Estimating the Depuration Rates of PCDD/Fs in American Oyster (Crassostrea virginica) with Quantum Chemical Descriptors
Using quantum chemical descriptors and partial least squares (PLS) regression,a quantitative activity-property relationship (QSAR) model was developed to predict the depuration rate constants (kd) of tetra-,penta-,hexa-,hepta-chlorinated dibenzo-p-dioxins and dibenzofurans in the American oyster (Crassostrea virginica).The cross-validated Q2cum and standard deviation (SD) are 0.701 and 0.096 respectively,indicating good predictive ability of the optimal model.Since the significant descriptors of EHOMOELUMO,EHOMO and QC-are all able to quantify hydrogen-bonding ability of PCDD/Fs,the depuration of PCDD/Fs chlorinated by 4 to 7 chlorines may be mainly attributed to some biota-water partitioning or biotabiota partitioning processes.While for the model with the physicochemical parameter of log Kow,the low squared correlation coefficient suggests that the mechanism of biota-water partitioning or biota-biota partitioning is different from the liquid-liquid partitioning.Mechanisms other than lipid solubility might exist in the depuration of tetra-,penta-,hexa-,hepta-chlorinated dibenzo-p-dioxins and dibenzofurans in oysters.
QSAR Depuration PCDD/Fs Quantum chemical descriptors Oysters
Lei Wang Xinhui Liu Zhengjun Shan Lili Shi
Nanjing Institute of Environmental Sciences/Key laboratory of Pesticide Environmental Assessment and State Key Laboratory of Water Environment Simulation,School of Environment,Beijing Normal University
国际会议
Conference on Environmental Pollution and Public Health (2012年环境污染与大众健康学术会议(CEPPH2012))
上海
英文
453-458
2012-08-09（万方平台首次上网日期，不代表论文的发表时间）