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Schüürmann, G.; Aptula, A.O.; Kühne, R.; Ebert, R.U. Stepwise Discrimination between Four Modes of Toxic Action of Phenols in the Tetrahymena pyriformis Assay. Chem. Res. Toxicol. 2003, 16, 8, 974–987.

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Schüürmann, G.; Aptula, A.O.; Kühne, R.; Ebert, R.U. Stepwise Discrimination between Four Modes of Toxic Action of Phenols in the Tetrahymena pyriformis Assay. Chem. Res. Toxicol. 2003, 16, 8, 974–987.

QDB archive DOI: 10.15152/QDB.12   DOWNLOAD

QsarDB content

Property MOA: Mode of action

Compounds: 220 | Models: 0 | Predictions: 0

Property logIGC50: 2-day Tetrahymena toxicity as log(IGC50) [log(mol/L)]

Compounds: 220 | Models: 4 | Predictions: 4

13: Polar narcosis

Regression model (regression)

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Name Type n

R2

σ

Training training 153 0.775 0.379
14: Oxidative uncouping

Regression model (regression)

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Name Type n

R2

σ

Training training 19 0.735 0.429
15: Polar narcosis

Regression model (regression)

Open in:QDB Explorer QDB Predictor

Name Type n

R2

σ

Training training 153 0.804 0.354
16: Polar narcosis

Regression model (regression)

Open in:QDB Explorer QDB Predictor

Name Type n

R2

σ

Training training 153 0.802 0.356

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Title: Schüürmann, G.; Aptula, A.O.; Kühne, R.; Ebert, R.U. Stepwise Discrimination between Four Modes of Toxic Action of Phenols in the Tetrahymena pyriformis Assay. Chem. Res. Toxicol. 2003, 16, 8, 974–987.
Abstract: For a set of 220 phenols with literature data on their toxicity and associated mode of action (MOA) toward the ciliate Tetrahymena pyriformis, a stepwise classification scheme was developed that allows the identification of four MOAs from molecular hydrophobicity and AM1-based quantum chemical descriptors, employing linear discriminant analysis or binary logistic regression. Taking the AM1 lowest unoccupied molecular orbital energy as the only parameter, an initial separation of polar narcotics and proelectrophiles from oxidative uncouplers and soft electrophiles is correct to 97%, and for the subsequent discrimination between polar narcotics and proelectrophiles as well as between oxidative uncouplers and soft electrophiles, 99 and 98% correct classifications are achieved using three and two molecular descriptors, respectively. The results are discussed in terms of detailed contingency table statistics and with respect to relationships between molecular descriptors and mechanisms of toxicity. Statistical model evaluation includes simulated external validation employing complementary subset models.
URI: http://hdl.handle.net/10967/12
http://dx.doi.org/10.15152/QDB.12
Date: 2012-05-23


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