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Fish acute toxicity syndromes and their use in the QSAR approach to hazard assessment
Open accessAbstract
Implementation of the Toxic Substances Control Act of 1977 creates the need to reliably establish testing priorities because laboratory resources are limited and the number of industrial chemicals requiring evaluation is overwhelming. The use of quantitative structure activity relationship (QSAR) models as rapid and predictive screening tools to select more potentially hazardous chemicals for in-depth laboratory evaluation has been proposed. Further implementation and refinement of quantitative structure-toxicity relationships in aquatic toxicology and hazard assessment requires the development of a "mode-of-action" database. With such a database, a qualitative structure-activity relationship can be formulated to assign the proper mode of action, and respective QSAR, to a given chemical structure. In this review, the development of fish acute toxicity syndromes (FATS), which are toxic-response sets based on various behavioral and physiological-biochemical measurements, and their projected use in the mode-of-action database are outlined. Using behavioral parameters monitored in the fathead minnow during acute toxicity testing, FATS associated with acetylcholinesterase (AChE) inhibitors and narcotics could be reliably predicted. However, compounds classified as oxidative phosphorylation uncouplers or stimulants could not be resolved. Refinement of this approach by using respiratory-cardiovascular responses in the rainbow trout, enabled FATS associated with AChE inhibitors, convulsants, narcotics, respiratory blockers, respiratory membrane irritants, and uncouplers to be correctly predicted.
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“QSPR modeling is based on the statistical analysis of the data sets and has been frequently used in the field of medicinal chemistry and chemical toxicology for the prediction of efficacy and/or toxicity of small molecules [220].”
From Polymeric micelles for the delivery of poorly soluble drugs: From nanoformulation to clinical approval. (2020) · cites this paper as [220]
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Classifying environmental pollutants
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“QSPR modeling is based on the statistical analysis of the data sets and has been frequently used in the field of medicinal chemistry and chemical toxicology for the prediction of efficacy and/or toxicity of small molecules [220].”
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Metadata
- Authors
- McKim, J. M., Bradbury, S. P., & Niemi, G. J.
- Affiliations
- Environmental Protection Agency (US)
- Venue
- Environmental Health Perspectives
- Publisher
- American Chemical Society (ACS)
- Published
- 1987-04
- Volume
- 71
- Pages
- 171-186
- ISSN
- 0091-6765 (ISSN-L)
- 1552-9924
- PMC
- PMC1474360
- OpenAlex
- W1975650851
- Cited by
- 210
- References
- 84
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 5 · 2023: 5 · 2022: 3 · 2021: 8 · 2020: 3 · 2019: 3 · 2018: 12 · 2017: 11 · 2016: 5 · 2015: 6 · 2014: 2 · 2013: 4
- FWCI
- 2.50
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- public-domain
- Locations
- Environmental Health Perspectives (publishedVersion, public-domain)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Environmental Toxicology and Ecotoxicology
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Environmental Science › Environmental Chemistry › Environmental Chemistry and Analysis
- Keywords
- QSAR, hazard assessment, fathead minnow, rainbow trout, acetylcholinesterase inhibitors, narcotics, convulsants, aquatic toxicology, compound screening, Toxic Substances Control Act
- MeSH terms
- Animals, Fishes, Lethal Dose 50, Structure-Activity Relationship, Water Pollutants, Water Pollutants, Chemical
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