IViv 2010, Journées de rentrée des doctorants Guilhem FAURE Molecular Assemblies and Signaling...
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Transcript of IViv 2010, Journées de rentrée des doctorants Guilhem FAURE Molecular Assemblies and Signaling...
iViv 2010, Journées de rentrée des doctorants
Guilhem FAURE
Molecular Assemblies and SignalingStructural Biology and Radiobiology Lab
iBiTecS – URA CNRS 2096 - CEA Saclay
Structural prediction of protein assemblies
Supervisor : Raphaël Guérois
iViv 2010, Journées de rentrée des doctorants
Macromolecules in cellulo
Experimental insights into the protein interactions space ?
High resolutionapproches
Synergies/CompetitionsMolecular vision
High throughputapproaches
Large scale vision
iViv 2010, Journées de rentrée des doctorants
Translate each node of the interaction networks into a 3D structure ?
Experimental structuresHomology models ?
How to model the structure ofproteins/domains assemblies ?
iViv 2010, Journées de rentrée des doctorants
How to predict protein assemblies ?
104 decoys
1 most likely model
Filters
~ 10 decoys
Surface complementarities
Physico-chemestry features
Evolution data
iViv 2010, Journées de rentrée des doctorants
Thesis Goals
104 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 ?
iViv 2010, Journées de rentrée des doctorants
Can conservation leads protein assemblies ?
= conserved
AB interface
Interface conservation
Complex A-B
% o
f com
plex
es
Ratio of conserved residues part of a given interface ~ 30 %
% of all conserved residues
interface
protein
Lack of specificity to predict
iViv 2010, Journées de rentrée des doctorants
Evolutionary rates as relevant interface signals ?
Lif1 S. cerevisiaeXRCC4 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
iViv 2010, Journées de rentrée des doctorants
Evolutionary rates as relevant interface signals ?An example from the DNA repair interaction network
Lif1 S. cerevisiaeXRCC4 H. sapiens
Nej1 S. cerevisiae Cernunnos H. sapiens
conservation
BRCTDNA ligase
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)
2 4 6 8 10 12 14iRMS
Inte
rfac
e E
nerg
y-3
0-2
0-1
0
Rosetta Score (min vs all)Local perturbations, Optimisations of the
interactions… search for funnels
Step 2
Step 1Filter solutions using evolutionnary rates
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
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
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
iViv 2010, Journées de rentrée des doctorants
How to build an interolog database ?
G. Faure et al, in prep.
350 groups of structural interologs2500 groups of interologs
Extracting and cleaning heterocomplexTrue heteromer biological interfaces …
Redundancy traitement
2500 Non redundant interfaces
iViv 2010, Journées de rentrée des doctorants
How to explore coevolution ?
A PyMol plugin to visualize Structure and alignments
Data and Querying Serverat
http://biodev.extra.cea.fr/lbsr/
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
iViv 2010, Journées de rentrée des doctorants
iViv 2010, Journées de rentrée des doctorants
XXX heteromeric complexes
Redundancy filters
Coupled alignments for orthologous
sequences for both partners
ClusteringFamilies &
Superfamilies
Biological vs
non biological interfaces
XXXstructural interologs
NoXclass HHsearchMatras
XXX non redundant
interfaces
InterEvol : Automatic and self-updating interface databasefor extracting structural and evolutionary information
Querying Serverat
http://biodev.extra.cea.fr/lbsr/
Pymol pluginfor interfacecoevolution
visualisation
iViv 2010, Journées de rentrée des doctorants
How to study coevolution ?
Querying Serverat
http://biodev.extra.cea.fr/lbsr/
iViv 2010, Journées de rentrée des doctorants
iViv 2010, Journées de rentrée des doctorants
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
iViv 2010, Journées de rentrée des doctorants
How to explore coevolution at interfaces ?
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
iViv 2010, Journées de rentrée des doctorants
RPN1
HSM3
RPT5RPT2
RPT1
conservation score
Conservation analyses
Which evolutionary signals at protein surfaces can be capturedto identify the interaction sites ?
conservation
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
% o
f co
mpl
exes
Which ratio of conserved residues are part of the interface ?
% of all conserved residues
interface
protein
iViv 2010, Journées de rentrée des doctorants
Evolutionary rates do not provide mutual information between interacting surfaces …
iViv 2010, Journées de rentrée des doctorants
Protein A Protein B
i j
A/B complexij
90°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
HumanMouseFish
Yeast
…
Madaoui & Guerois, PNAS 2008
HydrophobicPolarAcidicBasic
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
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 Conserved Residues
Docking under constrains with Haddock (Bonvin’s group)
iViv 2010, Journées de rentrée des doctorants
The evolutionary dimension should provide key informationto exploit interaction data under a structural perspective
iViv 2010, Journées de rentrée des doctorants
2 majors issues
Difficulties to identify orthologs
How to characterize selection pressure at the interface
iViv 2010, Journées de rentrée des doctorants
2 majors issues
Difficulties to identify orthologs
How to characterize selection pressure at the interface
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
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
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
Seq
uen
ces
fro
m P
SIB
LA
ST
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
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
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
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
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
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
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
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))
% o
f co
mpl
exes
Which ratio of conserved residues are part of the interface ?
% of all conserved residues
interface
protein
iViv 2010, Journées de rentrée des doctorants
RPN1
HSM3
RPT5RPT2
RPT1
conservation score
Conservation analyses
Which evolutionary signals at protein surfaces can be capturedto identify the interaction sites ?
conservation
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