Unveil the quantum chemical descriptors determining direct photodegradation of antibiotics under simulated sunlight: Batch experiments and model development - Yitao Lyu; Taobo Huang; Liu, Wen; Sun, Weiling (Journal of Environmental Chemical Engineering, 2022)
The massive use of antibiotics has led to their omnipresence in aquatic environments, and the photodegradation was found to be the dominant transformation process for antibiotics in the natural river system. Herein, we investigated the photodegradation kinetics of 77 antibiotics in 7 classes in water under simulated sunlight. Using the quantum chemical descriptors predicted by the density functional theory calculation, the quantitative structure-activity relationship (QSAR) models were established to explore the main chemical descriptors determining the photodegradation of antibiotics. The results showed that the photodegradation kinetics of antibiotics conformed to the pseudo-first order kinetic model. The photodegradation rate constants of different antibiotics varied 4 orders of magnitude, and the photodegradation rate constants of quinolones were significantly higher than those for other classes of antibiotics due to the F atoms in their molecular structures. The developed QSAR models revealed that the energy gap (Egap) between ELUMO and EHOMO was the main chemical descriptor determining the photodegradation of antibiotics, and it was negatively correlated with lgk. In addition, the number of F atom was also included in the QSAR models due to the great contribution of F atom to the direct photolysis of quinolones. This study ordered the photodegradation rate constants of 77 antibiotics, and revealed the major chemical descriptors determining the photodegradation of antibiotics. The results provide the basic information for the photolysis of antibiotics, which is significant for predicting the environmental behaviors and evaluating the ecological risks of antibiotics in aquatic environments.
Keywords: Antibiotics; DFT calculation; Photodegradation; Quantitative structure-activity relationship (QSAR)