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Development of Quantitative Structure–Activity Relationship Models for Predicting Chronic Toxicity of Substituted Benzenes to Daphnia Magna

Abstract

The chronic toxicity of anthropogenic molecules such as substituted benzenes to Daphnia magna is a basic eco-toxicity parameter employed to assess their environmental risk. As the experimental methods are laborious, costly, and time-consuming, development in silico models for predicting the chronic toxicity is vitally important. In this study, on the basis of five molecular descriptors and 48 compounds, a quantitative structure–property relationship model that can predict the chronic toxicity of substituted benzenes were developed by employing multiple linear regressions. The correlation coefficient (R 2) and root-mean square error (RMSE) for the training set were 0.836 and 0.390, respectively. The developed model was validated by employing 10 compounds tested in our lab. The R 2EXT and RMSE EXT for the validation set were 0.736 and 0.490, respectively. To further characterizing the toxicity mechanism of anthropogenic molecules to Daphnia, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed.

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Acknowledgments

Financial support from 2013 Commonweal and Environmental Protection Project of Ministry of Environmental Protection of the People’s Republic of China(No.: 2013467028), the National High Technology Research and Development Program of China(863 Program, No.: 2013AA06A308), 2015 Basic Research Operating Expenses Program of Central Public Welfare Research Institutes and National Natural Science Foundation of China (Nos. 31200338 and 21507038).

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Correspondence to Jining Liu.

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Fan, D., Liu, J., Wang, L. et al. Development of Quantitative Structure–Activity Relationship Models for Predicting Chronic Toxicity of Substituted Benzenes to Daphnia Magna . Bull Environ Contam Toxicol 96, 664–670 (2016). https://doi.org/10.1007/s00128-016-1787-6

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Keywords

  • Chronic toxicity
  • Daphnia magna
  • Quantitative structure–property relationships
  • Substituted benzenes
  • CoMFA
  • CoMSIA