Abstract
In order to evaluate the toxicity of several different ionic liquids (ILs) towards the leukemia rat cell line (ICP-81), an efficient and reliable quantitative structure-activity relationships (QSAR) model is developed based on descriptors from COSMO-SAC (conductor-like screening model for segment activity coefficient) model. The distribution of screen charge density (σ-profile) of 127 ILs is calculated by GC-COSMO (group contribution based COSMO) method. Two segmentation methods toward σ-profile are used to find out the appropriate descriptors for the QSAR model. The optimal subset of descriptors is obtained by enhanced replacement method (ERM). A multiple linear regression (MLR) and multilayer perceptron technique (MLP) are used to build the linear and nonlinear models, respectively, and the applicability domain of the models is assessed by the Williams plot. It turns out that the nonlinear model based the second segmentation method (MLP-2) is the best QSAR model with an R2=0.975, MSE=0.019 for the training set and R2=0.938, MSE=0.037 for the test set. The reliability and robustness of the presented QSAR models are confirmed by Leave-One-Out (LOO) cross and external validations.
Highlights
The σ-profile of 127 ionic liquids (ILs) are calculated by Group Contribution (GC)-COSMO method and the corresponding descriptors are acquired by two segmentation methods
The reliability of the selected descriptors is validated by detailed analysis of the relationship between the structure and the toxicity of ILs and cation is found to have a major effect on the toxicity of ILs
Based on the chosen descriptors, linear and nonlinear quantitative structure-activity relationships (QSAR) models are established to estimate the toxicity of 127 ILs towards IPC-81
Summary
With their unique properties, such as negligible vapor pressure, high thermal, chemical stability and wide liquid-phase range, ionic liquids (ILs) have been researched for a diverse range of technologies and applications, including gas capture and separation (Bates et al, 2002; Chen et al, 2015), extraction (Lyu et al, 2014; Song et al, 2016; Wlazło et al, 2017; Zhou et al, 2012), organic synthesis (Eshetu et al, 2016; Sanchez Zayas et al, 2016), etc. In order to find environmentally friendly ILs for different using purposes, evaluation of their toxicity has become very important
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