Study Of Quantitative Structure-Activity Relationship Models For Bioconcentration Factors Of Organic Pollutants

Bioconcentration factor(BCF) is an important ecotoxicological parameter charactering the bioaccumulation of chemicals in organisms.It is commonly used to assess the hazard and risk of new and existing substances,such as persistent organic pollutants(POPs) and persistent,bioaccumulative and toxic(PBT) substances.Many researchers developed BCF predictive methods by the methodology of quantitative structure-activity relationship(QSAR). In environmental science,QSAR are mathematical models that explore the inherent relations between molecular structures of chemicals and their physicochemical properties, environmental behavioral and ecotoxicological parameters.Thus,QSAR can fill in the data gap of organic pollutants,decrease experimental expenses and especially reduce animal testing.The guidelines for development and validation of QSAR models proposed by the Organization for Economic Co-operation and Development(OECD) were followed.In this study,QSAR model for fish BCFs of 8 groups of compounds was developed employing stepwise regression,based on Abraham linear solvation energy relationship(LSER) descriptors.For the established model,the correlation coefficient square adjusted for the degrees of freedom(R²_adj)=0.818,the standard error(SE)=0.662 log units,and the cross-validated Q²_CV=0.797,indicating its good goodness-of-fit and robustness.In order to further improve the model prediction accuracy,QSAR model for fish BCF of 8 groups of compounds was developed employing partial least squares(PLS) regression,based on LSER theory and theoretical molecular structural descriptors.The model results shows that the main factors governing logBCF are Connolly molecular area(CMA),average molecular polarizability(α) and molecular weight(MW).Thus molecular size plays a critical role in affecting the bioconcentration of organic pollutants in fish.The bigger the molecular size is, the more energy is needed to overcome the cohesive interactions of solvent molecules to form a cavity for the solute molecules.As the cohesive interactions for water molecules are stronger than lipid molecules,the compounds with big molecular size tend to be enriched in the lipid phase.Moreover,compounds that have have larger electrostatic basicity(accept protons more easily) and thus exist more easily in water phase.For the established model,the multiple correlation coefficient square(R²_Y)=0.868,the root mean square error(RMSE)= 0.553 log units,and the leave-many-out cross-validated Q²_CUM=0.860,indicating its good goodness-of-fit and robustness.The model predictivity was evaluated by external validation, with the external explained variance(Q²_EXT)=0.755 and RMSE=0.647 log units.Moreover, the applicability domain of the developed model was assessed and visualized by the Williams plot.The developed QSAR model can be used to predict fish logBCF for organic chemicals within the application domain.