative manner.
机译:为了获得一个高度精确的模型,能够预测天然来源的新化学实体对金黄色葡萄球菌NorA的抑制作用,已经进行了胡椒碱类似物作为金黄色葡萄球菌外排泵NorA抑制剂的定量结构活性关系(QSAR)分析合成的。使用基于遗传函数逼近法的Cerius2变量选择算法生成模型。在生成QSAR模型时考虑的几种描述符类型,即拓扑,空间,热力学,信息含量和E状态指数中,三个描述符(例如化合物的部分负表面积,XZ中的分子阴影面积)平面和分子形成的热量产生具有r(2)= 0.962和交叉验证参数q(2)= 0.917的统计学显着模型。 QSAR模型的验证是通过交叉验证,遗漏25%和外部测试集预测来完成的。理论方法表明,暴露的部分负表面积的增加增加了化合物对NorA的抑制活性,而XZ平面中分子阴影的面积与抑制活性成反比。该模型还解释了化合物形成热与抑制活性的关系。该模型不仅能够预测新化合物的活性,而且能够定量地解释分子中的重要区域。

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