Henan Engineering Research Center of Industrial, Circulating Water TreatmentInstitution, Henan University, Kaifeng, 475004, China.
Henan Joint International Research Laboratory of environmental pollution control materials, Henan University, Kaifeng, 475004, China.
Mol Inform. 2020 Oct;39(10):e2000102. doi: 10.1002/minf.202000102. Epub 2020 Jul 9.
Ionic liquids as green solvents have been paid extensive attention in recent years. However, mostly it is cost and time-consuming to measure their properties. Thus, theorical methods, especially ultrafast chemoinformatics methods were introduced into these studies. Instead of abstract and complex models in some QSPR studies, in this study, the 2D structural features related to the toxicity of ionic liquids were discussed at first, and then the corresponding intuitive and meaningful descriptors were suggested to construct quantitative chemoinformatics models, finally a multiple linear regression (MLR) based on the empirical-like models were applied to the estimation of toxicities of 304 ionic liquids. For the test sets, the relationship coefficients reached up to R=0.90. An external test set of 11 ionic liquids collected from other literatures was submitted to the achieved MLR equations, and the satisfactory result (R=0.94) was obtained.
近年来，离子液体作为绿色溶剂受到了广泛关注。然而，测量它们的性质通常既耗时又费成本。因此，理论方法，尤其是超快 chemoinformatics 方法被引入到这些研究中。与一些 QSPR 研究中抽象复杂的模型不同，在这项研究中，首先讨论了与离子液体毒性相关的二维结构特征，然后提出了相应直观有意义的描述符来构建定量 chemoinformatics 模型，最后基于经验模型的多元线性回归（MLR）被应用于 304 种离子液体毒性的估计。对于测试集，相关系数高达 R=0.90。从其他文献中收集的 11 种离子液体的外部测试集被提交到所获得的 MLR 方程中，得到了令人满意的结果（R=0.94）。
