Inferring domain-domain interactions from protein-protein interactions
Inferring domain-domain interactions from protein-protein interactions
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DOI：
10.1101/gr.153002
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发表时间：
2002-10-01
期刊：
影响因子：
7
通讯作者：
Chen, T
中科院分区：
文献类型：
--
作者：
Deng, MH;Mehta, S;Chen, T
蛋白质之间的相互作用是蛋白质功能的重要特征之一。在蛋白质-蛋白质相互作用的背后，有蛋白质结构域相互作用以执行必要的功能。因此，在结构域水平上了解蛋白质相互作用可以提供蛋白质相互作用网络的全局视角，甚至可能是蛋白质功能的全局视角。两个研究小组使用酵母双杂交试验产生了5719个啤酒酵母蛋白质之间的相互作用。这使我们能够研究蛋白质结构域之间相互作用的大规模保守模式。使用在称为PFAM(http://PFAM.wustl.edu)，)的蛋白质结构域数据库中定义的进化保守结构域，我们应用最大似然估计方法来推断与观察到的蛋白质-蛋白质相互作用一致的相互作用结构域。我们估计每一对结构域之间相互作用的概率，并在蛋白质水平上衡量我们预测的准确性。使用推断的结构域-结构域相互作用，我们预测蛋白质之间的相互作用。我们预测的蛋白质-蛋白质相互作用与蛋白质-蛋白质相互作用(MIPS：http://mips.gfs.de))有很大重叠，这些重叠是通过双杂交分析以外的方法获得的。我们预测的相互作用对的基因表达谱的平均相关系数显著高于随机对。我们的方法在分析不完全数据集和处理各种实验误差方面表现出了稳健性。我们发现了一些新的蛋白质-蛋白质相互作用，如RPSOA与APG17的相互作用，TAF40与SPT3的相互作用，这与蛋白质的功能是一致的。
The interaction between proteins is one of the most important features of protein functions. Behind protein-protein interactions there are protein domains interacting physically with one another to perform the necessary functions. Therefore, understanding protein interactions at the domain level gives a global view of the protein interaction network, and possibly of protein functions. Two research groups used yeast two-hybrid assays to generate 5719 interactions between proteins of the yeast Saccharomyces cerevisiae. This allows us to study the large-scale conserved patterns of interactions between protein domains. Using evolutionarily conserved domains defined in a protein-domain database called PFAM (http://PFAM.wustl.edu), we apply a Maximum Likelihood Estimation method to infer interacting domains that are consistent with the observed protein-protein interactions. We estimate the probabilities of interactions between every pair of domains and measure the accuracies of our predictions at the protein level. Using the inferred domain-domain interactions, we predict interactions between proteins. Our predicted protein-protein interactions have a significant overlap with the protein-protein interactions (MIPS: http://mips.gfs.de) obtained by methods other than the two-hybrid assays. The mean correlation coefficient of the gene expression profiles for our predicted interaction pairs is significantly higher than that for random pairs. Our method has shown robustness in analyzing incomplete data sets and dealing with various experimental errors. We found several novel protein-protein interactions such as RPSOA interacting with APG17 and TAF40 interacting with SPT3, which are consistent with the functions of the proteins.