#### Leuciscus idus LC50 96h

Endpoint

The acute aquatic toxicity (AAT) model predicts the
concentration of chemicals that kill 50% (*LC _{50}*)
of the test fish

*Leuciscus idus*within a designated period.

Data

The training set consists of *LC _{50}* values for
141 chemicals [1]:

- Test duration - 96 hours,
- Test species -
*Leuciscus idus*(ide).

The tested chemicals belong to the following categories:

- Narcotic toxicants - 60 chemicals,
- Phenols and anilines - 10 chemicals,
- Reactive unspecified chemicals - 57 chemicals.

Model

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 [2]. 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 [3]. 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:

Narcotic toxicants

Phenols and anilines

where *BCF*_{Max} is the maximum bioconcentration
factor [4], and *E*_{LUMO} 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).

Domain

The stepwise approach [5] 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
*K*_{OW}and*MW*, - Structural domain - based on atom-centered fragments (ACFs).

A chemical is considered *In Domain* if its log
*K*_{OW} 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.

Statistics

The precision of the regression model is characterized by the
following estimates - the 95% confidence intervals of model
parameters, coefficient of determination (*R ^{2}*),
mean squared error (estimate of error variance,

*s*), F value:

^{2}

Narcotic toxicants

- Coefficient of determination
*R*= 0.71,^{2} - Mean squared error (estimate of error variance)
*s*= 0.39,^{2} *F*value = 68.84,- Number of chemicals,
*n*= 60.

Phenols and anilines

- Coefficient of determination
*R*= 0.76,^{2} - Mean squared error (estimate of error variance)
*s*= 0.14,^{2} *F*value = 11.30,- Number of chemicals,
*n*= 10.

References

** **

- 1. Estimating environmentally important properties of chemicals from the chemical structure - Erik Furusjo, Magnus Andersson, Magnus Rahmberg, Anders Svenson - Report B1517.
- 2. J.W. McFarland, J. Med. Chem. 13 (1970) 1092-1196.
- 3. S.D. Dimitrov, O.G. Mekenyan, G.D. Sinks, T.W. Schultz, Journal of Molecular Structure (Theochem), 622 (2003) 63-70.
- 4. S. Dimitrov, N. Dimitrova, D. Georgieva, K. Vasilev, T. Hatfield, J. Straka, O. Mekenyan, SAR and QSAR in Environmental Research, 23 (2012) 17-36.
- 5. S. Dimitrov, G. Dimitrova, T. Pavlov, N. Dimitrova, G. Patlevisz, J. Niemela and O. Mekenyan, J. Chem. Inf. Model. 45 (2005) 839-849.