ArticleBMC bioinformatics2021
Comparison of seven in silico tools for evaluating of daphnia and fish acute toxicity: case study on Chinese Priority Controlled Chemicals and new chemicals.
Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Toxicity evaluation and anti-ischemic stroke activity of selected natural extracts in zebrafish.Biomedical reports · 2026Article
- Activation of HJournal of environmental health science & engineering · 2025Article
- Exposure to marine contaminant mixtures with different toxicity drivers reduces microzooplankton diversity.FEMS microbiology ecology · 2025Article
- Simulation of Fish Acute Toxicity of Pharmaceuticals Using Simplified Molecular Input Line Entry System (SMILES) Notation as a Representation of Molecular Structure.International journal of molecular sciences · 2025Article
- Comparative study of (Q)SAR models for predicting the environmental fate of cosmetic ingredients: Persistence, bioaccumulation, and mobility.NAM journal · 2025Article
- Analysis of bacterial biodiversity and ecological risk evaluation of organophosphorus in Lianhuan Lake.PloS one · 2025Article
- Article
- Integrated Approach for Synthetic Cathinone Drug Prioritization and Risk Assessment: In Silico Approach and Sub-Chronic Studies inMolecules (Basel, Switzerland) · 2023Article
- Toxicity prediction and analysis of flavonoid apigenin as a histone deacetylase inhibitor: an in-silico approach.In silico pharmacology · 2023Article
- Potential Toxicity Risk Assessment and Priority Control Strategy for PAHs Metabolism and Transformation Behaviors in the Environment.International journal of environmental research and public health · 2022Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundA number of predictive models for aquatic toxicity are available, however, the accuracy and extent of easy to use of these in silico tools in risk assessment still need further studied. This study evaluated the performance of seven in silico tools to daphnia and fish: ECOSAR, T.E.S.T., Danish QSAR Database, VEGA, KATE, Read Across and Trent Analysis. 37 Priority Controlled Chemicals in China (PCCs) and 92 New Chemicals (NCs) were used as validation dataset.
resultsIn the quantitative evaluation to PCCs with the criteria of 10-fold difference between experimental value and estimated value, the accuracies of VEGA is the highest among all of the models, both in prediction of daphnia and fish acute toxicity, with accuracies of 100% and 90% after considering AD, respectively. The performance of KATE, ECOSAR and T.E.S.T. is similar, with accuracies are slightly lower than VEGA. The accuracy of Danish Q.D. is the lowest among the above tools with which QSAR is the main mechanism. The performance of Read Across and Trent Analysis is lowest among all of the tested in silico tools. The predictive ability of models to NCs was lower than that of PCCs possibly because never appeared in training set of the models, and ECOSAR perform best than other in silico tools.
conclusionQSAR based in silico tools had the greater prediction accuracy than category approach (Read Across and Trent Analysis) in predicting the acute toxicity of daphnia and fish. Category approach (Read Across and Trent Analysis) requires expert knowledge to be utilized effectively. ECOSAR performs well in both PCCs and NCs, and the application shoud be promoted in both risk assessment and priority activities. We suggest that distribution of multiple data and water solubility should be considered when developing in silico models. Both more intelligent in silico tools and testing are necessary to identify hazards of Chemicals.
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