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Overview of data and conceptual approaches for derivation of quantitative structure‐activity relationships for ecotoxicological effects of organic chemicals
Author(s) -
Bradbury Steven P.,
Russom Christine L.,
Ankley Gerald T.,
Schultz T. Wayne,
Walker John D.
Publication year - 2003
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1897/01-234
Subject(s) - quantitative structure–activity relationship , aquatic toxicology , organic chemicals , biochemical engineering , computer science , environmental chemistry , chemistry , machine learning , toxicity , engineering , organic chemistry
The use of quantitative structure‐activity relationships (QSARs) in assessing potential toxic effects of organic chemicals on aquatic organisms continues to evolve as computational efficiency and toxicological understanding advance. With the ever‐increasing production of new chemicals, and the need to optimize resources to assess thousands of existing chemicals in commerce, regulatory agencies have turned to QSARs as essential tools to help prioritize tiered risk assessments when empirical data are not available to evaluate toxicological effects. Progress in designing scientifically credible QSARs is intimately associated with the development of empirically derived databases of well‐defined and quantified toxicity endpoints, which are based on a strategic evaluation of diverse sets of chemical structures, modes of toxic action, and species. This review provides a brief overview of four databases created for the purpose of developing QSARs for estimating toxicity of chemicals to aquatic organisms. The evolution of QSARs based initially on general chemical classification schemes, to models founded on modes of toxic action that range from nonspecific partitioning into hydrophobic cellular membranes to receptor‐mediated mechanisms is summarized. Finally, an overview of expert systems that integrate chemical‐specific mode of action classification and associated QSAR selection for estimating potential toxicological effects of organic chemicals is presented.