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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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Haemoglobins.A: Matrix of relative coevolution scores . Five coevolved residues networks are detected by the MST method and manually selected (boxes limit the boundaries). Dotted lines in the second square from the bottom left distinguish two subnetworks detected by the SCA method. BCD: Coevolved residues networks in the structure of the human haemoglobin  subunit (two faces of the 1HDB chain B). Residues in the networks are indicated using the Van der Walls representation, haem in orange,  subunit in green and  in black; B: network associated to the haem binding site (red); C: network associated to the allosteric function; residues are colored in brown and blue according to which SCA network they belong to. Brown positions are located between the haem and the  subunit binding site, and blue positions are in contact with brown positions close to the haem; D: networks associated to the  and  subunit binding sites; they correspond to the third (deep violet), forth (light violet) and fifth (yellow) networks in A. E: Global view of the coevolved residues networks.
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pcbi-1000488-g010: Haemoglobins.A: Matrix of relative coevolution scores . Five coevolved residues networks are detected by the MST method and manually selected (boxes limit the boundaries). Dotted lines in the second square from the bottom left distinguish two subnetworks detected by the SCA method. BCD: Coevolved residues networks in the structure of the human haemoglobin subunit (two faces of the 1HDB chain B). Residues in the networks are indicated using the Van der Walls representation, haem in orange, subunit in green and in black; B: network associated to the haem binding site (red); C: network associated to the allosteric function; residues are colored in brown and blue according to which SCA network they belong to. Brown positions are located between the haem and the subunit binding site, and blue positions are in contact with brown positions close to the haem; D: networks associated to the and subunit binding sites; they correspond to the third (deep violet), forth (light violet) and fifth (yellow) networks in A. E: Global view of the coevolved residues networks.

Mentions: Among the 161 alignment positions of the haemoglobin family, 57 (35% of aligned positions) have been selected as seed positions. Our combinatorial method applied to this family lead to the identification of five networks (Figure 10A) covering the 29% of the residues of the 1HDB chain B structure.


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

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

Haemoglobins.A: Matrix of relative coevolution scores . Five coevolved residues networks are detected by the MST method and manually selected (boxes limit the boundaries). Dotted lines in the second square from the bottom left distinguish two subnetworks detected by the SCA method. BCD: Coevolved residues networks in the structure of the human haemoglobin  subunit (two faces of the 1HDB chain B). Residues in the networks are indicated using the Van der Walls representation, haem in orange,  subunit in green and  in black; B: network associated to the haem binding site (red); C: network associated to the allosteric function; residues are colored in brown and blue according to which SCA network they belong to. Brown positions are located between the haem and the  subunit binding site, and blue positions are in contact with brown positions close to the haem; D: networks associated to the  and  subunit binding sites; they correspond to the third (deep violet), forth (light violet) and fifth (yellow) networks in A. E: Global view of the coevolved residues networks.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2723916&req=5

pcbi-1000488-g010: Haemoglobins.A: Matrix of relative coevolution scores . Five coevolved residues networks are detected by the MST method and manually selected (boxes limit the boundaries). Dotted lines in the second square from the bottom left distinguish two subnetworks detected by the SCA method. BCD: Coevolved residues networks in the structure of the human haemoglobin subunit (two faces of the 1HDB chain B). Residues in the networks are indicated using the Van der Walls representation, haem in orange, subunit in green and in black; B: network associated to the haem binding site (red); C: network associated to the allosteric function; residues are colored in brown and blue according to which SCA network they belong to. Brown positions are located between the haem and the subunit binding site, and blue positions are in contact with brown positions close to the haem; D: networks associated to the and subunit binding sites; they correspond to the third (deep violet), forth (light violet) and fifth (yellow) networks in A. E: Global view of the coevolved residues networks.
Mentions: Among the 161 alignment positions of the haemoglobin family, 57 (35% of aligned positions) have been selected as seed positions. Our combinatorial method applied to this family lead to the identification of five networks (Figure 10A) covering the 29% of the residues of the 1HDB chain B structure.

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