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首页> 外文期刊>The Science of the Total Environment >Integrating QSAR models predicting acute contact toxicity and mode of action profiling in honey bees (A. mellifera): Data curation using open source databases, performance testing and validation
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Integrating QSAR models predicting acute contact toxicity and mode of action profiling in honey bees (A. mellifera): Data curation using open source databases, performance testing and validation

机译：集成QSAR模型预测焦蜜蜂（A. Mellifera）中的急性接触毒性和作用模式曲线模式：使用开源数据库，性能测试和验证数据策策

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摘要

Honey bees (Apis mellifera) provide key ecosystem services as pollinators bridging agriculture, the food chain and ecological communities, thereby ensuring food production and security. Ecological risk assessment of single Plant Protection Products (PPPs) requires an understanding of the exposure and toxicity. In silico tools such as QSAR models can play a major role for the prediction of structural, physico-chemical and pharmacokinetic properties of chemicals as well as toxicity of single and multiple chemicals. Here, the first integrative honey bee QSAR model has been developed for PPPs using EFSA's OpenFoodTox, US-EPA ECOTOX and Pesticide Properties DataBase ⅰ) to predict acute contact toxicity (LD_(50)) and ⅱ) to profile the Mode of Action (MoA) of pesticides active substances. Three different classification-based and four regression-based models were developed and tested for their performance, thus identifying two models providing the most reliable predictions based on k-NN algorithm. The two-category QSAR model (toxicon-toxic; n = 411) was validated using sensitivity (=0.93), specificity (= 0.85), balanced accuracy (=0.90), and Matthews correlation coefficient (MCC = 0.78) as statistical parameters. The regression-based model (n = 113) was validated for its reliability and robustness (R~2 = 0.74; MAE = 0.52). Current study proposes the MoA profiling for 113 pesticides active substances and the first harmonised MoA classification scheme for acute contact toxicity in honey bees, including LD_(50s) data points from three different databases. The classification allows to further define MoAs and the target site of PPPs active substances, thus enabling regulators and scientists to refine chemical grouping and toxicity extrapolations for single chemicals and component-based mixture risk assessment of multiple chemicals. Relevant future perspectives are briefly addressed to integrate MoA, adverse outcome pathways (AOPs) and toxicokinetic information for the refinement of single-chemical/combined toxicity predictions and risk estimates at different levels of biological organization in the bee health context.
机译：蜜蜂（API Mellifera）提供关键的生态系统服务，作为越过农业，食物链和生态社区的粉丝器，从而确保粮食生产和安全。单植物保护产品（PPP）的生态风险评估需要了解暴露和毒性。在QSAR模型的硅工具中，可以发挥化学品的结构，物理化学和药代动力学性能的主要作用以及单一和多种化学品的毒性。在这里，使用EFSA的OpenFoodtox，US-ECOTOX和农药性能数据库Ⅰ的PPPS开发了第一种整合蜂蜜蜜蜂QSAR模型，以预测急性接触毒性（LD_（50））和Ⅱ）来简要行动方式（MOA ）农药活性物质。为其性能开发并测试了基于三种基于分类的基于型号，从而识别了基于K-NN算法提供最可靠的预测的两个模型。使用灵敏度（= 0.93），特异性（= 0.85），平衡精度（= 0.90），以及Matthews相关系数（MCC = 0.78）作为统计，验证了两类QSAR模型（​​毒性/无毒; n = 411）。参数。基于回归的模型（n = 113）被验证了其可靠性和鲁棒性（R〜2 = 0.74; MAE = 0.52）。目前的研究提出了113种农药活性物质的MOA分析和蜂蜜蜜蜂中急性接触毒性的第一个协调的MOA分类方案，包括来自三个不同数据库的LD_（50s）数据点。分类允许进一步定义PPPS活性物质的MOA和靶位点，从而使调节器和科学家能够改进用于单一化学品和基于组成的组成的化学物质和组分的混合物风险评估的化学分组和毒性外推。简要介绍了未来的未来观点，以整合MOA，不利结果途径（AOP）和毒性信息，以改进单一化学/联合毒性预测和在蜂健康背景下的不同水平的生物组织的风险估计。

著录项

  • 来源
    《The Science of the Total Environment》 |2020年第15期|139243.1-139243.20|共20页
  • 作者

    Edoardo Carnesecchi; Cosimo Toma; Alessandra Roncaglioni; Nynke Kramer; Emilio Benfenati; Jean Lou C.M. Dome;

  • 作者单位

    Institute for Risk Assessment Sciences (IRAS) Utrecht University PO Box 80177 3508 TD Utrecht the Netherlands Laboratory of Chemistry and Environmental Toxicology Department of Environmental Health Sciences Istituto di Ricerche Farmacologiche Mario Negri IRCCS Via Mario Negri 2 20156 Milan Italy;

    Institute for Risk Assessment Sciences (IRAS) Utrecht University PO Box 80177 3508 TD Utrecht the Netherlands Laboratory of Chemistry and Environmental Toxicology Department of Environmental Health Sciences Istituto di Ricerche Farmacologiche Mario Negri IRCCS Via Mario Negri 2 20156 Milan Italy;

    Laboratory of Chemistry and Environmental Toxicology Department of Environmental Health Sciences Istituto di Ricerche Farmacologiche Mario Negri IRCCS Via Mario Negri 2 20156 Milan Italy;

    Institute for Risk Assessment Sciences (IRAS) Utrecht University PO Box 80177 3508 TD Utrecht the Netherlands;

    Laboratory of Chemistry and Environmental Toxicology Department of Environmental Health Sciences Istituto di Ricerche Farmacologiche Mario Negri IRCCS Via Mario Negri 2 20156 Milan Italy;

    European Food Safety Authority (EFSA) Scientific Committee and Emerging Risks Unit Via Carlo Magno 1A 43126 Parma Italy;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    QSAR models; Honey bees; Mode of action; Ecological risk assessment; Chemical mixtures;

    机译：QSAR模型;蜜蜂;行动方式;生态风险评估;化学混合物;

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