期刊
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
卷 35, 期 11, 页码 2691-2697出版社
WILEY-BLACKWELL
DOI: 10.1002/etc.3466
关键词
Computational toxicology; Ecological risk assessment; Environmental toxicology; Aquatic toxicology; Organic contaminant
资金
- European Commission [686141]
- Ministry of Education and Science, the Republic of Serbia [43012]
- National Science Foundation [NSF/CREST HRD-0833178]
- EPSCoR [362492-190200-01/NSFEPS-090378]
- Division Of Human Resource Development
- Direct For Education and Human Resources [1547754] Funding Source: National Science Foundation
- Office Of The Director
- EPSCoR [0903787] Funding Source: National Science Foundation
Quantitative structure-activity relationships (QSARs) for toxicity of a large set of 758 organic compounds to Daphnia magna were built up. The simplified molecular input-line entry system (SMILES) was used to represent the molecular structure. The Correlation and Logic (CORAL) software was utilized as a tool to develop the QSAR models. These models are built up using the Monte Carlo method and according to the principle QSAR is a random event if one checks a group of random distributions in the visible training set and the invisible validation set. Three distributions of the data into the visible training, calibration, and invisible validation sets are examined. The predictive potentials (i.e., statistical characteristics for the invisible validation set of the best model) are as follows: n = 87, r(2) = 0.8377, root mean square error = 0.564. The mechanistic interpretations and the domain of applicability of built models are suggested and discussed. (C) 2016 SETAC
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