Faculty of Chemical Engineering and Technology, University of Zagreb, Marulicev trg 19, Zagreb 10000, Croatia.
Faculty of Chemical Engineering and Technology, University of Zagreb, Marulicev trg 19, Zagreb 10000, Croatia.
Ecotoxicol Environ Saf. 2019 Mar;169:918-927. doi: 10.1016/j.ecoenv.2018.10.100. Epub 2018 Nov 30.
Extensive commercial use of aromatic hydrocarbons results with significant amounts of these chemicals and related by-products in waters, causing a severe ecological and health threat, thus requiring an increased attention. This study was aimed at developing models for prediction of the initial toxicity of the aromatic water-pollutants (expressed as EC and TU) as well as the toxicity of their intermediates at half-life of the parent pollutant (TU). For that purpose, toxicity toward Vibrio fischery was determined for 36 single-benzene ring compounds (S-BRCs), diversified by the type, number and position of substituents. Quantitative structure-activity relationship (QSAR) methodology paired with genetic algorithm optimization tool and multiple linear regression was applied to obtain the models predicting the targeted toxicity, which are based on pure structural characteristics of the tested pollutants, avoiding thus additional experimentation. Upon derivation of the models and extensive analysis on training and test sets, 4-, 4- and 5-variable models (for EC and TU, TU, respectively) were selected as the most predictive possessing 0.839<R< 0.901 and 0.789<Q< 0.859. The analysis of the selected descriptors indicated three major structural characteristics influencing the toxicity: electronegativity, geometry and electrotopological states of the molecule. Degradation kinetics determining as well the pathways of intermediates formation, reflected over ionization potential, was found to be an important parameter determining the toxicity in half-life.
芳烃类化合物在商业上的广泛应用导致了大量此类化学物质及其相关副产物进入水体,对生态和健康造成了严重威胁,因此需要引起更多的关注。本研究旨在建立预测芳香族水污染物质(以 EC 和 TU 表示)初始毒性以及母体污染物半衰期时其中间产物毒性的模型。为此,针对 36 种单苯环化合物(S-BRC)的毒性进行了研究,这些化合物的取代基类型、数量和位置各不相同。采用定量构效关系(QSAR)方法结合遗传算法优化工具和多元线性回归,获得了基于测试污染物纯结构特征的目标毒性预测模型,从而避免了额外的实验。通过对模型进行推导,并对训练集和测试集进行广泛分析,选择了 4-、4-和 5-变量模型(分别用于 EC 和 TU、TU)作为最具预测性的模型,其相关系数 R 为 0.839<R<0.901,Q 值为 0.789<Q<0.859。对所选描述符的分析表明,有三个主要的结构特征影响毒性:电负性、分子几何形状和电拓扑状态。动力学降解也确定了中间体形成的途径,反映了电离势,被发现是决定半衰期毒性的一个重要参数。