Abstract
Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence.
Highlights
The function and mechanical properties of a protein demand strong evolutionary pressures along evolution which are directed on the one hand, to conserve residues involved in catalytic sites and in interactions with amino acids of other proteins [1,2,3,4], and on the other hand, to mutually conserve residues involved in networks of interacting residues lying within the protein itself [5,6]
Fine analyses of families of protein sequences reveal the existence of networks of coevolved amino acids
By carefully tracing the way residues evolved within the phylogenetic tree of sequences of a protein family, the Maximal SubTree Method captures the transition along the time scale evolution of a conserved position to a coevolved position, and provides a numerical evaluation of the degree of coevolution of pairs of coevolved residues in a protein
Summary
The function and mechanical properties of a protein demand strong evolutionary pressures along evolution which are directed on the one hand, to conserve residues involved in catalytic sites and in interactions with amino acids of other proteins [1,2,3,4], and on the other hand, to mutually conserve residues involved in networks of interacting residues lying within the protein itself [5,6]. To measure in a precise manner different degrees of coevolution (where conservation is identified to have maximal degree) is central to the understanding of coevolution To tackle this problem means to propose a method to quantitatively measure coevolution of positions in aligned sequences and to identify clusters of positions following similar patterns of coevolution
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