A Semi-Empirical Quantum Chemical Computational Study Of Acute Toxicity Of Substituted Benzene Compounds To Aquatic Organisms

An increasing number of toxic pollutants in the environment, especially the type and quantity of the substituted benzene compounds have posed a great threat to the ecological environment and human health, and how to evaluate the toxic effects of the substituted benzene compounds on the environment has caught intensive academic attention. Quantitative structure-activity relationship toxicity study is an important method to investigate the molecular characteristics by studying the molecular structural features of its toxicity, physicochemical properties and the regular patterns of biological activities.Based on the semi-empirical quantum chemical methods, the present research first studied the internal quantitative relationship between26substituted benzene compounds with zebra fish48h acute toxicity (-lgLC50), and by applying the AMI quantum chemical calculation, the correlation between8typical quantum chemical parameters and zebra fish48h-lgLC50was also calculated. Through the stepwise multiple linear regression (MLR) method, a QSAR model is set up depicting the relationship between substituted benzene compounds and48h-lgLC50’ on zebra fish, tested by internal and external validations; the internal quantitative relationship between60substituted benzene compounds and40kinds of nitrobenzene compounds with fathead minnow of96h-lgLC50was calculated. AMI and PM3semi-empirical quantum chemistry calculation were conducted with structural parameters. Using QSAR model studies the substituted benzene compounds quantum chemistry parameters to aquatic organisms48h-lgLC50influence.The results indicate that:the strongest correlation parameter with the zebra fish-lgLCso is n-octanol-water partition coefficient (Log/3), and the electronegativity [-(L+H)/2] is negatively correlated with zebra fish-lgLC50, and the strongest affect with fathead minnow-lgLC50is molecular weight (MW), the PM3method is superior to AMI method when calculating the heat of formation descriptor. The obtained QSAR model shows good robustness and high predictive ability, and can be used to predict the acute toxicity of substituted benzene compounds on aquatic organisms.