Consensus QSAR models estimating acute toxicity to aquatic organisms from different trophic levels: algae, Daphnia and fish. Issue 9 (1st September 2020)

• Record Type: Journal Article
• Authors: Lunghini, F.; Marcou, G.; Azam, P.; Enrici, M.H.; Van Miert, E.; Varnek, A.
• Is Part Of: SAR and QSAR in environmental research. Volume 31:Issue 9(2020)
• Page Start: 655
• Page End: 675
• Publication Date: 2020-09-01
• Subjects: QSAR/QSPR -- acute aquatic toxicity -- generative topographic mapping (GTM) -- REACH; Structure-activity relationships (Biochemistry) -- Periodicals; QSAR (Biochemistry) -- Periodicals; 572.4
• DOI: 10.1080/1062936X.2020.1797872
• Languages: English
• ISSNs: 1062-936X

Abstract

ABSTRACT: We report new consensus models estimating acute toxicity for algae, Daphnia and fish endpoints. We assembled a large collection of 3680 public unique compounds annotated by, at least, one experimental value for the given endpoint. Support Vector Machine models were internally and externally validated following the OECD principles. Reasonable predictive performances were achieved (RMSEext = 0.56–0.78) which are in line with those of state-of-the-art models. The known structural alerts are compared with analysis of the atomic contributions to these models obtained using the ISIDA/ColorAtom utility. A benchmarking against existing tools has been carried out on a set of compounds considered more representative and relevant for the chemical space of the current chemical industry. Our model scored one of the best accuracy and data coverage. Nevertheless, industrial data performances were noticeably lower than those on public data, indicating that existing models fail to meet the industrial needs. Thus, final models were updated with the inclusion of new industrial compounds, extending the applicability domain and relevance for application in an industrial context. Generated models and collected public data are made freely available.