Prediction Of Toxicity For Organic Pollutants To Fathead Minnow And Rat

Organic compounds are widely used in industrial production and life,and result in a large number of residues in the environment.Organic compounds can be transported and transformed through air,water,soil,sediment and other environmental media,which has potential threats to the health of animals,plants and human beings in the ecosystem.In order to strengthen the standardized use and safe disposal of organic compounds,it is necessary to evaluate their ecological toxicity and ecological risk.However,facing a large number of organic compounds,relying on animal experiments is not only time-consuming and laborious,but also contrary to the 3R principle of animal ethics.Quantitative structure-activity relationship(QSAR)is an important alternative method to fill the gaps in toxicity data of organic compounds.The QSAR method uses the molecular structure of organic compounds as a variable and establishes a computational model to predict the physical and chemical properties or biological activities of organic compounds.This method has played an important role In drug molecular design and environmental ecological assessment.This work is based on QSAR method to study the toxicity of organic pollutants to fathead minnow and rat.This work has important guiding significance for the environmental and ecological risk assessment of organic pollutants and the safe use of organic pollutants.In this paper,a new descriptor is proposed based on the molecular structure and atomic properties of organic compounds by using quantitative structure-activity relationship,and a QSAR regression model is established by stepwise regression method.In order to analyze the robustness and prediction ability of the model,cross validation,Y-random validation,external validation,mean absolute error and application domain were used to validate the model.The main results are as follows:[1]In this present study,the electronic affinity of atoms was proposed in our property matrices.As the basic atom property,the electronic affinity can reflect the gains or losses of electrons.Accordingly,it might be possible that the toxicity mechanism of organic compounds to fathead minnow pLC50 could be reflected indirectly to some extent.[2]Toxicity calculation of organic pollutants to fathead minnow.A series of norm descriptors were proposed to calculate the toxicity of organic pollutants to fathead minnow,and a QSAR model was established to calculate the toxicity of 685 organic pollutants to fathead minnow.The results show that the model established in this work can effectively predict the toxicity of organic pollutants to fathead minnow.The predicted value of the model is basically consistent with the experimental value.The correlation coefficient R2 of model is 0.8174,the correlation coefficient f of the training set and the test set is 0.8137 and 0.8117,respectively.The correlation coefficient Q2 of the left-one cross-validation method is 0.7923.The validation results show that the model has good accuracy and stability,and has a wide application area.[3]Toxicity calculation of organic pollutants in rat.A series of norm descriptors were proposed to calculate the toxicity of organic pollutants to rat,and a QSAR model was established to calculate the toxicity of 139 organic pollutants to rat.The results show that the model established in this work can effectively predict the toxicity of organic pollutants to rat.The predicted value of the model is basically in accordance with the experimental value.The correlation coefficient R2 of the whole model is 0.88,the correlation coefficient R2 of the training set and the test set is 0.88 and 0.87,respectively.The correlation coefficient Q2 of the left-one cross-validation method is 0.84.The validation results show that the accuracy and stability of the model are good.It has a wide range of applications.The results show that the new descriptor proposed in this paper can better reflect the toxicity mechanism of organic compounds to organisms on the ruacro level.The QSAR model constructed with other norm descriptors can predict the toxicity of organic pollutants to different organisms.Compared with the literature,the calculation accuracy of this work has been greatly improved.Therefore,the results of this study can achieve the ecological risk assessment of organic pollutants,and this method is expected to accurately predict the toxicity of various types of organic pollutants.