Department of Systems Biology, Technical University of Denmark, Center for Biological Sequence Analysis, Lyngby, Denmark.
PLoS Comput Biol. 2010 May 20;6(5):e1000788. doi: 10.1371/journal.pcbi.1000788.
Exposure to environmental chemicals and drugs may have a negative effect on human health. A better understanding of the molecular mechanism of such compounds is needed to determine the risk. We present a high confidence human protein-protein association network built upon the integration of chemical toxicology and systems biology. This computational systems chemical biology model reveals uncharacterized connections between compounds and diseases, thus predicting which compounds may be risk factors for human health. Additionally, the network can be used to identify unexpected potential associations between chemicals and proteins. Examples are shown for chemicals associated with breast cancer, lung cancer and necrosis, and potential protein targets for di-ethylhexyl-phthalate, 2,3,7,8-tetrachlorodibenzo-p-dioxin, pirinixic acid and permethrine. The chemical-protein associations are supported through recent published studies, which illustrate the power of our approach that integrates toxicogenomics data with other data types.
暴露于环境化学物质和药物可能对人类健康产生负面影响。为了确定风险,需要更好地了解这些化合物的分子机制。我们提出了一个基于化学毒理学和系统生物学整合的高可信度人类蛋白质-蛋白质相互作用网络。这个计算系统化学生物学模型揭示了化合物和疾病之间未被描述的联系,从而预测哪些化合物可能是人类健康的风险因素。此外,该网络还可用于识别化学物质和蛋白质之间意想不到的潜在关联。以与乳腺癌、肺癌和坏死有关的化学物质以及邻苯二甲酸二(2-乙基己基)酯、二噁英、戊菌隆和扑灭威的潜在蛋白靶标为例,说明了这一点。化学-蛋白质的关联得到了最近发表的研究的支持,这些研究说明了我们的方法的强大之处,该方法将毒理学基因组学数据与其他数据类型相结合。