CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, China.
J Genet Genomics. 2011 May 20;38(5):201-7. doi: 10.1016/j.jgg.2011.04.003. Epub 2011 Apr 15.
Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein--protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein--protein interaction in intra-complex and the binary protein--protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 × 10(-6)). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein--protein interaction. Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study.
共进化可以被看作是进化历史之间的相互依存关系。在蛋白质进化的背景下,功能相关的蛋白质是始终存在的协调进化特征,不会破坏生物体的完整性。对于复杂系统,体内存在两种形式的蛋白质-蛋白质相互作用,分别是复合物间相互作用和复合物内相互作用。在本文中,我们使用“镜像树”方法研究了呼吸链(RC)蛋白中复合物间相互作用和复合物内相互作用的共进化特征之间的差异。我们将每个 RC 蛋白对的相关系数分为两组,分别对应于复合物内的二元蛋白质-蛋白质相互作用和复合物间的二元蛋白质-蛋白质相互作用。两组蛋白质相互作用的共进化特征存在显著差异(Wilcoxon 检验,p 值=4.4×10(-6))。我们的发现揭示了共进化研究的一些关键信息,并有助于对蛋白质-蛋白质相互作用的力学研究。此外,这些结果还为线粒体内膜中蛋白质复合物的超分子组织提供了一些独特的线索。核编码 RC 蛋白的更详细的结合位点图谱和基因组信息将对进一步的线粒体动力学研究具有非凡的价值。