Interdisciplinary Nanotoxicity Center, Department of Chemistry and Biochemistry, Jackson State University, 1400 Lynch Street, Jackson, Mississippi 39217-0510, USA.
Nat Nanotechnol. 2011 Mar;6(3):175-8. doi: 10.1038/nnano.2011.10. Epub 2011 Feb 13.
It is expected that the number and variety of engineered nanoparticles will increase rapidly over the next few years, and there is a need for new methods to quickly test the potential toxicity of these materials. Because experimental evaluation of the safety of chemicals is expensive and time-consuming, computational methods have been found to be efficient alternatives for predicting the potential toxicity and environmental impact of new nanomaterials before mass production. Here, we show that the quantitative structure-activity relationship (QSAR) method commonly used to predict the physicochemical properties of chemical compounds can be applied to predict the toxicity of various metal oxides. Based on experimental testing, we have developed a model to describe the cytotoxicity of 17 different types of metal oxide nanoparticles to bacteria Escherichia coli. The model reliably predicts the toxicity of all considered compounds, and the methodology is expected to provide guidance for the future design of safe nanomaterials.
预计在未来几年内，工程纳米粒子的数量和种类将迅速增加，因此需要新的方法来快速测试这些材料的潜在毒性。由于对化学品安全性进行实验评估既昂贵又耗时，因此人们发现计算方法是在大规模生产之前预测新型纳米材料潜在毒性和环境影响的有效替代方法。在这里，我们表明，常用于预测化合物物理化学性质的定量构效关系 (QSAR) 方法可用于预测各种金属氧化物的毒性。基于实验测试，我们开发了一个模型来描述 17 种不同类型的金属氧化物纳米颗粒对细菌大肠杆菌的细胞毒性。该模型可靠地预测了所有考虑化合物的毒性，并且该方法有望为未来安全纳米材料的设计提供指导。
