Literature DB >> 24773472

Discriminating toxicant classes by mode of action: 4. Baseline and excess toxicity.

M Nendza1, M Müller, A Wenzel.   

Abstract

Functional similarity of chemicals combines toxicological knowledge (which toxicity pathways can happen in which species under which exposure conditions) with chemical expertise (which parts of the chemical structures and physico-chemical properties are involved in which interactions) to discriminate between baseline and excess toxicants. The objective is to identify as many baseline toxicants as possible because their acute fish toxicities can be predicted with sufficient accuracy from their log Kow. Established tools like structural alerts are used to indicate modes of action (MOAs) that are typical causes of excess toxicity. Verhaar classifications are supplemented with additional chemical attributes and physico-chemical property thresholds to cover a larger range of compounds within the baseline toxicity domain. Our approach is precautionary to avoid false negatives with a sensitivity of 96.3%. It classifies 57.1% of the compounds of the EPA Fathead Minnow Acute Toxicity Database (EPAFHM) as baseline toxicants and suggests that more than 50% of acute fish toxicity testing could be replaced by reliable QSAR predictions. Furthermore, functional similarity can support the MOA classification of chemicals in different species. Toxicity profiles with fish, Daphnia and algae reveal specific targets for the compounds and, particularly for chemicals with multiple MOA, identify the most sensitive species.

Entities:  

Keywords:  QSAR; fish toxicity; mode of action (MOA) classification; reactive substructures; similarity

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Year:  2014        PMID: 24773472     DOI: 10.1080/1062936X.2014.907205

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  2 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

Review 2.  Environmental Metabolomics Promises and Achievements in the Field of Aquatic Ecotoxicology: Viewed through the Pharmaceutical Lens.

Authors:  Thibaut Dumas; Frédérique Courant; Hélène Fenet; Elena Gomez
Journal:  Metabolites       Date:  2022-02-17
  2 in total

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