Global versus local QSAR models for predicting ionic liquids toxicity against IPC-81 leukemia rat cell line: the predictive ability

Anita Sosnowska , Monika Grzonkowska , Tomasz Puzyn

Abstract

The unlimited possibility of modifying the structure of the cation and anion of a given ionic liquid (IL) delivers a countless number of potential derivatives having different toxicological activities. The experimental measurements for such huge set of compounds are impossible due to time and costs limitations. In the absence of experimental data, computational methods such as quantitative structure–activity relationship (QSAR) method can be applied to characterize those species for which experimental data is not available. However, two different ways of QSAR modeling could be applied: local modeling - dedicating to one specific group and more complex global models. The aim of this study was to investigate how local/global QSAR modeling works for the ionic liquids. Which of these two approaches is more suitable in ILs' modeling? We have developed six local models and a global one for predicting the toxicity against the leukemia rat cell line IPC-81. Based on the obtained results, we conclude that local models are useful to solve specific mechanistic problems among one group of ILs, but in case of predicting the toxicity for a new designed compound the global model, whenever fulfills all quality recommendations, is recommended.
Author Anita Sosnowska PChŚ
Anita Sosnowska,,
- Laboratory of Environmental Chemometrics
, Monika Grzonkowska PChŚ
Monika Grzonkowska,,
- Laboratory of Environmental Chemometrics
, Tomasz Puzyn PChŚ
Tomasz Puzyn,,
- Laboratory of Environmental Chemometrics
Other language title versions
Journal seriesJournal of Molecular Liquids, ISSN 0167-7322
Issue year2017
Vol231
Pages333-340
Publication size in sheets0.5
Keywords in Englishglobal models, local model, QSAR, ionic liquids, toxicity against the leukemia rat cell line IPC-81
DOIDOI:10.1016/j.molliq.2017.02.025
URL http://doi.org/10.1016/j.molliq.2017.02.025
Languageen angielski
Score (nominal)30
ScoreMinisterial score = 30.0, 20-12-2017, ArticleFromJournal
Ministerial score (2013-2016) = 30.0, 20-12-2017, ArticleFromJournal
Publication indicators WoS Impact Factor: 2016 = 3.648 (2) - 2016=3.187 (5)
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