Guilhem FAURE

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


Macromolecules in cellulo

Experimental insights into the protein interactions space ?

High resolutionapproches

Synergies/CompetitionsMolecular vision

High throughputapproaches

Large scale vision


Translate each node of the interaction networks into a 3D structure ?

Experimental structuresHomology models ?

How to model the structure ofproteins/domains assemblies ?


How to predict protein assemblies ?

104 decoys

1 most likely model

Filters

~ 10 decoys

Surface complementarities

Physico-chemestry features

Evolution data


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 ?


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


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


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


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


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


: 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


How to study coevolution : concept of interology

Same ancestor = homolog

Same evolution profil + same fold

Same interaction involving same partners=

INTEROLOGS

Same interface


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


How to explore coevolution ?

A PyMol plugin to visualize Structure and alignments

Data and Querying Serverat

http://biodev.extra.cea.fr/lbsr/


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



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


Pymol pluginfor interfacecoevolution

visualisation


How to study coevolution ?

Querying Serverat




How to find coevolution ?


An interolog structural databank (350 groups of interologs)

same fold+

same evolutif profil+

same interaction area


How to explore coevolution at interfaces ?


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


RPN1

HSM3

RPT5RPT2

RPT1

conservation score

Conservation analyses

Which evolutionary signals at protein surfaces can be capturedto identify the interaction sites ?

conservation


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 ?


interface

protein


Evolutionary rates do not provide mutual information between interacting surfaces …


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


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


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)


The evolutionary dimension should provide key informationto exploit interaction data under a structural perspective


2 majors issues

Difficulties to identify orthologs

How to characterize selection pressure at the interface


2 majors issues

Difficulties to identify orthologs

How to characterize selection pressure at the interface


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





An interolog structural databank (350 structures)

A B

A’ B’

same fold+

Same evolutif profil

Rajouter les % id




An interolog sequence databank (2300 alignments)

…

at least 30% of identity

Initial structure

Seq

uen

ces

fro

m P

SIB

LA

ST




PISA 1 (PDB complex assemblies)







Cleaned true heteromer







Non redundant PDB structures databank








Non redundant heterodimer databank

SCOTCHAlign databank








Non redundant heterodimer databank

SCOTCHAlign databank

Interolog databank


Through multidimensionnal data: InterEvolVisu



Photo du plugin sur un exemple


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


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 ?


interface

protein


RPN1

HSM3

RPT5RPT2

RPT1

conservation score

Conservation analyses

Which evolutionary signals at protein surfaces can be capturedto identify the interaction sites ?

conservation


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

Documents

Guilhem FAURE