陈景文,
徐童,
王雅
工业生态与环境工程教育部重点实验室, 大连理工大学环境学院, 大连 116024
作者简介: 张文灏(1991-),女,硕士,研究方向为污染生态化学及毒理学,E-mail:zhang_w_h@outlook.com.
基金项目: 国家自然科学基金(21661142001)中图分类号: X171.5
QSAR Models for Predicting Biological Half-life of Xenobiotics in Fish
Zhang Wenhao,Chen Jingwen,
Xu Tong,
Wang Ya
Key Laboratory of Industrial Ecology and Environmental Engineering(Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China
CLC number: X171.5
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摘要:生物半减期(t1/2)是评价外源化合物在鱼体内蓄积效应的重要参数。实验测定t1/2的速度慢、成本高，难以满足化学品生态风险评价的需求，需要发展替代实验的模型预测方法。本研究搜集了653种化合物t1/2实测值，采用多元线性回归(MLR)和支持向量机(SVM) 2种方法，建立了鱼体logt1/2的定量构效关系(QSAR)预测模型。MLR模型的校正决定系数(Radj2)为0.751，均方根误差(RMSEtrain)为0.587，去一法交叉验证系数(QLOO2)为0.735，外部验证系数(Qext2)为0.682，这表明模型具有较好的拟合度、稳健性和预测能力。SVM模型具有更好的拟合和预测能力(Radj2 = 0.839, RMSEtrain = 0.457, Qext2 = 0.708)。采用Williams法对模型的应用域进行表征。所建模型可用于预测多环芳烃、多氯联苯、多溴联苯醚、有机磷农药、药物等典型化合物，以及其他烷烃、环烷烃、烯烃、醇、醚、酸、酯、酮、含卤素化合物、芳香族化合物、含硫、氮、磷化合物的在鱼体内的logt1/2值。
关键词: 外源化合物/
生物半减期/
QSAR/
支持向量机
Abstract:Biological half-life (t1/2) of chemicals is a key parameter for assessing bioaccumulation of xenobiotics. As the number of synthetic chemicals is huge, it is not practical to experimentally measure their t1/2 values one by one. It is important to develop alternative methods to predict the t1/2 values of xenobiotics. In this study, t1/2 values of 653 chemicals in fish were collected, and multiple linear regression (MLR) and support vector machine (SVM) methods were adopted to develop quantitative structure-activity relationship (QSAR) models for predicting t1/2. For the MLR model, the adjusted determination coefficient (Radj2) is 0.751, the root-mean-square error (RMSE) is 0.587, leave-one-out cross validated coefficient (QLOO2) is 0.735 and external explained variance (Qext2) is 0.682, which indicate that the MLR model has high goodness of fit, robustness, and predictive ability. The results of the SVM model also show high goodness of fit and good predictive ability (Radj.train2 = 0.839, RMSEtrain = 0.457, Qext2 = 0.708). The model application domains were characterized by the Williams plot. The obtained models can be used to predict logt1/2 of chemicals including polycyclic aromatic hydrocarbons, polychlorinated biphenyls, poly brominated diphenyl ethers, pesticides, pharmaceuticals, alkanes, naphthenic hydrocarbons, alkenes, alcohols, ethers, acids, esters, ketones, halogenated compounds, aromatics, organosulfur compounds, organonitrogen compounds and organophosphorus compounds.
Key words:xenobiotics/
biological half-life/
QSAR/
SVM.
