QSAR study of aromatic compounds toxicity to Chlorella vulgaris

As demands for energy have increased worldwide, oil has become the main pollutant of the ocean. The impact of aromatic compounds, which are primary pollutants in oil, on various marine ecosystems has become a growing concern. Establishing a quantitative structure–activity relationship (QSAR) model to predict the toxicity of unknown aromatic compounds may thus serve as an important pollution-preventive measure. In this study, 21 aromatic compounds, 15 of which served as a training set and 6 as a test set, were selected. The structural parameters of the compounds were obtained by multiple linear regression, and a 2-descriptor prediction model was established. The test set was used to determine the predictive ability of the model. The model built using the proposed method showed satisfactory statistical results (R = 0.974 vs. the test set R = 0.804). These data show that the model provides good predictability and stability and can thus be used to predict the inhibitory effect of aromatic compounds on Chlorella vulgaris.