Knowledge Management System Of Institute of process engineering,CAS
| Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method | |
| Alternative Title | J. Hazard. Mater. |
| Zhao, Yongsheng1,2; Zhao, Jihong2; Huang, Ying1; Zhou, Qing1; Zhang, Xiangping1; Zhang, Suojiang1 | |
| 2014-08-15 | |
| Source Publication | JOURNAL OF HAZARDOUS MATERIALS
 |
| ISSN | 0304-3894 |
| Volume | 278Issue:AUG.Pages:320-329 |
| Abstract | 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.; 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. |
| Keyword | Qsar Multiple Linear Regression (Mlr) Support Vector Machine (Svm) Toxicity Ionic Liquids |
| Subtype | Article |
| WOS Headings | Science & Technology ; Technology ; Life Sciences & Biomedicine |
| DOI | 10.1016/j.jhazmat.2014.06.018 |
| URL | 查看原文 |
| Indexed By | SCI |
| Language | 英语 |
| WOS Keyword | STRUCTURE-PROPERTY RELATIONSHIP ; SUPPORT VECTOR MACHINES ; PHYSICAL-PROPERTIES ; VIBRIO-FISCHERI ; PHYSICOCHEMICAL PROPERTIES ; QSPR CORRELATION ; NEURAL-NETWORKS ; MELTING-POINTS ; DAPHNIA-MAGNA ; CELL-LINE |
| WOS Research Area | Engineering ; Environmental Sciences & Ecology |
| WOS Subject | Engineering, Environmental ; Engineering, Civil ; Environmental Sciences |
| WOS ID | WOS:000340689100038 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Version | 出版稿 |
| Identifier | http://ir.ipe.ac.cn/handle/122111/11628 |
| Collection | 研究所（批量导入） |
| Affiliation | 1.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. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Toxicity of ionic li（964KB） | 限制开放 | CC BY-NC-SA | Application Full Text | |||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment