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Predictive ecotoxicity of MoA 1 of organic chemicals using in silico approaches

机译:使用计算机模拟方法预测有机化合物MoA 1的预测生态毒性

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摘要

Persistent organic products are compounds used for various purposes, such as personal care products, surfactants, colorants, industrial additives, food, pesticides and pharmaceuticals. These substances are constantly introduced into the environment and many of these pollutants are difficult to degrade. Toxic compounds classified as MoA 1 (Mode of Action 1) are low toxicity compounds that comprise nonreactive chemicals. In silico methods such as Quantitative Structure-Activity Relationships (QSARs) have been used to develop important models for prediction in several areas of science, as well as aquatic toxicity studies. The aim of the present study was to build a QSAR model-based set of theoretical Volsurf molecular descriptors using the fish acute toxicity values of compounds defined as MoA 1 to identify the molecular properties related to this mechanism. The selected Partial Least Squares (PIS) results based on the values of cross-validation coefficients of determination (Q(cv)(2)) show the following values: Q(cv)(2) = 0.793, coefficient of determination (R-2) = 0.823, explained variance in extemal prediction (Q(ext)(2)) = 0.87. From the selected descriptors, not only the hydrophobicity is related to the toxicity as already mentioned in previously published studies but other physicochemical properties combined contribute to the activity of these compounds. The symmetric distribution of the hydrophobic moieties in the structure of the compounds as well as the shape, as branched chains, are important features that are related to the toxicity. This information from the model can be useful in predicting so as to minimize the toxicity of organic compounds.
机译:持久性有机产品是用于各种目的的化合物,例如个人护理产品,表面活性剂,着色剂,工业添加剂,食品,农药和药品。这些物质不断地引入环境,其中许多污染物难以降解。分类为MoA 1(作用模式1)的有毒化合物是包含非反应性化学物质的低毒性化合物。诸如定量结构-活性关系(QSAR)等计算机方法已被用于开发重要的预测科学模型以及水生毒性研究的模型。本研究的目的是使用定义为MoA 1的化合物的鱼类急性毒性值来建立基于QSAR模型的理论Volsurf分子描述子集,以鉴定与该机制有关的分子特性。基于交叉验证确定系数(Q(cv)(2))的值选择的偏最小二乘(PIS)结果显示以下值:Q(cv)(2)= 0.793,确定系数(R- 2)= 0.823,外部预测的解释方差(Q(ext)(2))= 0.87。从所选的描述语中,不仅疏水性与毒性有关,如先前发表的研究中已经提到的,而且其他理化性质的组合也有助于这些化合物的活性。疏水部分在化合物结构中的对称分布以及作为支链的形状是与毒性有关的重要特征。来自模型的此信息可用于预测,从而最大程度地减少有机化合物的毒性。

著录项

  • 来源
    《Ecotoxicology and Environmental Safety》 |2018年第5期|151-159|共9页
  • 作者单位

    State Univ Paraiba, Dept Sanit & Environm Engn, Postgrad Program Sci & Environm Technol, BR-58429500 Campina Grande, PB, Brazil;

    Univ Fed Paraiba, Pharm Dept, BR-58051900 Joao Pessoa, Paraiba, Brazil;

    Univ Fed Paraiba, Postgrad Program Nat & Synthet Bioact Prod, BR-58051900 Joao Pessoa, Paraiba, Brazil;

    State Univ Paraiba, Dept Sanit & Environm Engn, Postgrad Program Sci & Environm Technol, BR-58429500 Campina Grande, PB, Brazil;

    Univ Fed Paraiba, Postgrad Program Nat & Synthet Bioact Prod, BR-58051900 Joao Pessoa, Paraiba, Brazil;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    QSAR; Fish acute toxicity; Molecular descriptors; Volsurf software; MoA 1;

    机译:QSAR;鱼类急性毒性;分子描述符;Volsurf软件;MoA 1;
  • 入库时间 2022-08-17 13:22:37

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