Departement de sante environnementale et sante au travail, Faculte de medecine, Universite de Montreal, PQ, Canada.
SAR QSAR Environ Res. 2011 Mar;22(1-2):107-28. doi: 10.1080/1062936X.2010.548350.
The objective of this study was to predict the inhalation toxicokinetics of chemicals in mixtures using an integrated QSAR-PBPK modelling approach. The approach involved: (1) the determination of partition coefficients as well as V(max) and K(m) based solely on chemical structure for 53 volatile organic compounds, according to the group contribution approach; and (2) using the QSAR-driven coefficients as input in interaction-based PBPK models in the rat to predict the pharmacokinetics of chemicals in mixtures of up to 10 components (benzene, toluene, m-xylene, o-xylene, p-xylene, ethylbenzene, dichloromethane, trichloroethylene, tetrachloroethylene, and styrene). QSAR-estimated values of V(max) varied compared with experimental results by a factor of three for 43 out of 53 studied volatile organic compounds (VOCs). K(m) values were within a factor of three compared with experimental values for 43 out of 53 VOCs. Cross-validation performed as a ratio of predicted residual sum of squares and sum of squares of the response value indicates a value of 0.108 for V(max) and 0.208 for K(m). The integration of QSARs for partition coefficients, V(max) and K(m), as well as setting the K(m) equal to K(i) (metabolic inhibition constant) within the mixture PBPK model allowed to generate simulations of the inhalation pharmacokinetics of benzene, toluene, m-xylene, o-xylene, p-xylene, ethylbenzene, dichloromethane, trichloroethylene, tetrachloroethylene and styrene in various mixtures. Overall, the present study indicates the potential usefulness of the QSAR-PBPK modelling approach to provide first-cut evaluations of the kinetics of chemicals in mixtures of increasing complexity, on the basis of chemical structure.
本研究旨在采用整合的定量构效关系-生理药代动力学(QSAR-PBPK)建模方法预测混合物中化学物质的吸入毒代动力学。该方法包括:(1)根据基团贡献法,仅基于化学结构确定 53 种挥发性有机化合物的分配系数以及 Vmax 和 Km;(2)将 QSAR 驱动系数用作输入,在大鼠基于相互作用的 PBPK 模型中预测多达 10 种成分(苯、甲苯、间二甲苯、对二甲苯、邻二甲苯、乙苯、二氯甲烷、三氯乙烯、四氯乙烯和苯乙烯)混合物中化学物质的药代动力学。QSAR 估算的 Vmax 值与 53 种研究挥发性有机化合物(VOCs)中的 43 种相比,差异为实验结果的三倍。K m 值与 53 种 VOCs 中的 43 种相比,在实验值的三倍以内。作为预测残差平方和与响应值平方和的比值进行的交叉验证表明,Vmax 的值为 0.108,Km 的值为 0.208。QSAR 用于分配系数、Vmax 和 Km 的整合,以及在混合物 PBPK 模型中将 Km 设置为 K i(代谢抑制常数),使得可以模拟苯、甲苯、间二甲苯、对二甲苯、邻二甲苯、乙苯、二氯甲烷、三氯乙烯、四氯乙烯和苯乙烯在各种混合物中的吸入药代动力学。总体而言,本研究表明,QSAR-PBPK 建模方法具有潜在的有用性,可以基于化学结构,对日益复杂的混合物中化学物质的动力学进行初步评估。