protein-protein interactions chapter 12. stable complex transient interaction transient signaling...
TRANSCRIPT
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Protein-protein interactions
Chapter 12
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Stable complex Transient Interaction
Transient Signaling Complex Rap1A – cRaf1
Interface 1310 Å2
Stable complex: homodimeric citrate synthase
Interface 4890 Å2
Hydrophobic interfaces “Hydrophilic” interfaces
Stable vs. transientprotein-protein interactions
Multi-domain protein
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Using publicly available interaction data
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…
Are there know interaction partners for you pet protein?Check if:
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Using publicly available interaction data
Problems:•Low coverage•Does not include results from high throughput experiments•Gene names may not be consistent
1. Are there interactors for my protein in the literature ?
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Using publicly available interaction data2. 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)
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Experimental techniques
Yeast two-hybrid screens
MS analysis of tagged complexes
Correlated mRNA expression levels Tagged protein
Protein AProtein BProtein C
Purified complex with 3 proteins3 proteins separated 3 proteins identified byby gel electrophoresis mass spectrometry
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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 complexesUse microarrays to identify co-expression
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How good is the data?(von Mering et al., Nature 417:399)
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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”
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Computational prediction of protein interactions
Tryptophan synthetase fusion
1PII
TrpC TrpF
Fused in E.coliUnfused in some other genomes(Synechocystis sp. and Thermotoga maritima.)
Enright et al (1999) Nature 409:86Marcotte et al (1999) Science 285: 751
Gene fusion events
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Pellegrini et al (1999) PNAS 96: 4285
Computational prediction of protein interactions
Phylogenetic profiles
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Computational prediction of protein interactionsPre-computed predictions: where to find them?
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Identification of functional modules from protein interaction data
Graph theory
formalisms
Custering
Messy data Functional modules
Pereiral-Leal, Enright and Ouzounis (2003) Proteins in press
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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
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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
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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
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DIP/LiveDIP
Duan et al., Mol Cell Proteomics, 2002
• Records biological state– Post-translational
modifications
– Conformational changes
– Cellular location
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DIP/Prolinks database
Bowers et al., Genome Biol, 2004.
• Records functional association using prediction methods:– Gene neighbors
– Rosetta Stone
– Phylogenetic profiles
– Gene clusters
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Other functional association databases
• Phydbac2 (Claverie)• Predictome (DeLisi)• ArrayProspector (Bork)
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BIND database
• Records experimental interaction data
• 83,517 protein-protein interactions
• 204,468 total interactions
• Includes small molecules, NAs, complexes
• URL
Alfarano et al., Nucleic Acids Res, 2005
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BIND database
• Displays unique icons of functional classes
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MPact/MIPS database
• Records yeast protein-protein interactions
• Curates interactions:– 4,300 PPI
– 1,500 proteins
Guldener et al., Nucleic Acids Res, 2006
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STRING database
• Records experimental and predicted protein-protein interactions using methods:– Genomic context
– High-throughput
– Coexpression
– Database/literature mining
– URL
von Mering et al., Nucleic Acids Res., 2005
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STRING database
• Graphical interface for each of the evidence types
• Benchmark against Kegg pathways for rankings
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STRING database
• 736,429 proteins in 179 species
• Uses COGs and homology to transfer annotation
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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
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InterDom database
• Predicts domain interactions (~30000) from PPIs
• Data sources:– Domain fusions
– PPI from DIP
– Protein complexes
– Literature
• Scores interactions
Ng et al., Nucleic Acids Res, 2003
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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.
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DIMA database
Pagel et al., Bioinformatics, 2005
• Phylogenetic profiles of Pfam domain pairs
• Uses structural info from iPfam
• Works well for moderate information content
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Prediction of the molecular basis of protein interactions
So.. You know your two proteins interact… do you want to know how?
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Molecular basis of protein interaction
“Tree determinant residues”
Rab
RasRhoArfRan
x
REP
REP
+
_
MSA
Prediction
Experimentaltests
Pereira-Leal and Seabra (2001) J. Mol. Biol.Pereira-Leal et al (2003) Biochem. Biophys. Res. Com.
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Molecular basis of protein interaction
“Tree determinant residues”
Continued…
Sequence Space algorithm
Casari et al (1995) Nat. Struct. Biol 2(2)
AMAS(part of a bigger package)
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Molecular basis of protein interaction
In silico docking
Requires 3D structures of components
Conformational changes cannot be considered(rigid body)