An Electronic-structure Informatics Study on the Toxicity of Alkylphenols to Tetrahymena pyriformis

Abstract

Alkylphenols (APs) dissolved in water are known to be toxic to animals including humans. In this study, regression models describing the toxicity of the 33 AP molecules were investigated for reproducing and thereby making it possible to predict a quantitative structure-activity relationship (QSAR). For this purpose, we tried to derive regression models for the experimental IGC₅₀ (growth inhibition concentration at 50 %) to Tetrahymena pyriformis by using various descriptor sets consisting of electronic and shape descriptors. By applying the multiple linear regression (MLR) analysis, it was successful to derive a quantitative regression model for the IGC₅₀ values. In this analysis, the size parameters of the molecules were found important, suggesting that bulky molecules should be less toxic. We could also obtain, when the size descriptors were excluded, an MLR model indicating that the electron affinity (EA) should be important, which is consistent with the previous QSAR studies. Through the correlation analysis among the descriptors, it was shown that, in the present set of molecules, EA and a size parameter are highly correlated. Since EA was calculated to be negative, indicating that the related process would be energetically unfavourable, it was concluded that the size of the molecules should be a dominant factor determining IGC₅₀ . This implies that a molecular recognition process would play a critical role in the mode of action for the toxicity.

Keywords: DFT; QSAR; Tetrahymena pyriformis; electronic-structure informatics; toxicity.