Regression model (regression)
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Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training | training | 197 | 0.817 | 0.334 |
Validation | external validation | 20 | 0.975 | 0.146 |
When using this QDB archive, please cite (see details) it together with the original article:
Ruusmann, V. Data for: Structure-Toxicity Relationships for Benzenes Evaluated with Tetrahymena pyriformis. QsarDB repository, QDB.19. 2012. https://doi.org/10.15152/QDB.19
Schultz, T. W. Structure-Toxicity Relationships for Benzenes Evaluated with Tetrahymena pyriformis. Chem. Res. Toxicol. 1999, 12, 1262–1267. https://doi.org/10.1021/tx9900730
Title: | Schultz, T.W. Structure-Toxicity Relationships for Benzenes Evaluated with Tetrahymena pyriformis. Chem. Res. Toxicol. 1999, 12, 12, 1262–1267. |
Abstract: | Toxicity data for 200 substituted benzenes tested in the two-day Tetrahymena pyriformis population growth impairment assay representing the neutral narcosis, polar narcosis, respiratory uncoupling, and weak and strong electrophilic mechanisms of toxic action were evaluated. A quantitative structure-toxicity model correlating toxic potency [log(IGC(50)(-)(1))] with hydrophobicity quantified by the 1-octanol/water partition coefficient (log K(ow)) and electrophilic reactivity quantified by the molecular orbital parameter, maximum superdelocalizability (S(max)), was developed. This model [log(IGC(50)(-)(1)) = 0.50(log K(ow)) + 9.85(S(max)) - 3.47; n = 197, r(2) = 0.816, s = 0.34, F = 429, Pr > F = 0.0001] allows for the prediction of acute potency without the a priori identification of the mechanism of action. The examination of residuals reveals that neutral narcotics with high volatility (e.g., methyl- and chloro-substituted benzenes) and highly reactive fluoro- and nitro-containing derivatives are fitted poorly. A comparison of observed (obs) and predicted (pred) toxicities on the additional set of derivatives [log(obs IGC(50)(-)(1)) = 1.05[log(pred IGC(50)(-)(1))] + 0.02; n = 20, r(2) = 0.979, s = 0.13, F = 825, Pr > F = 0.0001] validated the model as a good predictor of toxicity regardless of the mechanism of toxic action. |
URI: | http://hdl.handle.net/10967/19
http://dx.doi.org/10.15152/QDB.19 |
Date: | 2012-05-23 |
Name | Description | Format | Size | View |
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tx9900730.qdb.zip | n/a | application/zip | 10.37Kb | View/ |