Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
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Training | training | 203 | 0.592 | 0.485 |
Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training | training | 203 | 0.694 | 0.420 |
Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training | training | 198 | 0.649 | 0.432 |
Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training | training | 193 | 0.775 | 0.353 |
When using this QDB archive, please cite (see details) it together with the original article:
Ruusmann, V. Data for: Parametrization of Electrophilicity for the Prediction of the Toxicity of Aromatic Compounds. QsarDB repository, QDB.9. 2012. https://doi.org/10.15152/QDB.9
Cronin, M. T. D.; Manga, N.; Seward, J. R.; Sinks, G. D.; Schultz, T. W. Parametrization of Electrophilicity for the Prediction of the Toxicity of Aromatic Compounds. Chem. Res. Toxicol. 2001, 14, 1498–1505. https://doi.org/10.1021/tx015502k
Title: | Cronin, M.T.D.; Manga, N.; Seward, J.R.; Sinks, G.D.; Schultz, T.W. Parametrization of Electrophilicity for the Prediction of the Toxicity of Aromatic Compounds. Chem. Res. Toxicol. 2001, 14, 11, 1498–1505. |
Abstract: | The aim of this study was to determine which descriptor best parametrized the electrophilicity of aromatic compounds with regard to their acute toxicity. To achieve this, toxicity data for 203 substituted aromatic compounds containing a nitro- or cyano group were evaluated in the 40-h Tetrahymena pyriformis population growth impairment assay. Quantitative structure-activity relationships (QSARs) were developed relating toxic potency [log(IGC(50)(-1))] with hydrophobicity quantified by the 1-octanol/water partition coefficient (log P) and electrophilic reactivity quantified by the molecular orbital parameters, either the energy of the lowest unoccupied molecular orbital (E(LUMO)) or maximum acceptor superdelocalizability (A(max)) was developed. For the full data set, E(LUMO) and A(max) were collinear (r = 0.87). A comparison of the QSARs [log(IGC(50)(-1)) = 0.40 log P - 0.94E(LUMO) - 1.27; n = 203, r(2) = 0.60, s = 0.49, F = 151] and [log(IGC(50)(-1)) = 0.37 log P + 13.1A(max) - 4.30; n = 203, r(2) = 0.70, s = 0.42, F = 237] reveals A(max) to be the better electrophilic parameter for modeling these data. Analysis of outliers indicates a preponderance of 4-subsituted nitrophenols and nitroanilines. Smaller datasets (51 and 102 compounds) selected in order to reduce the collinearity between A(max) and E(LUMO) were also evaluated. Results indicate A(max) to be the superior descriptor of electrophilicity for the purpose of toxicological QSARs for aromatic compounds. Development of QSARs using partial least-squares yielded similar results. |
URI: | http://hdl.handle.net/10967/9
http://dx.doi.org/10.15152/QDB.9 |
Date: | 2012-05-23 |
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tx015502k.qdb.zip | n/a | application/zip | 15.67Kb | View/ |