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Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method
Alternative TitleJ. Hazard. Mater.
Zhao, Yongsheng1,2; Zhao, Jihong2; Huang, Ying1; Zhou, Qing1; Zhang, Xiangping1; Zhang, Suojiang1
2014-08-15
Source PublicationJOURNAL OF HAZARDOUS MATERIALS
ISSN0304-3894
Volume278Issue:AUG.Pages:320-329
AbstractA comprehensive database on toxicity of ionic liquids (ILs) is established. The database includes over 4000 pieces of data. Based on the database, the relationship between IL's structure and its toxicity has been analyzed qualitatively. Furthermore, Quantitative Structure Activity relationships (QSAR) model is conducted to predict the toxicities (EC50 values) of various ILs toward the Leukemia rat cell line IPC-81. Four parameters selected by the heuristic method (HM) are used to perform the studies of multiple linear regression (MLR) and support vector machine (SVM). The squared correlation coefficient (R-2) and the root mean square error (RMSE) of training sets by two QSAR models are 0.918 and 0.959, 0.258 and 0.179, respectively. The prediction R-2 and RMSE of QSAR test sets by MLR model are 0.892 and 0.329, by SVM model are 0.958 and 0.234, respectively. The nonlinear model developed by SVM algorithm is much outperformed MLR, which indicates that SVM model is more reliable in the prediction of toxicity of ILs. This study shows that increasing the relative number of O atoms of molecules leads to decrease in the toxicity of ILs. (C) 2014 Elsevier B.V. All rights reserved.; A comprehensive database on toxicity of ionic liquids (ILs) is established. The database includes over 4000 pieces of data. Based on the database, the relationship between IL's structure and its toxicity has been analyzed qualitatively. Furthermore, Quantitative Structure Activity relationships (QSAR) model is conducted to predict the toxicities (EC50 values) of various ILs toward the Leukemia rat cell line IPC-81. Four parameters selected by the heuristic method (HM) are used to perform the studies of multiple linear regression (MLR) and support vector machine (SVM). The squared correlation coefficient (R-2) and the root mean square error (RMSE) of training sets by two QSAR models are 0.918 and 0.959, 0.258 and 0.179, respectively. The prediction R-2 and RMSE of QSAR test sets by MLR model are 0.892 and 0.329, by SVM model are 0.958 and 0.234, respectively. The nonlinear model developed by SVM algorithm is much outperformed MLR, which indicates that SVM model is more reliable in the prediction of toxicity of ILs. This study shows that increasing the relative number of O atoms of molecules leads to decrease in the toxicity of ILs. (C) 2014 Elsevier B.V. All rights reserved.
KeywordQsar Multiple Linear Regression (Mlr) Support Vector Machine (Svm) Toxicity Ionic Liquids
SubtypeArticle
WOS HeadingsScience & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1016/j.jhazmat.2014.06.018
URL查看原文
Indexed BySCI
Language英语
WOS KeywordSTRUCTURE-PROPERTY RELATIONSHIP ; SUPPORT VECTOR MACHINES ; PHYSICAL-PROPERTIES ; VIBRIO-FISCHERI ; PHYSICOCHEMICAL PROPERTIES ; QSPR CORRELATION ; NEURAL-NETWORKS ; MELTING-POINTS ; DAPHNIA-MAGNA ; CELL-LINE
WOS Research AreaEngineering ; Environmental Sciences & Ecology
WOS SubjectEngineering, Environmental ; Engineering, Civil ; Environmental Sciences
WOS IDWOS:000340689100038
Citation statistics
Cited Times:96[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Version出版稿
Identifierhttp://ir.ipe.ac.cn/handle/122111/11628
Collection研究所(批量导入)
Affiliation1.Chinese Acad Sci, Inst Proc Engn, Beijing Key Lab Ion Liquids Clean Proc, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China
2.Zhengzhou Univ Light Ind, Sch Mat & Chem Engn, Zhengzhou 450001, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Yongsheng,Zhao, Jihong,Huang, Ying,et al. Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method[J]. JOURNAL OF HAZARDOUS MATERIALS,2014,278(AUG.):320-329.
APA Zhao, Yongsheng,Zhao, Jihong,Huang, Ying,Zhou, Qing,Zhang, Xiangping,&Zhang, Suojiang.(2014).Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method.JOURNAL OF HAZARDOUS MATERIALS,278(AUG.),320-329.
MLA Zhao, Yongsheng,et al."Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method".JOURNAL OF HAZARDOUS MATERIALS 278.AUG.(2014):320-329.
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