基于毒物基因组学的定量构效关系方法建立环境污染物毒性预测模型。

ISRN Toxicology Pub Date : 2011-07-02 Print Date: 2011-01-01 DOI:10.5402/2011/515724
Junichi Hosoya, Kumiko Tamura, Naomi Muraki, Hiroki Okumura, Tsuyoshi Ito, Mitsugu Maeno
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引用次数: 4

摘要

汽车减排技术的发展使汽车尾气中的颗粒物浓度急剧下降;然而,由于新技术和新燃料的使用,排放物中可能会形成意想不到的有害化学物质。因此,我们试图为包括汽车排放在内的众多环境污染物开发新的、有效的毒性预测模型。我们选择了54种与发动机废气有关的化合物,并通过使用DNA微阵列,检测了它们对人类肺细胞基因表达的影响。我们将IL-8作为促炎细胞因子,利用计算机系统建立了IL-8基因表达定量构效关系(QSAR)预测模型。我们的结果表明,该模型在预测IL-8基因上调方面具有较高的准确性。这些结果表明,基于毒物基因组学基因表达的QSAR预测模型在环境污染物毒理学预测中具有很大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A novel approach for a toxicity prediction model of environmental pollutants by using a quantitative structure-activity relationship method based on toxicogenomics.

The development of automobile emission reduction technologies has decreased dramatically the particle concentration in emissions; however, there is a possibility that unexpected harmful chemicals are formed in emissions due to new technologies and fuels. Therefore, we attempted to develop new and efficient toxicity prediction models for the myriad environmental pollutants including those in automobile emissions. We chose 54 compounds related to engine exhaust and, by use of the DNA microarray, examined their effect on gene expression in human lung cells. We focused on IL-8 as a proinflammatory cytokine and developed a prediction model with quantitative structure-activity relationship (QSAR) for the IL-8 gene expression by using an in silico system. Our results demonstrate that this model showed high accuracy in predicting upregulation of the IL-8 gene. These results suggest that the prediction model with QSAR based on the gene expression from toxicogenomics may have great potential in predictive toxicology of environmental pollutants.

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