通过使用定量结构-活性关系和物种敏感度分布 (QSAR-SSD) 来推导帕奎特,双A和卡巴马西平的水质标准

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Ya-Qian Xu¹, Peng Huang², Xiang-Wei Li¹

¹School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.

The Science of the total environment

|July 15, 2024

概括

定量结构-活性关系 (QSAR) 模型预测水生物种的毒性,有助于制定水质标准. 这种具有成本效益的方法支持对新兴污染物的风险评估,如酸和双A.

科学领域:

环境毒理学环境毒理学
生态毒理学生态毒理学
计算化学是一种计算化学.

背景情况:

种类敏感度分布 (SSD) 对于水生生态系统风险评估和水质标准至关重要.
固态硬盘需要大量的多性毒性数据,这往往是昂贵的和耗时的实验性获得.
新出现的污染物对水生环境构成越来越大的风险,需要有效的评估方法.

研究的目的:

开发可靠的定量结构-活性关系 (QSAR) 模型来预测水生物质的毒性.
利用预测的毒性数据来构建物种灵敏度分布 (SSD) 模型.
为了获得帕奎特,双甲和碳胺的慢性水质标准.

主要方法:

开发了使用部分最小平方 (PLS) 算法和留出一个 (LOO) 交叉验证的QSAR模型.
对四种水生物种的预测毒性数据:Rana pipiens,Crassostrea virginica,Aselus aquaticus和Lepomis macrochirus. 这四种水生物种的预测毒性数据包括:
将预测数据与实验数据整合起来,以构建SSD模型并确定5%物种的危险度 (HC5).

主要成果:

成功开发了QSAR模型,能够预测特定水生物种的毒性数据.
衍生的慢性水质标准: 6.7 微克/升的帕奎特, 11.1 微克/升的双甲,和 3.5 微克/升的卡巴马泽.
在构建SSD和建立监管基准时证明了预测数据的实用性.

结论:

QSAR-SSD方法提供了一种可行且具有成本效益的替代方案,可以替代实验测试来推导水质标准.
该方法可应用于更广泛的新兴污染物,以评估和管理水生生态系统风险.
该研究提供了保护水生生物免受特定化学污染物的影响的基本数据.

关键词:

在DRAGON软件中,新出现的污染物新出现的污染物杀虫剂是一种杀虫剂.风险评估风险评估风险评估有毒性有毒性

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