ENVIRONMENTAL

Daphnia pulex LC50 96h

Endpoint

The acute aquatic toxicity model predicts the concentration of chemicals that kill 50% (LC₅₀) of the test water flea Daphnia pulex within a designated period.

Data

The training set consists of LC₅₀ values for 23 chemicals [1]:

• Test duration - 96 hours,
• Test species - Daphnia pulex (water flea).

The tested chemicals belong to the categories of narcotic toxicants.

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 model was developed based on regression analysis of the data:

log 1/LC50 = 1.26(±0.41)+1.29(±0.14) logBCFmax -0.08(±0.08)E_LUMO 

where BCF_Max is the maximum bioconcentration factor [4], and E_LUMO is the energy of the lowest unoccupied molecular orbital.

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:

• 95% Confidence intervals of model parameters,
• Coefficient of determination R² = 0.87,
• Mean squared error (estimate of error variance) s² = 0.24,
• F value = 65.07,
• Number of chemicals, n = 22.

References

1. P. Ohe, R. Kuhne, R.U. Ebert, R. Altenburger, M. Liess, G. Schuurmann. Chem. Resear. Toxicol. (2005) 18(3): 536-555.
2. J. McFarland, J. Med. Chem. 13 (1970) 1092-1196.
3. S.Dimitrov, O.Mekenyan, G.Sinks, T.Schultz, Journal of Molecular Structure (Theochem), 622 (2003) 63-70.
4. S. Dimitrov, N. Dimitrovaa, 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.