Escherichia coli EC50
The Acute Aquatic Toxicity (AAT) model predicts the effect concentration of a substance that causes growth inhibition on 50% (EC50) of the test bacterium Escherichia coli within a designated period.
The training set consists of EC50 values for 80 chemicals [1, 2].
- Test duration - 12 hours,
- Test species - Escherichia coli.
The tested chemicals belong to the following categories:
- Narcotic toxicants - 14 chemicals,
- Phenols and anilines - 44 chemicals,
- Reactive unspecified chemicals - 16 chemicals.
The organism response to the presence of toxicant in the environment is considered as a consequence of the combined influence of two different processes: uptake of the chemical into the biophase and interaction with the site of action . In the present model, the uptake is modeled by maximum potential of the toxicant to bioconcentrate in the fish, while the interaction of chemicals is explained by descriptors assessing the electrophilic character of the molecule . Such descriptors could include the energy of the lowest unoccupied molecular orbital, electronegativity, average or maximum superdelocalizability, maximum charge at non-hydrogen atom, etc. The following models were developed based on regression analysis of the data:
log 1/EC50 = 0.85(±0.26)+0.88(±0.16)logBCFmax -0.07(±0.07) ELUMO
Phenols and anilines
log 1/EC50 = 1.76(±0.12)+0.69(±0.07) logBCFmax -0.31(±0.08)ELUMO
where BCFMax is the maximum bioconcentration factor , and ELUMO is the energy of the lowest unoccupied molecular orbital. For the reactive unspecified chemicals, only the minimum toxicity is determined based on the model for narcotic chemicals (i.e., log 1/EC50 ≥ log 1/EC50 of narcotics).
The stepwise approach  was used to define the applicability domain of the model. It consists of the following sub-domain levels:
- General parametric requirements - includes ranges of variation of log KOW and MW,
- Structural domain - based on atom-centered fragments (ACFs).
A chemical is considered In Domain if its log KOW and MW are within the specified ranges and its ACFs are presented in the training chemicals. The information implemented in the applicability domain is extracted from the correctly predicted training chemicals used to build the model and in this respect the applicability domain determines practically the interpolation space of the model.
The precision of the regression model is characterized by the following estimates - the 95% confidence intervals of model parameters, coefficient of determination (R2), mean squared error (estimate of error variance, s2), F value:
- Coefficient of determination R2 = 0.82,
- Mean squared error (estimate of error variance) s2 = 0.09,
- F value = 24.59,
- Number of chemicals, n = 14.
Phenols and anilines
- Coefficient of determination R2 = 0.77,
- Mean squared error (estimate of error variance) s2 = 0.10,
- F value = 69.44,
- Number of chemicals, n = 44.
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