定量读取-交叉结构-属性关系(q-RASPR):一种估算不同类别工业化学品在水生生物体内生物累积潜力的新方法。

IF 4.3 3区 环境科学与生态学 Q1 CHEMISTRY, ANALYTICAL Environmental Science: Processes & Impacts Pub Date : 2024-11-01 DOI:10.1039/d4em00374h
Prodipta Bhattacharyya, Pabitra Samanta, Ankur Kumar, Shubha Das, Probir Kumar Ojha
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引用次数: 0

摘要

生物富集系数(BCF)用于评估化学物质在参照生物体内的生物累积潜力,它与生态毒性直接相关。传统的体内生物富集系数估算方法成本高、耗时长,而且需要牺牲动物。为了避免与体内测试相关的问题,人们采用了许多硅学技术。本研究旨在利用由 1303 种化合物组成的结构多样化数据集,结合定量结构-性质关系(QSPR)和横向读取(RA)算法,开发一种定量横向读取结构-性质关系(q-RASPR)模型。该模型结合了简单、可解释、可重复的二维分子描述符和 RASAR 描述符。基于 PLS 的 q-RASPR 模型在内部验证指标(R2 = 0.727 和 Q2(LOO) = 0.723)和外部验证指标(Q2F1 = 0.739、Q2F2 = 0.739 和 CCC = 0.858)上都表现出稳健的性能。这些结果表明,q-RASPR 模型在统计学上优于相应的 QSPR 模型。此外,利用基于 PLS 的 q-RASPR 模型对农药特性数据库(PPDB)中的 1694 种化合物进行了筛选,以评估各种化合物的生态毒理学生物累积潜力,从而确保了所开发模型的外部可预测性,并证实了所开发模型在现实世界中的应用。该模型为预测新化合物或未测试化合物的生物累积系数提供了可靠的工具,从而有助于开发安全、环保的化学品。
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Quantitative read-across structure-property relationship (q-RASPR): a novel approach to estimate the bioaccumulative potential for diverse classes of industrial chemicals in aquatic organisms.

The Bioconcentration Factor (BCF) is used to evaluate the bioaccumulation potential of chemical substances in reference organisms, and it directly correlates with ecotoxicity. Traditional in vivo BCF estimation methods are costly, time-consuming, and involve animal sacrifice. Many in silico technologies are used to avoid the problems associated with in vivo testing. This study aims to develop a quantitative read across structure-property relationship (q-RASPR) model using a structurally diverse dataset consisting of 1303 compounds by combining quantitative structure-property relationship (QSPR) and read-across (RA) algorithms. The model incorporates simple, interpretable, and reproducible 2D molecular descriptors along with RASAR descriptors. The PLS-based q-RASPR model demonstrated robust performance with internal validation metrics (R2 = 0.727 and Q2(LOO) = 0.723) and external validation metrics (Q2F1 = 0.739, Q2F2 = 0.739, and CCC = 0.858). These results indicate that the q-RASPR model is statistically superior to the corresponding QSPR model. Furthermore, screening of 1694 compounds from the Pesticide Properties Database (PPDB) was performed using the PLS-based q-RASPR model for assessing the eco-toxicological bioaccumulative potential of various compounds, ensuring the external predictability of the developed model and confirming the real-world application of the developed model. This model offers a reliable tool for predicting the BCF of new or untested compounds, thereby helping to develop safe and environment-friendly chemicals.

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来源期刊
Environmental Science: Processes & Impacts
Environmental Science: Processes & Impacts CHEMISTRY, ANALYTICAL-ENVIRONMENTAL SCIENCES
CiteScore
9.50
自引率
3.60%
发文量
202
审稿时长
1 months
期刊介绍: Environmental Science: Processes & Impacts publishes high quality papers in all areas of the environmental chemical sciences, including chemistry of the air, water, soil and sediment. We welcome studies on the environmental fate and effects of anthropogenic and naturally occurring contaminants, both chemical and microbiological, as well as related natural element cycling processes.
期刊最新文献
Emerging investigator series: open dumping and burning: an overlooked source of terrestrial microplastics in underserved communities. Commercial kitchen operations produce a diverse range of gas-phase reactive nitrogen species. How do ecosystem service functions affect ecological health? Evidence from the Yangtze River Economic Belt in China. Polyethylene microplastics affect behavioural, oxidative stress, and molecular responses in the Drosophila model. Quantitative read-across structure-property relationship (q-RASPR): a novel approach to estimate the bioaccumulative potential for diverse classes of industrial chemicals in aquatic organisms.
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