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QSAR 预测抗生素和农药的添加剂和非添加剂混合物毒性。

QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide.

机构信息

College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China; Guangxi Key Laboratory of Environmental Pollution Control Theory and Technology, Guilin University of Technology, Guilin, 541004, China; Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, Guilin University of Technology, Guilin, 541004, China.

College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China.

出版信息

Chemosphere. 2018 May;198:122-129. doi: 10.1016/j.chemosphere.2018.01.142. Epub 2018 Feb 6.

Abstract

Antibiotics and pesticides may exist as a mixture in real environment. The combined effect of mixture can either be additive or non-additive (synergism and antagonism). However, no effective predictive approach exists on predicting the synergistic and antagonistic toxicities of mixtures. In this study, we developed a quantitative structure-activity relationship (QSAR) model for the toxicities (half effect concentration, EC) of 45 binary and multi-component mixtures composed of two antibiotics and four pesticides. The acute toxicities of single compound and mixtures toward Aliivibrio fischeri were tested. A genetic algorithm was used to obtain the optimized model with three theoretical descriptors. Various internal and external validation techniques indicated that the coefficient of determination of 0.9366 and root mean square error of 0.1345 for the QSAR model predicted that 45 mixture toxicities presented additive, synergistic, and antagonistic effects. Compared with the traditional concentration additive and independent action models, the QSAR model exhibited an advantage in predicting mixture toxicity. Thus, the presented approach may be able to fill the gaps in predicting non-additive toxicities of binary and multi-component mixtures.

摘要

抗生素和农药可能在真实环境中混合存在。混合物的联合效应可能是相加的或非相加的(协同作用和拮抗作用)。然而,目前还没有有效的预测方法可以预测混合物的协同和拮抗毒性。在这项研究中,我们建立了一个定量构效关系(QSAR)模型,用于预测由两种抗生素和四种农药组成的 45 种二元和多元混合物的毒性(半效浓度,EC)。测试了单一化合物和混合物对发光菌的急性毒性。使用遗传算法获得了具有三个理论描述符的最优模型。各种内部和外部验证技术表明,QSAR 模型的决定系数为 0.9366,均方根误差为 0.1345,预测 45 种混合物的毒性呈相加、协同和拮抗作用。与传统的浓度相加和独立作用模型相比,QSAR 模型在预测混合物毒性方面具有优势。因此,所提出的方法可能能够填补预测二元和多元混合物非加性毒性的空白。

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