Riley Robert, Pellegrini Matteo, Eisenberg David
Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.
PLoS Comput Biol. 2008 Sep 12;4(9):e1000174. doi: 10.1371/journal.pcbi.1000174.
We consider the problem of how to detect cognate pairs of proteins that bind when each belongs to a large family of paralogs. To illustrate the problem, we have undertaken a genomewide analysis of interactions of members of the PE and PPE protein families of Mycobacterium tuberculosis. Our computational method uses structural information, operon organization, and protein coevolution to infer the interaction of PE and PPE proteins. Some 289 PE/PPE complexes were predicted out of a possible 5,590 PE/PPE pairs genomewide. Thirty-five of these predicted complexes were also found to have correlated mRNA expression, providing additional evidence for these interactions. We show that our method is applicable to other protein families, by analyzing interactions of the Esx family of proteins. Our resulting set of predictions is a starting point for genomewide experimental interaction screens of the PE and PPE families, and our method may be generally useful for detecting interactions of proteins within families having many paralogs.
我们考虑的问题是,当蛋白质各自属于一个庞大的旁系同源物家族时,如何检测相互结合的同源蛋白质对。为了阐明这个问题,我们对结核分枝杆菌的PE和PPE蛋白家族成员之间的相互作用进行了全基因组分析。我们的计算方法利用结构信息、操纵子组织和蛋白质协同进化来推断PE和PPE蛋白之间的相互作用。在全基因组范围内可能的5590对PE/PPE对中,预测出了约289个PE/PPE复合物。还发现其中35个预测复合物具有相关的mRNA表达,为这些相互作用提供了额外的证据。通过分析Esx蛋白家族的相互作用,我们表明我们的方法适用于其他蛋白质家族。我们得到的预测集是对PE和PPE家族进行全基因组实验性相互作用筛选的起点,并且我们的方法可能普遍有助于检测具有许多旁系同源物的家族内蛋白质之间的相互作用。