Lee Byung-Chul, Park Keunwan, Kim Dongsup
Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon 305-701, Korea.
Proteins. 2008 Aug 15;72(3):863-72. doi: 10.1002/prot.21972.
It is a common belief that some residues of a protein are more important than others. In some cases, point mutations of some residues make butterfly effect on the protein structure and function, but in other cases they do not. In addition, the residues important for the protein function tend to be not only conserved but also coevolved with other interacting residues in a protein. Motivated by these observations, the authors propose that there is a network composed of the residues, the residue-residue coevolution network (RRCN), where nodes are residues and links are set when the coevolutionary interaction strengths between residues are sufficiently large. The authors build the RRCN for the 44 diverse protein families. The interaction strengths are calculated by using McBASC algorithm. After constructing the RRCN, the authors identify residues that have high degree of connectivity (hub nodes), and residues that play a central role in network flow of information (C(I) nodes). The authors show that these residues are likely to be functionally important residues. Moreover, the C(I) nodes appear to be more relevant to the function than the hub nodes. Unlike other similar methods, the method described in this study is solely based on sequences. Therefore, the method can be applied to the function annotation of a wider range of proteins.
人们普遍认为,蛋白质的某些残基比其他残基更重要。在某些情况下,某些残基的点突变会对蛋白质的结构和功能产生蝴蝶效应,但在其他情况下则不会。此外,对蛋白质功能重要的残基往往不仅保守,而且与蛋白质中其他相互作用的残基共同进化。受这些观察结果的启发,作者提出存在一个由残基组成的网络,即残基 - 残基共同进化网络(RRCN),其中节点是残基,当残基之间的共同进化相互作用强度足够大时设置链接。作者为44个不同的蛋白质家族构建了RRCN。相互作用强度通过使用McBASC算法计算。构建RRCN后,作者识别出具有高连接度的残基(枢纽节点)以及在网络信息流中起核心作用的残基(C(I)节点)。作者表明这些残基可能是功能上重要残基。此外,C(I)节点似乎比枢纽节点与功能更相关。与其他类似方法不同,本研究中描述的方法仅基于序列。因此,该方法可应用于更广泛蛋白质的功能注释。