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探讨辛醇-水分配系数和亨利定律常数在预测有机化学品的脂水分配系数中的作用。

Exploring the role of octanol-water partition coefficient and Henry's law constant in predicting the lipid-water partition coefficients of organic chemicals.

机构信息

Institute of Environmental Science and Engineering (IESE), School of Civil and Environmental Engineering (SCEE), National University of Sciences and Technology (NUST), Islamabad, H-12, Pakistan.

Environment and Agriculture Laboratory, School of Interdisciplinary Engineering and Sciences (SINES), National University of Sciences and Technology (NUST), Islamabad, H-12, Pakistan.

出版信息

Sci Rep. 2022 Sep 2;12(1):14936. doi: 10.1038/s41598-022-19452-6.

DOI:10.1038/s41598-022-19452-6
PMID:36056200
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9440013/
Abstract

Partition coefficients for storage lipid-water (logK) and phospholipid-water (logK) phases are key parameters to understand the bioaccumulation and toxicity of organic contaminants. However, the published experimental databases of these properties are dwarfs and current estimation approaches are cumbersome. Here, we present partition models that exploit the correlations of logK, and of logK with the linear combinations of the octanol-water partition coefficient (logK) and the dimensionless Henry's law constant (air-water partition coefficient, logK). The calibrated partition models successfully describe the variations in logK data (n = 305, R = 0.971, root-mean-square-error (rmse) = 0.375), and in logK data (n = 131, R = 0.953, rmse = 0.413). With the inputs of logK and logK estimated from the U.S. EPA's EPI Suite, our models of logK and logK have exhibited rmse = 0.52 with respect to experimental values indicating suitability of these models for inclusion in the EPI Suite. Our models perform similar to or better than the previously reported models such as one parameter partition models, Abraham solvation models, and models based on quantum-chemical calculations. Taken together, our models are robust, easy-to-use, and provide insight into variations of logK and logK in terms of hydrophobicity and volatility trait of chemicals.

摘要

分配系数是用于存储脂质-水(logK)和磷脂-水(logK)相的关键参数,可用于理解有机污染物的生物累积和毒性。然而,这些性质的已发表实验数据库规模较小,且当前的估算方法繁琐。在这里,我们提出了利用 logK 以及 logK 与辛醇-水分配系数(logK)和无量纲亨利定律常数(空气-水分配系数,logK)的线性组合的相关性的分配模型。经过校准的分配模型成功地描述了 logK 数据(n=305,R=0.971,均方根误差(rmse)=0.375)和 logK 数据(n=131,R=0.953,rmse=0.413)的变化。利用美国环保署 EPI 套件中估算的 logK 和 logK,我们的 logK 和 logK 模型相对于实验值的 rmse 为 0.52,表明这些模型适合纳入 EPI 套件。我们的模型与以前报告的模型(如单参数分配模型、Abraham 溶剂化模型和基于量子化学计算的模型)的性能相似或更好。总之,我们的模型稳健、易于使用,并提供了有关化学物质疏水性和挥发性特征的 logK 和 logK 变化的深入了解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df8a/9440013/7e9cb5bb2d8b/41598_2022_19452_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df8a/9440013/321b78336c1c/41598_2022_19452_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df8a/9440013/7e9cb5bb2d8b/41598_2022_19452_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df8a/9440013/321b78336c1c/41598_2022_19452_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df8a/9440013/7e9cb5bb2d8b/41598_2022_19452_Fig2_HTML.jpg

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