Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
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Training | training | 70 | 0.951 | 0.271 |
Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
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Training | training | 12 | 0.931 | 0.286 |
Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
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Training | training | 8 | 0.854 | 0.302 |
Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
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Training | training | 11 | 0.875 | 0.278 |
Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
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Training | training | 50 | 0.856 | 0.319 |
When using this QDB archive, please cite (see details) it together with the original article:
Ruusmann, V. Data for: Comparison of Tetrahymena and Pimephales Toxicity Based on Mechanism of Action. QsarDB repository, QDB.73. 2012. https://doi.org/10.15152/QDB.73
Bearden, A. P.; Schultz, T. W. Comparison of Tetrahymena and Pimephales Toxicity Based on Mechanism of Action. SAR QSAR Environ. Res. 1998, 9, 127–153. https://doi.org/10.1080/10629369808039153
Title: | Bearden, A.P.; Schultz, T.W. Comparison of Tetrahymena and Pimephales Toxicity Based on Mechanism of Action. SAR QSAR Environ. Res. 1998, 9, 3-4, 127–153. |
Abstract: | The toxicity data of 256 chemicals tested in both the 96-h Pimephales promelas mortality assay and the 2-d Tetrahymena pyriformis growth inhibition assay were evaluated using quantitative structure-activity relationships (QSARs). Each chemical was a priori assigned a mode of action of either narcoses or soft electrophilicity. Narcoses were separated into nonpolar narcosis, polar narcosis, monoester narcosis, diester narcosis, amine narcosis, and weak acid respiratory uncoupling based on the presence or absence of specific toxicophores. Toxicity of each narcotic mechanism was initially regressed against the 1-octanol-water partition coefficient (log K(ow)). The slopes of these log K(ow) based QSARs were observed to ascertain whether a relationship exists between the value of the slope and the reactivity of the mechanism of action. With both the fish and ciliate data nonpolar narcosis was the least reactive mechanism. It was followed by the other reversible narcoses. The soft electrophile mode was separated into the specific molecular mechanisms of: SN2 reactors, Schiff-base formers, Michael-type addition, or proelectrophilicity (precursors to Michael-type addition chemicals). These mechanisms were represented structurally by the nitrobenzenes, aldehydes, polarized alpha-beta unsaturates (e.g., acrylates and methacrylates), and acetylenic alcohols, respectively. Electrophilic toxicity was not correlated with hydrophobicity. QSARs based on molecular orbital (MO) quantum chemical descriptors were used to improve the predictability of the electrophilic mechanisms. Relevant descriptors include average superdelocalizability (Svna) for the nucleophilic addition of the nitrobenzene; atom x and y acceptor superdelocalizability (Ax); and bond order (Bx y) for the Michael-type addition of the acrylates; and log K(ow) and atom x net charge (Qx) for the Schiff-base forming aldehydes. The pertinent descriptors for proelectrophiles were log K(ow) and Svna. Principal differences between the QSARs for the two biological endpoints were observed for the ester narcoses, proelectrophiles, and Schiff-base forming aldehydes. |
URI: | http://hdl.handle.net/10967/73
http://dx.doi.org/10.15152/QDB.73 |
Date: | 2012-05-23 |
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