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IViv 2010, Journées de rentrée des doctorants Guilhem FAURE Molecular Assemblies and Signaling Structural Biology and Radiobiology Lab iBiTecS – URA CNRS.

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Presentation on theme: "IViv 2010, Journées de rentrée des doctorants Guilhem FAURE Molecular Assemblies and Signaling Structural Biology and Radiobiology Lab iBiTecS – URA CNRS."— Presentation transcript:

1 iViv 2010, Journées de rentrée des doctorants Guilhem FAURE Molecular Assemblies and Signaling Structural Biology and Radiobiology Lab iBiTecS – URA CNRS CEA Saclay Structural prediction of protein assemblies Supervisor : Raphaël Guérois

2 iViv 2010, Journées de rentrée des doctorants Macromolecules in cellulo Experimental insights into the protein interactions space ? High resolution approches Synergies/Competitions Molecular vision High throughput approaches Large scale vision

3 iViv 2010, Journées de rentrée des doctorants Translate each node of the interaction networks into a 3D structure ? Experimental structures Homology models ? How to model the structure of proteins/domains assemblies ?

4 iViv 2010, Journées de rentrée des doctorants How to predict protein assemblies ? 10 4 decoys 1 most likely model Filters ~ 10 decoys  Surface complementarities  Physico-chemestry features  Evolution data

5 iViv 2010, Journées de rentrée des doctorants Thesis Goals 10 4 decoys 1 most likely model Filters ~ 10 decoys  Use evolution data to predict protein assemblies How to characterize evolution ?  Conservation ? Coevolution ?  type of data to analyse ? How to use evolution to predict ?

6 iViv 2010, Journées de rentrée des doctorants Can conservation leads protein assemblies ? = conserved AB interface Interface conservation Complex A-B % of complexes Ratio of conserved residues part of a given interface ~ 30 % % of all conserved residues interface protein Lack of specificity to predict

7 iViv 2010, Journées de rentrée des doctorants Evolutionary rates as relevant interface signals ? Lif1 S. cerevisiae XRCC4 H. sapiens (low sequence identity) Nej1 S. cerevisiae Cernunnos H. sapiens (low sequence identity) Xray structure known at 2.4A Xray structure known at 2.3A

8 iViv 2010, Journées de rentrée des doctorants Evolutionary rates as relevant interface signals ? An example from the DNA repair interaction network Lif1 S. cerevisiae XRCC4 H. sapiens Nej1 S. cerevisiae Cernunnos H. sapiens conservation BRCT DNA ligase

9 iViv 2010, Journées de rentrée des doctorants An Example of Prediction with XRCC4-Cernunnos Exploiting Evolution and Energy Calculations Coll. JB Charbonnier (LBSR) G. Faure in Malivert et al, JBC (2010) iRMS Interface Energy Rosetta Score (min vs all) Local perturbations, Optimisations of the interactions … search for funnels Step 2 Step 1 Filter solutions using evolutionnary rates

10 iViv 2010, Journées de rentrée des doctorants Model gives many precious information  Interface mutations can be design to study the complex But without biochemestry information about BRCT  hard to predict  Model can lead the resolving of Xray structure Need mutual information  coevolution / coadaptation

11 iViv 2010, Journées de rentrée des doctorants : complementary interactions - charge compensation - polar interactions - apolar interactions … How do deleterious mutations at the interface can be tolerated ?  Neighbouring positions can buffer the loss of complementarity  Other mechanisms of co-evolution ?  How to account for structural plasticity ? Madaoui & Guerois, PNAS 2008 Euk. sup. S. cerevisiae Deleterious mutation

12 iViv 2010, Journées de rentrée des doctorants How to study coevolution : concept of interology Same ancestor = homolog  Same evolution profil + same fold Same interaction involving same partners = INTEROLOGS  Same interface

13 iViv 2010, Journées de rentrée des doctorants How to build an interolog database ? G. Faure et al, in prep. 350 groups of structural interologs 2500 groups of interologs Extracting and cleaning heterocomplex  True heteromer  biological interfaces  … Redundancy traitement 2500 Non redundant interfaces

14 iViv 2010, Journées de rentrée des doctorants How to explore coevolution ? A PyMol plugin to visualize Structure and alignments Data and Querying Server at

15 iViv 2010, Journées de rentrée des doctorants Large spectrum of sequence divergence  Explore structural plasticity at complex interfaces while increasing sequence divergence  Test our ability to reproduce this plasticity  Analyze the evolution of hot-spot regions Benchmark to address how far structural models can be used in modelling protein complexes Conclusion & Perspecpives  Conservation can not be used to predict protein assemblies  Building a large database Developpement of statistical potential taking account evolution data

16 iViv 2010, Journées de rentrée des doctorants

17 XXX heteromeric complexes Redundancy filters Coupled alignments for orthologous sequences for both partners Clustering Families & Superfamilies Biological vs non biological interfaces XXX structural interologs NoXclass HHsearch Matras XXX non redundant interfaces InterEvol : Automatic and self-updating interface database for extracting structural and evolutionary information Querying Server at Pymol plugin for interface coevolution visualisation

18 iViv 2010, Journées de rentrée des doctorants How to study coevolution ? Querying Server at

19 iViv 2010, Journées de rentrée des doctorants

20 How to find coevolution ? G. Faure et al, in prep. An interolog structural databank (350 groups of interologs) same fold + same evolutif profil + same interaction area

21 iViv 2010, Journées de rentrée des doctorants How to explore coevolution at interfaces ?

