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Acute toxicity estimation by calculation--Tubifex assay and quantitative structure-activity relationships

M. Tichy, M. Rucki, I. Hanzlikova, Z. Roth

. 2008 ; 27 (11) : 2281-2286.

Language English Country United States

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NLK ProQuest Central from 2005-01-01 to 2009-12-31
Health & Medicine (ProQuest) from 2005-01-01 to 2009-12-31
Public Health Database (ProQuest) from 2005-01-01 to 2009-12-31

A quantitative structure-activity relationship (QSAR) model dependent on log P(n - octanol/water), or log P(OW), was developed with acute toxicity index EC50, the median effective concentration measured as inhibition of movement of the oligochaeta Tubifex tubifex with 3 min exposure, EC50(Tt) (mol/L): log EC50(Tt) = -0.809 (+/-0.035) log P(OW) - 0.495 (+/-0.060), n=82, r=0.931, r2=0.867, residual standard deviation of the estimate 0.315. A learning series for the QSAR model with the oligochaete contained alkanols, alkenols, and alkynols; saturated and unsaturated aldehydes; aniline and chlorinated anilines; phenol and chlorinated phenols; and esters. Three cross-validation procedures proved the robustness and stability of QSAR models with respect to the chemical structure of compounds tested within a series of compounds used in the learning series. Predictive ability was described by q2 .801 (cross-validated r2; predicted variation estimated with cross-validation) in LSO (leave-a structurally series-out) cross-validation.

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$a A quantitative structure-activity relationship (QSAR) model dependent on log P(n - octanol/water), or log P(OW), was developed with acute toxicity index EC50, the median effective concentration measured as inhibition of movement of the oligochaeta Tubifex tubifex with 3 min exposure, EC50(Tt) (mol/L): log EC50(Tt) = -0.809 (+/-0.035) log P(OW) - 0.495 (+/-0.060), n=82, r=0.931, r2=0.867, residual standard deviation of the estimate 0.315. A learning series for the QSAR model with the oligochaete contained alkanols, alkenols, and alkynols; saturated and unsaturated aldehydes; aniline and chlorinated anilines; phenol and chlorinated phenols; and esters. Three cross-validation procedures proved the robustness and stability of QSAR models with respect to the chemical structure of compounds tested within a series of compounds used in the learning series. Predictive ability was described by q2 .801 (cross-validated r2; predicted variation estimated with cross-validation) in LSO (leave-a structurally series-out) cross-validation.
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