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Updated: Jul 2, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Prediction of toxicity of phenols and anilines to algae by quantitative structure-activity relationship
Guang-Hua Lu1, Chao Wang, Xiao-Ling Guo
1State Key Laboratory for Hydrology-water Resources and Hydraulic Engineering, College of Environmental Science and Engineering, Hohai University, Nanjing 210098, Jiangsu, China.
Objective:
To measure the toxicity of phenol, aniline, and their derivatives to algae and to assess, model, and predict the toxicity using quantitative structure-activity relationship (QSAR) method.
Methods:
Oxygen production was used as the response endpoint for assessing the toxic effects of chemicals on algal photosynthesis. The energy of the lowest unoccupied molecular orbital (E(LUMO)) and the energy of the highest occupied molecular orbital (E(HOMO)) were obtained from the ChemOffice 2004 program using the quantum chemical method MOPAC, and the frontier orbital energy gap (deltaE) was obtained.
Results:
The compounds exhibited a reasonably wide range of algal toxicity. The most toxic compound was alpha-naphthol, whereas the least toxic one was aniline. A two-descriptor model was derived from the algal toxicity and structural parameters: log1/EC50 = 0.268,logKow - 1.006deltaE + 11.769 (n = 20, r2 = 0.946). This model was stable and satisfactory for predicting toxicity. CONCLUSION Phenol, aniline, and their derivatives are polar narcotics. Their toxicity is greater than estimated by hydrophobicity only, and addition of the frontier orbital energy gap deltaE can significantly improve the prediction of logKow-dependent models.
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