Transcript Bioinformatik - Brigham Young University

Protein-protein interactions
Chapter 12
Stable vs. transient
protein-protein interactions
Stable complex
Transient Interaction
Stable complex:
homodimeric citrate synthase
Transient Signaling
Complex Rap1A – cRaf1
Interface
4890 Å2
Hydrophobic interfaces
Interface
1310 Å2
“Hydrophilic” interfaces
Multi-domain protein
Using publicly available interaction data
Are there know interaction partners for you pet protein?
Check if:
1. There are interactors for your protein in the literature
2. There are databases of interactions where your protein may appear
3. There are homologues of your protein in the protein interaction databases
4. You can predict interactors by other means?
5. This failing, at this point you go back to the bench…
Using publicly available interaction data
1. Are there interactors for my protein in the literature ?
Problems:
•Low coverage
•Does not include results from high throughput experiments
•Gene names may not be consistent
Using publicly available interaction data
2. Are there databases of interactions where my protein may appear?
Some DBs:
BIND, MINT (General) + organism specific databases (e.g. MIPS/CYGD)
Caution! Check:
-the experimental methods used to identify the interaction
(e.g. high error rate in large scale yeast-two hybrids)
-check the method used to incorporate the interaction in the database
(e.g. manual curation vs. literature mining using “intelligent” algorithms)
Experimental techniques
Yeast two-hybrid screens
MS analysis of tagged complexes
Correlated mRNA expression levels
Tagged protein
Protein A
Protein B
Protein C
Purified complex with 3 proteins
3 proteins separated
by gel electrophoresis
3 proteins identifi ed by
mass spectrometry
Experimental techniques
Yeast two-hybrid screens
MS analysis of tagged complexes
Correlated mRNA expression levels
90% of genes with conserved co-expression
are members of stable complexes
Use microarrays to identify co-expression
How good is the data?
(von Mering et al., Nature 417:399)
How good is the data?
(von Mering et al., Nature 417:399)
”We estimate that more than half of all current
high-throughput interaction data are spurious”
Computational prediction of protein interactions
Gene fusion events
Tryptophan synthetase a b fusion
TrpC
TrpF
1PII
Enright et al (1999) Nature 409:86
Marcotte et al (1999) Science 285: 751
Fused in E.coli
Unfused in some other genomes
(Synechocystis sp. and Thermotoga maritima.)
Computational prediction of protein interactions
Phylogenetic profiles
Pellegrini et al (1999) PNAS 96: 4285
Computational prediction of protein interactions
Pre-computed predictions: where to find them?
Identification of functional modules from protein interaction data
Messy data
Functional modules
Graph theory
formalisms
Pereiral-Leal, Enright and Ouzounis (2003) Proteins in press
Custering
DIP database
• Documents protein-protein
interactions from
experiment
– Y2H, protein microarrays,
TAP/MS, PDB
• 55,733 interactions
between 19,053 proteins
from 110 organisms.
Organisms
# proteins # interactions
Fruit fly
7052
20,988
H. pylori
710
1425
Human
916
1407
E. coli
1831
7408
C. elegans
2638
4030
Yeast
4921
18,225
Others
985
401
14
DIP database
Duan et al., Mol Cell Proteomics, 2002
• Assess quality
– Via proteins: PVM, EPR
– Via domains: DPV
• Search by BLAST or
identifiers / text
• URL
• Dyrk1a GI 24418935
15
DIP database
Duan et al., Mol Cell Proteomics, 2002
• Assess quality
– Via proteins: PVM, EPR
– Via domains: DPV
• Search by BLAST or
identifiers / text
• Map expression data
16
DIP/LiveDIP
Duan et al., Mol Cell Proteomics, 2002
• Records biological state
– Post-translational
modifications
– Conformational changes
– Cellular location
17
DIP/Prolinks database
Bowers et al., Genome Biol, 2004.
• Records functional
association using
prediction methods:
–
–
–
–
Gene neighbors
Rosetta Stone
Phylogenetic profiles
Gene clusters
18
Other functional association databases
• Phydbac2 (Claverie)
• Predictome (DeLisi)
• ArrayProspector (Bork)
19
BIND database
Alfarano et al., Nucleic Acids Res, 2005
• Records experimental
interaction data
• 83,517 protein-protein
interactions
• 204,468 total interactions
• Includes small molecules,
NAs, complexes
• URL
20
BIND database
• Displays unique icons
of functional classes
21
MPact/MIPS database
Guldener et al., Nucleic Acids Res, 2006
• Records yeast
protein-protein
interactions
• Curates interactions:
– 4,300 PPI
– 1,500 proteins
22
STRING database
von Mering et al., Nucleic Acids Res., 2005
• Records experimental
and predicted proteinprotein interactions
using methods:
–
–
–
–
Genomic context
High-throughput
Coexpression
Database/literature
mining
– URL
23
STRING database
• Graphical interface for each of the evidence types
• Benchmark against Kegg pathways for rankings
24
STRING database
• 736,429 proteins in 179 species
• Uses COGs and homology to transfer annotation
25
More interaction databases
• IntAct (Valencia)
– Open source interaction database and analysis
– 68,165 interactions from literature or user submissions
• MINT (Cesareni)
– 71,854 experimental interactions mined from literature by
curators
– Uses IntAct data model
• BioGRID (Tyers)
– 116,000 protein and genetic interactions
26
InterDom database
Ng et al., Nucleic Acids Res, 2003
• Predicts domain
interactions (~30000)
from PPIs
• Data sources:
–
–
–
–
Domain fusions
PPI from DIP
Protein complexes
Literature
• Scores interactions
27
Definition of CBM
• Interacting domain pair – if at least 5
residue-residue contacts between domains
(contacts – distance of less than 8 Ǻ)
• Structure-structure alignments between
all proteins corresponding to a given pair
of interacting domains
• Clustering of interface similarity, those
with >50% equivalently aligned positions
are clustered together
• Clusters with more than 2 entries define
conserved binding mode.
28
DIMA database
Pagel et al., Bioinformatics, 2005
• Phylogenetic profiles of
Pfam domain pairs
• Uses structural info
from iPfam
• Works well for
moderate information
content
29
So.. You know your two proteins interact…
do you want to know how?
Prediction of the molecular basis of protein
interactions
Molecular basis of protein interaction
“Tree determinant residues”
Rab
REP
MSA
REP
x
Ras
Rho
Arf
Ran
Prediction
_
Experimental
tests
Pereira-Leal and Seabra (2001) J. Mol. Biol.
Pereira-Leal et al (2003) Biochem. Biophys. Res. Com.
+
Molecular basis of protein interaction
“Tree determinant residues”
Continued…
Sequence Space algorithm
AMAS
(part of a bigger package)
Casari et al (1995) Nat. Struct. Biol 2(2)
Molecular basis of protein interaction
In silico docking
Requires 3D structures of
components
Conformational changes
cannot be considered
(rigid body)