利用急性和慢性终点预测土壤对念珠菌的生态毒性。

IF 2.3 3区 环境科学与生态学 Q3 CHEMISTRY, MULTIDISCIPLINARY
R Paul, J Roy, K Roy
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引用次数: 0

摘要

土壤无脊椎动物是土壤质量的重要生物指标。然而,由于数据的缺乏,到目前为止,关于化学物质对土壤无脊椎动物的土壤毒性的计算机模型很少。本研究从ECOTOX数据库(cfpub.epa.gov/ecotox)中收集了3个土壤生态毒性数据(pLC50、pLOEL和pNOEL),并利用二维描述子进行定量构效关系(QSAR)分析。每个端点收集的数据最初被整理,并用于开发一个偏最小二乘(PLS)回归模型,该模型基于通过遗传算法选择的特征,然后是最佳子集选择。模型预测的内部和外部验证指标都很平衡,并且在经济合作与发展组织(OECD)标准的可接受范围内。从所建立的模型中发现,磷基、电子给体基团和多卤素取代的分子量和存在对土壤的生态毒性有显著影响。因此,有机化学品的土壤生态毒理学风险评估可以优先考虑这些特征。随着未来更多数据的可用性,这些模型可能会进一步完善,以获得更精确的预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of soil ecotoxicity against Folsomia candida using acute and chronic endpoints.

Soil invertebrates serve as great biological indicators of soil quality. However, there are very few in silico models developed so far on the soil toxicity of chemicals against soil invertebrates due to paucity of data. In this study, three available soil ecotoxicity data (pLC50, pLOEL and pNOEL) against the soil invertebrate Folsomia candida were collected from the ECOTOX database (cfpub.epa.gov/ecotox) and subjected to quantitative structure-activity relationship (QSAR) analysis using 2D descriptors. The collected data for each endpoint were initially curated and used to develop a partial least squares (PLS) regression model based on the features selected through a genetic algorithm followed by the best subset selection. Both internal and external validation metrics of the models' predictions are well-balanced and within the acceptable range as per the Organization for the Economic Cooperation and Development (OECD) criteria. From the developed models, it has been found that molecular weight and presence of phosphate group, electron donor groups, and polyhalogen substitution have a significant impact on the soil ecotoxicity. The soil ecotoxicological risk assessment of organic chemicals can therefore be prioritized by these features. With the availability of additional data in the future, the models may be further refined for more precise predictions.

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来源期刊
CiteScore
5.20
自引率
20.00%
发文量
78
审稿时长
>24 weeks
期刊介绍: SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.
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