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A combinatorial approach to detect coevolved amino acid networks in protein families of variable divergence.

Baussand J, Carbone A - PLoS Comput. Biol. (2009)

Bottom Line: 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 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.

View Article: PubMed Central - PubMed

Affiliation: Génomique Analytique, Université Pierre et Marie Curie, Paris, France.

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.

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MSTs and ranks illustrated in a sequence alignment and associated distance tree T.A. Analysis of conservation at position s = 9 in the sequence alignment, MST rank  and ET rank (as defined in [20]). The 5 MSTs conserving residues at position 9 are delimited by purple dotted lines and their roots are represented by purple circles. The 10 subtrees identified by the ET approach are delimited by pink dotted lines and the node determining the rank of conservation of the 9th position is indicated by a pink square. B. Analysis of 6 different alignment positions marked with distinguished colors in the alignment and in the tree. The rank , its corresponding ET rank and the roots of MSTs decomposing T with respect to position s are colored the same way.
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pcbi-1000488-g001: MSTs and ranks illustrated in a sequence alignment and associated distance tree T.A. Analysis of conservation at position s = 9 in the sequence alignment, MST rank and ET rank (as defined in [20]). The 5 MSTs conserving residues at position 9 are delimited by purple dotted lines and their roots are represented by purple circles. The 10 subtrees identified by the ET approach are delimited by pink dotted lines and the node determining the rank of conservation of the 9th position is indicated by a pink square. B. Analysis of 6 different alignment positions marked with distinguished colors in the alignment and in the tree. The rank , its corresponding ET rank and the roots of MSTs decomposing T with respect to position s are colored the same way.

Mentions: The rank of a position s in a tree T corresponds to the number of MSTs decomposing T at position s, where a MST is the largest subtree conserving a same residue (see Figure 1A).


A combinatorial approach to detect coevolved amino acid networks in protein families of variable divergence.

Baussand J, Carbone A - PLoS Comput. Biol. (2009)

MSTs and ranks illustrated in a sequence alignment and associated distance tree T.A. Analysis of conservation at position s = 9 in the sequence alignment, MST rank  and ET rank (as defined in [20]). The 5 MSTs conserving residues at position 9 are delimited by purple dotted lines and their roots are represented by purple circles. The 10 subtrees identified by the ET approach are delimited by pink dotted lines and the node determining the rank of conservation of the 9th position is indicated by a pink square. B. Analysis of 6 different alignment positions marked with distinguished colors in the alignment and in the tree. The rank , its corresponding ET rank and the roots of MSTs decomposing T with respect to position s are colored the same way.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2723916&req=5

pcbi-1000488-g001: MSTs and ranks illustrated in a sequence alignment and associated distance tree T.A. Analysis of conservation at position s = 9 in the sequence alignment, MST rank and ET rank (as defined in [20]). The 5 MSTs conserving residues at position 9 are delimited by purple dotted lines and their roots are represented by purple circles. The 10 subtrees identified by the ET approach are delimited by pink dotted lines and the node determining the rank of conservation of the 9th position is indicated by a pink square. B. Analysis of 6 different alignment positions marked with distinguished colors in the alignment and in the tree. The rank , its corresponding ET rank and the roots of MSTs decomposing T with respect to position s are colored the same way.
Mentions: The rank of a position s in a tree T corresponds to the number of MSTs decomposing T at position s, where a MST is the largest subtree conserving a same residue (see Figure 1A).

Bottom Line: 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 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.

View Article: PubMed Central - PubMed

Affiliation: Génomique Analytique, Université Pierre et Marie Curie, Paris, France.

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.

Show MeSH