Literature DB >> 27016939

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

Deling Fan1, Jining Liu2, Lei Wang1, Xianhai Yang1, Shenghu Zhang1, Yan Zhang3, Lili Shi1.   

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 EXT (2) 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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Keywords:  Chronic toxicity; CoMFA; CoMSIA; Daphnia magna; Quantitative structure–property relationships; Substituted benzenes

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Year:  2016        PMID: 27016939     DOI: 10.1007/s00128-016-1787-6

Source DB:  PubMed          Journal:  Bull Environ Contam Toxicol        ISSN: 0007-4861            Impact factor:   2.151


  4 in total

1.  Comparison of seven in silico tools for evaluating of daphnia and fish acute toxicity: case study on Chinese Priority Controlled Chemicals and new chemicals.

Authors:  Linjun Zhou; Deling Fan; Wei Yin; Wen Gu; Zhen Wang; Jining Liu; Yanhua Xu; Lili Shi; Mingqing Liu; Guixiang Ji
Journal:  BMC Bioinformatics       Date:  2021-03-24       Impact factor: 3.169

2.  New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments.

Authors:  Cosimo Toma; Claudia I Cappelli; Alberto Manganaro; Anna Lombardo; Jürgen Arning; Emilio Benfenati
Journal:  Molecules       Date:  2021-11-19       Impact factor: 4.411

3.  Effects of Phthalate Esters (PAEs) on Cell Viability and Nrf2 of HepG2 and 3D-QSAR Studies.

Authors:  Huan Liu; Huiying Huang; Xueman Xiao; Zilin Zhao; Chunhong Liu
Journal:  Toxics       Date:  2021-06-05

4.  A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria.

Authors:  Dali Wang; Yue Gu; Min Zheng; Wei Zhang; Zhifen Lin; Ying Liu
Journal:  Sci Rep       Date:  2017-07-20       Impact factor: 4.379

  4 in total

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