Quantitative Structure-Property Relationships Study Of Some Persistent Organic Pollutants

Persistent Organic Pollutants (POPs) are chemical substances that persist in the environment, bioaccumulate through the food web, and pose a risk of causing adverse effects to human health and the environment. POPs are often halogenated and characterized by low water solubility and high lipid solubility. They are also semi-volatile, a property which permits these compounds either to vaporize or to be adsorbed on atmospheric particles. They therefore undergo long range transport in air and water from warmer to colder regions of the world.Quantitative structure-property relationship (QSPR) is a cross subject covering chemistry, biology, mathematics and computer science etc and has become an active frontier field in environmental science. QSPR study has become an important means for appraising ecological risk of organic pollutants and can be used to predict transference, transformation and distribution behavior for them in environment. Quantum chemistry calculation is an important method to obtain molecular structural parameter in QSPR study of POPs.In this thesis, QSPR study were carried out for some typical POPs in environment such as polychlorinated diphenyl ethers (PCDEs), polybrominated diphenyl ethers (PBDEs), polychlorinated dibenzo-p-dioxins (PCDDs) and substituted naphthalenes. Density Functional Theory (DFT) method was used to optimize the geometries of 209 PCDE molecules, 209 PBDE molecules and 75 PCDD molecules at the B3LYP/6-31G* level. Using computed structural parameters as theoretical descriptors, the forward stepwise multiple regression technique was adopted to obtain QSPR models of environmental partition properties for these POPs by using GQSARF 2.0 and SPSS12.0 for windows programs. The obtained QSPR models are as follows:(1) QSPR models for predicting subcooled liquid vapor pressure (lgP_L), n-octanol/water partition coefficients (lgK_ow) and subcooled liquid water solubilities (-lgS_w,l) of PCDEs, of which correlative coefficients (R²) are 0.988, 0.958 and 0.959 and the root-mean-square-error of estimation (RMSEE) are 0.134, 0.116 and 0.327 respectively.(2) QSPR models of lgPL and n-octanol/air partition coefficients (lgK_oa) for PBDEs, which both contain three structural parameters (q-,μandα). The values of R2 for the two models are both 0.997 while the values of RMSEE are 0.073 and 0.062 respectively.(3) QSPR models of lgKow and–lgS_w,l for PCDEs, which both have one variable (mean molecular polarizability,α). The values of R² for the two models are 0.978 and 0.866 and the values of RMSEE are 0.300 and 0.270 respectively. (4) The molecular structures of 24 substituted naphthaline compounds were optimized using Hartree-Fock and DFT methods at four different levels and the same means was used to obtain four three-parameter (EHOMO, q⁺ andα) QSPR models of lgK_ow. The model at the HF/6-311G** level is the best one of which R2 is 0.9662 and RMSEE is 0.380.(5) QSPR study for environmental partition properties of PCDEs was also performed using position of Cl substitution (PCS) method in which simple parameters of substitution position were taken as descriptors. The multiple linear regression was performed with GQSARF 2.0 and SSPS 12.0 for windows programs to obtain QSPR models of lgP_L, lgK_ow and–lgS_w,l for PCDEs of which R² are 0.991, 0.983 and 0.965 and RMSEE are 0.311, 0.100 and 0.300 respectively.All of these models have high R² and low RMSEE values which indicate that they have high estimation power of model. Statistical test and appraisal for the obtained models were performed with LOO cross-validation, t-test, F-test or variation inflation factors (VIF). The results indicated that all of these models have good correlation and stability and can be used to predict properties of POPs and infer interaction mechanism.The researches also showed that the model established using new method of Cl substitution can be compared with that by DFT method, both may be used to predict physico-chemical properties of studied compounds. The difference between two methods is that the former is simpler while physical meaning of the parameters for the latter is more explicit. In addition, by comparing the results of our models with those reported in literatures, our QSPR models are more excellent than those by PM3 or connection index method etc.