4.7 Article

Correlating toxicological effects of ionic liquids on Daphnia magna with in silico calculated linear free energy relationship descriptors

Journal

CHEMOSPHERE
Volume 152, Issue -, Pages 207-213

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2016.02.108

Keywords

LFER; Daphnia magna; Toxicity; Prediction; Ionic liquids

Funding

  1. National Research Foundation of Korea (NRF) Grant - Korean Government (MSIP) [2014R1A2A1A09007378, 2014R1A1A2008337]
  2. National Research Foundation of Korea [2014R1A1A2008337] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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In silico prediction model for toxicological effects of ionic liquids (ILs) is useful to understand ILs' toxicological interactions and to design environmentally benign IL structures. Actually, it is essential since the types of ILs are extremely numerous. Accordingly, prediction models were developed in this study. For the modelling, well-defined linear free energy relationship (LFER) descriptors - i.e. excess molar refraction (E), dipolarity/polarizability (5), H-bonding acidity (A), H-bonding basicity (B), McGowan volume (V), cation interaction (J(+)) and anion interaction (J(-))- were in silica calculated using density functional theory and conductor-like screening model. These descriptors were then correlated with the toxicological values of ILs to Daphnia magna. First, a model established by Hoover et al. (2007) using measured LFER descriptors of 97 neutral compounds was applied to the prediction of ILs' toxicity. As expected, the model by Hoover et al. (2007) needs to be amended for ILs. To that end, the difference in toxicological interactions between neutral compounds and ILs was addressed by additional single J(+) or five LFER descriptors of cation i.e. E-c, S-c, B-c, V-c, and J(+). Secondly, a prediction model for only ILs was developed by using the three LFER descriptors E-c, B-c, and J+. The model had a reasonable predictability and robustness of R-2 = 0.880 for the training set, 0.848 for the test set, and 0.867 for the overall set. The established models can be used to design environmentally benign IL structures and to reduce labour, danger, time, and materials compared to the experiment-based study. (C) 2016 Elsevier Ltd. All rights reserved.

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