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Structural deformation upon protein-protein interaction: a structural alphabet approach.

Martin J, Regad L, Lecornet H, Camproux AC - BMC Struct. Biol. (2008)

Bottom Line: Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%).This proportion is even greater in the interface regions (41%).These results could be of help for flexible docking.

View Article: PubMed Central - HTML - PubMed

Affiliation: Equipe de Bioinformatique Génomique et Moléculaire, INSERM UMRS726/Université Denis Diderot Paris 7, F-75005 Paris, France. juliette.martin@jouy.inra.fr

ABSTRACT

Background: In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding.

Results: In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%). This proportion is even greater in the interface regions (41%). Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins.

Conclusion: Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

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Presentation of HMM-SA. a) 3D structure of the 27 structural letters. Images are generated using pymol [54]. b) hierarchical clustering of the 27 structural letters using the rmsddev.
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Figure 1: Presentation of HMM-SA. a) 3D structure of the 27 structural letters. Images are generated using pymol [54]. b) hierarchical clustering of the 27 structural letters using the rmsddev.

Mentions: The 27 structural letters, named [A-Z, a], are shown on Figure 1a. It has been shown previously [37], that four structural letters, [a,A,V,W] specifically describe α-helices, and five structural letters, [L,M,N,T,X], specifically describe β-strands. Letters [a] and [A] are the most regular, [a] being slightly shorter. It has been shown that linear helices are encoded by runs of [A], and curved helices are encoded by runs of [a] [39]. The 18 remaining structural letters describe loops. Letters [Z,B,C] form helix ends and letters [J,K] form strand ends. This alphabet allows a very precise decomposition of 3D structures. Some structural letters are structurally close, while others are more distant. This is quantified using the root-mean-square deviation between two structural letters (rmsddev). The rmsddev has been computed from 500 fragment pairs randomly chosen in the two structural letters [36]. It has been shown, that the rmsddev between two structural letters is always greater than the intrinsic variability of each structural letters, measured in the same way and called rmsdintra [36]. Figure 1b reports the hierarchical clustering of the 27 structural letters according to the rmsddev. Using a cut-off of 1 Å, the 27 structural letters are grouped into 8 groups: [Z,B,A,a,V,W], [I,C,U], [O,S], [E,Q], [G,M,N,T,R,X], [P,K,L,D,H,Y], [F], and [J].


Structural deformation upon protein-protein interaction: a structural alphabet approach.

Martin J, Regad L, Lecornet H, Camproux AC - BMC Struct. Biol. (2008)

Presentation of HMM-SA. a) 3D structure of the 27 structural letters. Images are generated using pymol [54]. b) hierarchical clustering of the 27 structural letters using the rmsddev.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2315654&req=5

Figure 1: Presentation of HMM-SA. a) 3D structure of the 27 structural letters. Images are generated using pymol [54]. b) hierarchical clustering of the 27 structural letters using the rmsddev.
Mentions: The 27 structural letters, named [A-Z, a], are shown on Figure 1a. It has been shown previously [37], that four structural letters, [a,A,V,W] specifically describe α-helices, and five structural letters, [L,M,N,T,X], specifically describe β-strands. Letters [a] and [A] are the most regular, [a] being slightly shorter. It has been shown that linear helices are encoded by runs of [A], and curved helices are encoded by runs of [a] [39]. The 18 remaining structural letters describe loops. Letters [Z,B,C] form helix ends and letters [J,K] form strand ends. This alphabet allows a very precise decomposition of 3D structures. Some structural letters are structurally close, while others are more distant. This is quantified using the root-mean-square deviation between two structural letters (rmsddev). The rmsddev has been computed from 500 fragment pairs randomly chosen in the two structural letters [36]. It has been shown, that the rmsddev between two structural letters is always greater than the intrinsic variability of each structural letters, measured in the same way and called rmsdintra [36]. Figure 1b reports the hierarchical clustering of the 27 structural letters according to the rmsddev. Using a cut-off of 1 Å, the 27 structural letters are grouped into 8 groups: [Z,B,A,a,V,W], [I,C,U], [O,S], [E,Q], [G,M,N,T,R,X], [P,K,L,D,H,Y], [F], and [J].

Bottom Line: Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%).This proportion is even greater in the interface regions (41%).These results could be of help for flexible docking.

View Article: PubMed Central - HTML - PubMed

Affiliation: Equipe de Bioinformatique Génomique et Moléculaire, INSERM UMRS726/Université Denis Diderot Paris 7, F-75005 Paris, France. juliette.martin@jouy.inra.fr

ABSTRACT

Background: In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding.

Results: In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%). This proportion is even greater in the interface regions (41%). Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins.

Conclusion: Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

Show MeSH