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首页> 外文期刊>Environmental Science & Technology >Computational Tool for Risk Assessment of Nanomaterials: Novel QSTR-Perturbation Model for Simultaneous Prediction of Ecotoxicity and Cytotoxicity of Uncoated and Coated Nanoparticles under Multiple Experimental Conditions
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Computational Tool for Risk Assessment of Nanomaterials: Novel QSTR-Perturbation Model for Simultaneous Prediction of Ecotoxicity and Cytotoxicity of Uncoated and Coated Nanoparticles under Multiple Experimental Conditions

机译：纳米材料风险评估的计算工具：新型QSTR扰动模型，可同时预测多种实验条件下未涂覆和涂覆的纳米颗粒的生态毒性和细胞毒性

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摘要

Nanomaterials have revolutionized modern science and technology due to their multiple applications in engineering, physics, chemistry, and biomedicine. Nevertheless, the use and manipulation of nanoparticles (NPs) can bring serious damages to living organisms and their ecosystems. For this reason, ecotoxicity and cytotoxicity assays are of special interest in order to determine the potential harmful effects of NPs. Processes based on ecotoxicity and cytotoxicity tests can significantly consume time and financial resources. In this sense, alternative approaches such as quantitative structure-activity/toxicity relationships (QSAR/QSTR) modeling have provided important insights for the better understanding of the biological behavior of NPs that may be responsible for causing toxicity. Until now, QSAR/QSTR models have predicted ecotoxicity or cytotoxicity separately against only one organism (bioindicator species or cell line) and have not reported information regarding the quantitative influence of characteristics other than composition or size. In this work, we developed a unified QSTR- perturbation model to simultaneously probe ecotoxicity and cytotoxicity of NPs under different experimental conditions, including diverse measures of toxicities, multiple biological targets, compositions, sizes and conditions to measure those sizes, shapes, times during which the biological targets were exposed to NPs, and coating agents. The model was created from 36488 cases (NP-NP pairs) and exhibited accuracies higher than 98% in both training and prediction sets. The model was used to predict toxicities of several NPs that were not included in the original data set. The results of the predictions suggest that the present QSTR-perturbation model can be employed as a highly promising tool for the fast and efficient assessment of ecotoxicity and cytotoxicity of NPs.
机译：纳米材料由于其在工程，物理，化学和生物医学中的多种应用，彻底改变了现代科学技术。但是，纳米颗粒（NPs）的使用和操作会严重损害生物体及其生态系统。因此，为了确定NP的潜在有害作用，特别需要进行生态毒性和细胞毒性分析。基于生态毒性和细胞毒性测试的过程会大量消耗时间和财力。从这个意义上讲，诸如定量结构-活性/毒性关系（QSAR / QSTR）建模之类的替代方法为更好地理解可能引起毒性的NP的生物学行为提供了重要的见识。到目前为止，QSAR / QSTR模型仅针对一种生物（生物指示剂物种或细胞系）单独预测了生态毒性或细胞毒性，并且尚未报告有关组成或大小以外的特征的定量影响的信息。在这项工作中，我们开发了一个统一的QSTR-扰动模型，以同时探查不同实验条件下NP的生态毒性和细胞毒性，包括不同程度的毒性测量，多种生物学目标，组成，大小和条件，以测量这些大小，形状，时间。生物靶标暴露于NP和包被剂。该模型是从36488个病例（NP-NP对）创建的，在训练和预测集中均显示出高于98％的准确性。该模型用于预测原始数据集中未包含的几种NP的毒性。预测结果表明，当前的QSTR扰动模型可以用作快速有效评估NPs的生态毒性和细胞毒性的极有前途的工具。

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  • 来源
    《Environmental Science & Technology》 |2014年第24期|14686-14694|共9页
  • 作者

    Valeria V. Kleandrova; Feng Luan; Humberto Gonzalez-Diaz; Juan M. Ruso; Alejandro Speck-Planche; M. Natalia D. S. Cordeiro;

  • 作者单位

    REQUIMTE/Department of Chemistry and Biochemistry, University of Porto, 4169-007 Porto, Portugal;

    REQUIMTE/Department of Chemistry and Biochemistry, University of Porto, 4169-007 Porto, Portugal,Department of Applied Chemistry, Yantai University, Yantai 264005, People's Republic of China;

    Department of Organic Chemistry Ⅱ, University of the Basque Country UPV/EHU, 48940 Bilbao, Spain,IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain;

    Department of Applied Physics, University of Santiago de Compostela (USC), 15782 Santiago de Compostela, Spain;

    REQUIMTE/Department of Chemistry and Biochemistry, University of Porto, 4169-007 Porto, Portugal,Department of Applied Physics, University of Santiago de Compostela (USC), 15782 Santiago de Compostela, Spain;

    REQUIMTE/Department of Chemistry and Biochemistry, University of Porto, 4169-007 Porto, Portugal;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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