Suppr超能文献

定量构效-生物降解关系(QSBR)方法预测芳香族化学品的生物降解速率。

A quantitative structure-biodegradation relationship (QSBR) approach to predict biodegradation rates of aromatic chemicals.

机构信息

School of Engineering, Cassie Building, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom.

School of Engineering, Cassie Building, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom.

出版信息

Water Res. 2019 Jun 15;157:181-190. doi: 10.1016/j.watres.2019.03.086. Epub 2019 Mar 28.

Abstract

The objective of this work was to develop a QSBR model for the prioritization of organic pollutants based on biodegradation rates from a database containing globally harmonized biodegradation tests using relevant molecular descriptors. To do this, we first categorized the chemicals into three groups (Group 1: simple aromatic chemicals with a single ring, Group 2: aromatic chemicals with multiple rings and Group3: Group 1 plus Group 2) based on molecular descriptors, estimated the first order biodegradation rate of the chemicals using rating values derived from the BIOWIN3 model, and finally developed, validated and defined the applicability domain of models for each group using a multiple linear regression approach. All the developed QSBR models complied with OECD principles for QSAR validation. The biodegradation rate in the models for the two groups (Group 2 and 3 chemicals) are associated with abstract molecular descriptors that provide little relevant practical information towards understanding the relationship between chemical structure and biodegradation rates. However, molecular descriptors associated with the QSBR model for Group 1 chemicals (R = 0.89, Q = 0.87) provided information on properties that can readily be scrutinised and interpreted in relation to biodegradation processes. In combination, these results lead to the conclusion that QSBRs can be an alternative tool to estimate the persistence of chemicals, some of which can provide further insights into those factors affecting biodegradation.

摘要

这项工作的目的是开发一个基于具有相关分子描述符的全球协调生物降解试验数据库中的生物降解速率对有机污染物进行优先级排序的定量构效关系(QSBR)模型。为此,我们首先根据分子描述符将化学品分为三组(第 1 组:具有单个环的简单芳香族化学品,第 2 组:具有多个环的芳香族化学品,第 3 组:第 1 组加第 2 组),使用源自 BIOWIN3 模型的评分值估算化学品的一级生物降解速率,最后使用多元线性回归方法为每组开发、验证和定义模型的适用性域。所有开发的 QSBR 模型都符合 OECD 定量构效关系验证原则。模型中两组(第 2 组和第 3 组化学品)的生物降解速率与抽象分子描述符相关联,这些描述符几乎没有提供有关理解化学结构与生物降解速率之间关系的相关实用信息。然而,与第 1 组化学品 QSBR 模型相关的分子描述符(R=0.89,Q=0.87)提供了有关性质的信息,这些信息可以很容易地与生物降解过程相关联进行审查和解释。综合这些结果得出的结论是,QSBR 可以作为一种替代工具来估计化学品的持久性,其中一些可以进一步深入了解影响生物降解的因素。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验