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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Predicted health and environmental hazards of liquid crystal materials via quantitative structure-property
Jing-Jing Feng1, Xiang-Fei Sun1, Eddy Y Zeng2
1Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China.
Abstract:
Liquid crystal materials (LCMs) are considered as emerging contaminants with high persistent and bioaccumulative potentials, but their toxicological effects are not well understood. To address this issue, a list of 1431 LCMs commercially available in the market was established through literature reviews and surveys of LCM suppliers. Toxicological properties of 221 target LCMs were derived from the Classification and Labeling Inventory by the European Chemicals Agency. More than 80 % of target LCMs likely pose adverse effects on human health or aquatic ecosystems. Two quantitative structure-property relationship (QSPR) models developed from the toxicological properties of LCMs achieved approximately 90 % accuracy in external data sets. The probability-based approach was more efficient in defining the applicability domain for the QSPR models than a range- or distance-based approach. The highest accuracy was achieved for chemicals within the probability-based applicability domain. The QSPR models were applied to predict health and environmental hazards of 1210 LCMs that had not been notified to the Classification and Labeling Inventory, and 301 and 94 LCMs were recognized as posing potential hazards to human health and the environment, respectively. The present study highlights the potential detrimental effects of LCMs and offers a specific in silico technique for screening hazardous LCMs.

