通过高通量建模优先考虑通过非目标分析确定的分子配方:用于从室内灰尘中识别具有高人体积累潜力的化合物
Zhizhen Zhang1,2, Li Li1,2, Hui Peng3
1Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, Toronto, Ontario, Canada M1C 1A4. frank.wania@utoronto.ca.
Environmental science. Processes & impacts
|October 16, 2023
概括
从环境样本中优先考虑化学结构至关重要. 这项研究引入了一种新的方法,根据其生物积累潜力对化学特征进行排序,有助于识别有关室内污染物的污染物.
科学领域:
- 环境化学环境化学
- 毒理学 毒理学 毒理学
- 计算化学计算化学
背景情况:
- 非目标分析 (NTA) 产生了众多化学特征,需要优先确定识别.
- 由于资源有限,所有检测到的化学物质的阐明结构往往是不可行的.
- 优先级策略对于将识别工作集中在潜在关注的化合物上至关重要.
研究的目的:
- 开发和验证环境样本中检测到的化学特征的排名策略.
- 根据它们对人类或野生动物的潜在生物积累,优先阐明化学结构.
- 用拟议的优先级工作流确定已知的室内污染物.
主要方法:
- 开发了一个模型衍生度量来量化阐明化学特征结构的可取性.
- 在NTA中检测到的分子配方的异构体是使用PubChem数据库识别的.
- 优先级指标,如剂量与度比 (DCR),是使用预测的物理化学性质来计算的.
- 量化结构与属性关系 (QSPR) 被用于属性预测.
主要成果:
- 工作流成功地根据预测的属性对分子公式进行了排名.
- 应用在室内尘埃样本中,在排名第一的配方中确定了已知的室内污染物.
- 排名第一的配方包括聚化二乙烯,四甲酸盐以及特定的阻燃剂和染料.
- DCR指标有效地突出了具有高生物积累潜力的化合物.
结论:
- 拟议的战略提供了一种有效的方法,可以从NTA数据中优先考虑化学结构.
- 这种方法有助于识别具有潜在毒理意义的环境污染物.
- 工作流程有助于明确目标结构,提高环境监测和风险评估的效率.
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