Analysis of the residue–residue coevolution network and the functionally important residues in proteins

BC Lee, K Park, D Kim - Proteins: Structure, Function, and …, 2008 - Wiley Online Library
BC Lee, K Park, D Kim
Proteins: Structure, Function, and Bioinformatics, 2008Wiley Online Library
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 …
Abstract
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 (CI nodes). The authors show that these residues are likely to be functionally important residues. Moreover, the CI 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. Proteins 2008. © 2008 Wiley‐Liss, Inc.
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