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  • 标题:Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors
  • 本地全文:下载
  • 作者:Chul-Woong Cho ; Stefan Stolte ; Yeoung-Sang Yun
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2016
  • 卷号:6
  • 期号:1
  • DOI:10.1038/srep33403
  • 语种:English
  • 出版社:Springer Nature
  • 摘要: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.
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