Development and assessment of quantitative structure-activity relationship models for bioconcentration factors of organic pollutants

作     者：QIN Hong CHEN JingWen WANG Ying WANG Bin LI XueHua LI Fei WANG YaNan 

作者机构：Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education) Department of Environmental Scienceand Technology Dalian University of Technology Dalian 116024 China 

出 版 物：《Chinese Science Bulletin》 (中国科学通报)

年 卷 期：2009年第54卷第4期

页      面：628-634页

核心收录：

学科分类：083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 07[理学] 08[工学] 09[农学] 0903[农学-农业资源与环境] 0713[理学-生态学] 

基　　金：Supported by the National Basic Research Program of China (Grant No. 2006CB403302) 

主　　题：生物浓缩因子 定量结构活动关系 有机污染物 生态学 风险评估 

摘      要：Bioconcentration factors (BCFs) are of great importance for ecological risk assessment of organic chemicals. In this study, a quantitative structure-activity relationship (QSAR) model for fish BCFs of 8 groups of compounds was developed employing partial least squares (PLS) regression, based on linear solvation energy relationship (LSER) theory and theoretical molecular structural descriptors. The guidelines for development and validation of QSAR models proposed by the Organization for Economic Cooperation and Development (OECD) were followed. The model results show that the main factors governing logBCF are Connolly molecular area (CMA), average molecular polarizability (α) and molecular weight (MW). Thus molecular size plays a critical role in affecting the bioconcentration of organic pollutants in fish. For the established model, the multiple correlation coefficient square (RY2) = 0.868, the root mean square error (RMSE) = 0.553 log units, and the leave-many-out cross-validated Q2CUM = 0.860, indicating its good goodness-of-fit and robustness. The model predictivity was evaluated by external validation, with the external explained variance (QE2XT) = 0.755 and RMSE = 0.647 log units. Moreover, the applicability domain of the developed model was assessed and visualized by the Williams plot. The developed QSAR model can be used to predict fish logBCF for organic chemicals within the application domain.