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Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors
The challenge and opportunity for design of environmentally-benign ionic liquids (ILs) would start from prediction of their toxicological effects on several endpoints solely based on the structural formulas. Especially, a comprehensive yet simple equation able to predict several biological responses...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5022054/ https://www.ncbi.nlm.nih.gov/pubmed/27624396 http://dx.doi.org/10.1038/srep33403 |
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author | Cho, Chul-Woong Stolte, Stefan Yun, Yeoung-Sang |
author_facet | Cho, Chul-Woong Stolte, Stefan Yun, Yeoung-Sang |
author_sort | Cho, Chul-Woong |
collection | PubMed |
description | The challenge and opportunity for design of environmentally-benign ionic liquids (ILs) would start from prediction of their toxicological effects on several endpoints solely based on the structural formulas. Especially, a comprehensive yet simple equation able to predict several biological responses to IL toxicity is of much advantage. Therefore, based on 50 toxicity testing systems on ILs a comprehensively approachable prediction method was developed. For the modelling, approximately 1600 toxicity values measured by several biological systems and an amended linear free energy relationship (LFER) model were used. Since the toxicological activities of an IL could be differently described according to sensitivity of toxicity testing systems, the sensitivity of each of toxicity testing systems was also estimated in the modelling. By statistical analysis with the calculated descriptors, a LFER model was built. Also the sensitivity value of each system on the basis of the comprehensively approachable model was numerically estimated. In results, it was observed that the combination of single model and sensitivity terms was able to predict each of 50 toxicological effects of ILs with R(2) of 0.593~0.978, and SE of 0.098~0.699 log unit, and the total data set with R(2) of 0.901 and SE of 0.426 log unit. |
format | Online Article Text |
id | pubmed-5022054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-50220542016-09-20 Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors Cho, Chul-Woong Stolte, Stefan Yun, Yeoung-Sang Sci Rep Article The challenge and opportunity for design of environmentally-benign ionic liquids (ILs) would start from prediction of their toxicological effects on several endpoints solely based on the structural formulas. Especially, a comprehensive yet simple equation able to predict several biological responses to IL toxicity is of much advantage. Therefore, based on 50 toxicity testing systems on ILs a comprehensively approachable prediction method was developed. For the modelling, approximately 1600 toxicity values measured by several biological systems and an amended linear free energy relationship (LFER) model were used. Since the toxicological activities of an IL could be differently described according to sensitivity of toxicity testing systems, the sensitivity of each of toxicity testing systems was also estimated in the modelling. By statistical analysis with the calculated descriptors, a LFER model was built. Also the sensitivity value of each system on the basis of the comprehensively approachable model was numerically estimated. In results, it was observed that the combination of single model and sensitivity terms was able to predict each of 50 toxicological effects of ILs with R(2) of 0.593~0.978, and SE of 0.098~0.699 log unit, and the total data set with R(2) of 0.901 and SE of 0.426 log unit. Nature Publishing Group 2016-09-14 /pmc/articles/PMC5022054/ /pubmed/27624396 http://dx.doi.org/10.1038/srep33403 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Cho, Chul-Woong Stolte, Stefan Yun, Yeoung-Sang Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors |
title | Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors |
title_full | Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors |
title_fullStr | Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors |
title_full_unstemmed | Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors |
title_short | Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors |
title_sort | comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5022054/ https://www.ncbi.nlm.nih.gov/pubmed/27624396 http://dx.doi.org/10.1038/srep33403 |
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