Nano-QSAR:纳米毒理学领域的新方法
Nano-QSAR:An Emerging Approach in Nanotoxicology
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摘要: 随着纳米毒理学实验研究的不断深入,反映纳米材料生物毒性效应的数据也不断丰富,以这些数据为基础建立的定量结构活性关系(QSAR)模型开始发挥其在纳米材料潜在毒性研究和预测方面的作用。纳米材料的QSAR(Nano-QSAR)研究以经典QSAR 模型为指导,结合纳米材料特殊的物理化学性质,提供了一种对纳米材料快速筛选和优先测试的新途径。本文就Nano-QSAR的前期研究现状,从纳米材料结构描述符、毒性效应数据和建模方法3个方面分析了模型的构建流程和框架;通过列举部分研究成果和主要的模型指标,初步探讨了建模方法的选择和结构描述符的识别;最后指出目前Nano-QSAR研究面临的挑战和今后努力的方向。Abstract: With the development of studies on safety of nanomaterials, the number of toxicological data reflecting biological effects of nanomaterials keeps increasing. The quantitative structure-activity relationship (QSAR) models begin to play their roles in predicting the potential toxicity of nanomaterials. QSAR models for nanomaterials (Nano-QSAR), on the basis of the classic QSAR methods combining with the special physicochemical properties of nanomaterials, offered a new way to rapidly screen nanomaterials and priotitize testing. The studies on establishing the framework of Nano-QSAR modeling were reviewed from three aspects of structure descriptors, toxicological effect data and modeling methods. Selecting and identifying properly modeling methods and structure descriptors were discussed through listing examples and main indices of Nano-QSAR studies. Finally, current challenges and future direction in Nano-QSAR research were pointed out.
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Key words:
- nanomaterials /
- nanotoxicology /
- Nano-QSAR /
- structure descriptor /
- data mining
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