Guilhem FAURE

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Structural prediction of protein assemblies. Guilhem FAURE. Supervisor : Raphaël Guérois. Molecular Assemblies and Signaling Structural Biology and Radiobiology Lab iBiTecS – URA CNRS 2096 - CEA Saclay. Experimental insights into the protein interactions space ?. High throughput approaches. - PowerPoint PPT Presentation

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Diapositive 1Guilhem FAURE
iBiTecS – URA CNRS 2096 - CEA Saclay
Structural prediction of protein assemblies
Supervisor : Raphaël Guérois
Macromolecules in cellulo
High resolution
Translate each node of the interaction
networks into a 3D structure ?
Experimental structures
Homology models ?
proteins/domains assemblies ?
How to predict protein assemblies ?
Surface complementarities
Physico-chemestry features
Evolution data
104 decoys
Thesis Goals
104 decoys
How to characterize evolution ?
How to use evolution to predict ?
iViv 2010, Journées de rentrée des doctorants
Can conservation leads protein assemblies ?
= conserved
% of complexes
% of all conserved residues
Evolutionary rates as relevant interface signals ?
Lif1 S. cerevisiae
Nej1 S. cerevisiae
Xray structure known at 2.4A
Xray structure known at 2.3A
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
An Example of Prediction with XRCC4-Cernunnos
Exploiting Evolution and Energy Calculations
Coll. JB Charbonnier (LBSR)
2
4
6
8
10
12
14
iRMS
Local perturbations,
Model gives many precious information
Interface mutations can be design to study the complex
But without biochemestry information about BRCT hard to predict
Need mutual information coevolution / coadaptation
Model can lead the resolving of Xray structure
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 ?
Madaoui & Guerois, PNAS 2008
Same ancestor = homolog
=
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
How to explore coevolution ?
Data and Querying Server
Large spectrum of sequence divergence
Explore structural plasticity at complex interfaces
while increasing sequence divergence
Analyze the evolution of hot-spot regions
Benchmark to address how far structural models can be used in modelling protein complexes
Conclusion & Perspecpives
Building a large database
Developpement of statistical potential
taking account evolution data
XXX heteromeric
Querying Server
How to study coevolution ?
How to find coevolution ?
An interolog structural databank (350 groups of interologs)
same fold
How to explore coevolution at interfaces ?
iViv 2010, Journées de rentrée des doctorants
How to predict protein assemblies with coevolution ?
Multi-body potential
Interface database (2500 interfaces)
InterAlign database (2500 alignments)
RPN1
HSM3
RPT5
RPT2
RPT1
to identify the interaction sites ?
conservation
between interacting surfaces …
Can this helps to better predict molecular assemblies
interface
protein
% of all conserved residues
between interacting surfaces …
Protein A
Protein B
for loss of complementarity
Co-adaptation involve not only pairs of residues but also groups of structural neighbours
Human
Mouse
Fish
Yeast
Ex avec 100 seq
Co-variation analyses at the interface
of intra-molecular domain-domain interactions
An Example of Prediction Exploiting Evolution
DNA repair complex
(Non-homologous End Joining)
Conserved Residues
Conserved Residues
iViv 2010, Journées de rentrée des doctorants
The evolutionary dimension should provide key information
to exploit interaction data under a structural perspective
iViv 2010, Journées de rentrée des doctorants
2 majors issues
iViv 2010, Journées de rentrée des doctorants
2 majors issues
iViv 2010, Journées de rentrée des doctorants
InterEvol: The R-evolutionary databank
(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
iViv 2010, Journées de rentrée des doctorants
InterEvol: The R-evolutionary databank
(1) Krissinel and K. Henrick
An interolog structural databank (350 structures)
A
B
A’
B’
InterEvol: The R-evolutionary databank

InterEvol: The R-evolutionary databank
PISA 1 (PDB complex assemblies)
(1) Krissinel and K. Henrick
iViv 2010, Journées de rentrée des doctorants
InterEvol: The R-evolutionary databank
PISA 1 (PDB complex assemblies)
(1) Krissinel and K. Henrick
Cleaned true heteromer
InterEvol: The R-evolutionary databank
PISA 1 (PDB complex assemblies)
(1) Krissinel and K. Henrick
Cleaned true heteromer
iViv 2010, Journées de rentrée des doctorants
InterEvol: The R-evolutionary databank
PISA 1 (PDB complex assemblies)
(1) Krissinel and K. Henrick
Cleaned true heteromer
Non redundant heterodimer databank
InterEvol: The R-evolutionary databank
PISA 1 (PDB complex assemblies)
(1) Krissinel and K. Henrick
Cleaned true heteromer
Non redundant heterodimer databank
Through multidimensionnal data: InterEvolVisu
(1) Krissinel and K. Henrick
Photo du plugin sur un exemple
iViv 2010, Journées de rentrée des doctorants
Conclusions & Perspectives
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
iViv 2010, Journées de rentrée des doctorants
Conservation analyses at the interface
of intra-molecular domain-domain interactions
to identify potential binding patches no mutual information
(ProMate (Neuvirth, JMB, 2004), PINUP (Liang et al, NAR, 2006), SPPIDER (Porollo, Proteins, 2007))
interface
protein
% of all conserved residues
RPN1
HSM3
RPT5
RPT2
RPT1
to identify the interaction sites ?
conservation
Relationships between sequence divergence and conservation of the binding mode
Human
Yeast
A
B
generally interact in a similar manner
Aloy & Russel, JMB 2003
*