22 iViv 2010, Journées de rentrée des doctorants How to predict protein assemblies with coevolution ? Multi-body potential Interologs database (350 groups of interologs) Interface database (2500 interfaces) InterAlign database (2500 alignments) Learning base Exploring base

23 iViv 2010, Journées de rentrée des doctorants RPN1 HSM3 RPT5 RPT2 RPT1 conservation score Conservation analyses Which evolutionary signals at protein surfaces can be captured to identify the interaction sites ? conservation

24 iViv 2010, Journées de rentrée des doctorants Evolutionary rates do not provide mutual information between interacting surfaces …  How to account for co-evolution or co-adaptation  Can this helps to better predict molecular assemblies Protein A Protein B AB interface % of complexes Which ratio of conserved residues are part of the interface ? % of all conserved residues interface protein

25 iViv 2010, Journées de rentrée des doctorants Evolutionary rates do not provide mutual information between interacting surfaces …

26 iViv 2010, Journées de rentrée des doctorants Protein A Protein B i j A/B complex i j 90° k k Structural Neighbours may compensate for loss of complementarity Co-adaptation involve not only pairs of residues but also groups of structural neighbours Human Mouse Fish Yeast … Madaoui & Guerois, PNAS 2008 Hydrophobic Polar Acidic Basic

27 iViv 2010, Journées de rentrée des doctorants Co-variation analyses at the interface of intra-molecular domain-domain interactions Protein A Protein B AB interface Human Partner B Fish Yeast … Mouse Partner A

28 iViv 2010, Journées de rentrée des doctorants An Example of Prediction Exploiting Evolution DNA repair complex (Non-homologous End Joining) Coll. JB Charbonnier (LBSR) G. Faure in Malivert et al, JBC (2010) Conserved Residues Docking under constrains with Haddock (Bonvin’s group)

29 iViv 2010, Journées de rentrée des doctorants The evolutionary dimension should provide key information to exploit interaction data under a structural perspective

30 iViv 2010, Journées de rentrée des doctorants 2 majors issues Difficulties to identify orthologs How to characterize selection pressure at the interface

31 iViv 2010, Journées de rentrée des doctorants 2 majors issues Difficulties to identify orthologs How to characterize selection pressure at the interface

32 iViv 2010, Journées de rentrée des doctorants InterEvol: The R-evolutionary databank G. Faure et al, in prep. (1) Krissinel and K. Henrick A non redundant heterodimer structures databank (2300 structures) Study the contact statistics at the interface Graph répartition transient permanent taille interface

33 iViv 2010, Journées de rentrée des doctorants InterEvol: The R-evolutionary databank G. Faure et al, in prep. (1) Krissinel and K. Henrick An interolog structural databank (350 structures) A B A’ B’ same fold + Same evolutif profil Rajouter les % id

34 iViv 2010, Journées de rentrée des doctorants InterEvol: The R-evolutionary databank G. Faure et al, in prep. An interolog sequence databank (2300 alignments) … at least 30% of identity Initial structure Sequences from PSIBLAST

35 iViv 2010, Journées de rentrée des doctorants InterEvol: The R-evolutionary databank G. Faure et al, in prep. PISA 1 (PDB complex assemblies) (1) Krissinel and K. Henrick

36 iViv 2010, Journées de rentrée des doctorants InterEvol: The R-evolutionary databank G. Faure et al, in prep. PISA 1 (PDB complex assemblies) (1) Krissinel and K. Henrick Cleaned true heteromer

37 iViv 2010, Journées de rentrée des doctorants InterEvol: The R-evolutionary databank G. Faure et al, in prep. PISA 1 (PDB complex assemblies) (1) Krissinel and K. Henrick Cleaned true heteromer Non redundant PDB structures databank

38 iViv 2010, Journées de rentrée des doctorants InterEvol: The R-evolutionary databank G. Faure et al, in prep. PISA 1 (PDB complex assemblies) (1) Krissinel and K. Henrick Cleaned true heteromer Non redundant PDB structures databank Non redundant heterodimer databank SCOTCHAlign databank

39 iViv 2010, Journées de rentrée des doctorants InterEvol: The R-evolutionary databank G. Faure et al, in prep. PISA 1 (PDB complex assemblies) (1) Krissinel and K. Henrick Cleaned true heteromer Non redundant PDB structures databank Non redundant heterodimer databank SCOTCHAlign databank Interolog databank

40 iViv 2010, Journées de rentrée des doctorants Through multidimensionnal data: InterEvolVisu G. Faure et al, in prep. (1) Krissinel and K. Henrick Photo du plugin sur un exemple

41 iViv 2010, Journées de rentrée des doctorants Conclusions & Perspectives (1) Krissinel and K. Henrick  Build a statistical multicore potential from structure and sequence data  Understand the pressure selection at the interface with Interologs  Build a full leading Docking method to automise each steps

42 iViv 2010, Journées de rentrée des doctorants Conservation analyses at the interface of intra-molecular domain-domain interactions Several approaches combined conservation with other structure and sequence features to identify potential binding patches  no mutual information (ProMate (Neuvirth, JMB, 2004), PINUP (Liang et al, NAR, 2006), SPPIDER (Porollo, Proteins, 2007)) % of complexes Which ratio of conserved residues are part of the interface ? % of all conserved residues interface protein

43 iViv 2010, Journées de rentrée des doctorants RPN1 HSM3 RPT5 RPT2 RPT1 conservation score Conservation analyses Which evolutionary signals at protein surfaces can be captured to identify the interaction sites ? conservation

44 iViv 2010, Journées de rentrée des doctorants Relationships between sequence divergence and conservation of the binding mode Human Yeast A B ~ > 30 % identity + +   A’B’ Complex A’ B’ AB Complex Two homologous complexes (~> 30% identity) generally interact in a similar manner Aloy & Russel, JMB 2003 Evolution data gives information about structure assemblies


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