Cho Chul-Woong, Yun Yeoung-Sang
School of Chemical Engineering, Chonbuk National University, 567 Beakje-dearo, Deokjin-gu, Jeonju, Jeonbuk 561-756, South Korea.
School of Chemical Engineering, Chonbuk National University, 567 Beakje-dearo, Deokjin-gu, Jeonju, Jeonbuk 561-756, South Korea.
Chemosphere. 2016 Jun;152:207-13. doi: 10.1016/j.chemosphere.2016.02.108. Epub 2016 Mar 9.
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 (S), H-bonding acidity (A), H-bonding basicity (B), McGowan volume (V), cation interaction (J(+)) and anion interaction (J(-)) - were in silico 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. Ec, Sc, Bc, Vc, and J(+). Secondly, a prediction model for only ILs was developed by using the three LFER descriptors Ec, Bc, 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.
离子液体(ILs)毒理学效应的计算机预测模型有助于理解ILs的毒理学相互作用,并设计对环境无害的IL结构。实际上,这是必不可少的,因为ILs的种类极其繁多。因此,本研究开发了预测模型。为了进行建模,使用密度泛函理论和类导体屏蔽模型在计算机上计算了定义明确的线性自由能关系(LFER)描述符,即过量摩尔折射(E)、偶极矩/极化率(S)、氢键酸度(A)、氢键碱度(B)、麦高恩体积(V)、阳离子相互作用(J(+))和阴离子相互作用(J(-))。然后将这些描述符与ILs对大型溞的毒理学值相关联。首先,将Hoover等人(2007年)使用97种中性化合物的实测LFER描述符建立的模型应用于ILs毒性的预测。正如预期的那样,Hoover等人(2007年)的模型需要针对ILs进行修正。为此,通过额外的单个J(+)或阳离子的五个LFER描述符Ec、Sc、Bc、Vc和J(+)来解决中性化合物和ILs之间毒理学相互作用的差异。其次,使用Ec、Bc和J(+)这三个LFER描述符开发了仅针对ILs的预测模型。该模型具有合理的预测能力和稳健性,训练集的R(2)=0.880,测试集的R(2)=0.848,总体集的R(2)=0.867。与基于实验的研究相比,所建立的模型可用于设计对环境无害的IL结构,并减少劳动力、危险、时间和材料。