1. Protein-protein Interactions
May 2, 2016

2. Why PPI?
Protein-protein interactions determine outcome of most cellular processes
Proteins which are close homologues often interact in the same way
Protein-protein interactions place evolutionary constraints on protein sequence and structural divergence
Pre-cursor to networks

3. PPI classification Strength of interaction Specificity
Permanent or transient
Specificity
Location within polypeptide chain
Similarity of partners
Homo- or hetero-oligomers
Direct (binary) or a complex
Confidence score

4. Determining PPIs Small-scale methods Co-immunoprecipitation
Affinity chromatography
Pull-down assays
In vitro binding assays
FRET, Biacore, AFM
Structural (co-crystals)

5. PPIs by high-throughput methods
Yeast two hybrid systems
Affinity tag purification followed by mass spectrometry
Protein microarrays
Microarrays/gene co-expression
Implied functional PPIs
Synthetic lethality
Genetic interactions, implied functional PPIs

6. Yeast two hybrid system
Gal4 protein comprises DNA binding and activating domains
Binding domain interacts with promoter
Activating domain interacts with polymerase
Measure reporter enzyme activity (e.g. blue colonies)

7. Yeast two hybrid system
Gal4 protein: two domains do not need to be transcribed in a single protein
If they come into close enough proximity to interact, they will activate the RNA polymerase
Two other protein domains (A & B) interact
Activating domain interacts with polymerase
Binding domain interacts with promoter A B
Measure reporter enzyme activity (e.g. blue colonies)

8. Yeast two hybrid system
This is achieved using gene fusion
Plasmids carrying different constructs can be expressed in yeast
Binding domain as a translational fusion with the gene encoding another protein in one plasmid.
Activating domain as a translational fusion with the gene encoding a different protein in a second plasmid. A B
If the two proteins interact, then GAL4 is expressed and blue colonies form

9. Yeast two hybrid Advantages Limitations
Fairly simple, rapid and inexpensive
Requires no protein purification
No previous knowledge of proteins needed
Scalable to high-throughput
Is not limited to yeast proteins
Limitations
Works best with cytosolic proteins
Tendency to produce false positives
Necessity for nuclear localization for interactions to occur
Can get activation of the reporter gene in the absence of a true PPI

10. Mass spectrometry Need to purify protein or protein complexes
Use a affinity-tag system
Need efficient method of recovering fusion protein in low concentration

11. TAP (tandem affinity purification)
PCR product
Spacer
TEV site
Protein A
CBP
Homologous recombination
Chromosome
CBP calmodulin binding protein
ProtA protein A
Both allow efficient recovery of a fusion protein (80 % 50% respectively) from low concentration
TEV (tobacco etch virus) protease cleavage site to allow proteolytic release of material under native conditions
Fusion of TAP tag to target protein
Introduction of target into host cell, maintain expression of fusion protein at close to natural level
Fusion protein and associated components are recovered from cell extracts by affinity purification on IgG matrix
After washing, TEV protease added to release bound material
Eluate incubated with Calmodulin-coated beads in presence of Ca. This is required to remove TEV protease and other minor contaminants
Bound material then released with EDTA
Fusion protein
Protein
Spacer
TEV site
Protein A
CBP
Calmodulin binding peptide

12. TAP process "Taptag simple" by Chandres - Own work.
Licensed under CC BY-SA 3.0 via Wikimedia Commons

13. TAP Advantages No prior knowledge of complex composition
Two-step purification increases specificity of pull-down
Limitations
Transient interactions may not survive 2 rounds of washing
Tag may prevent interactions
Tag may affect expression levels
Works less efficiently in mammalian cells
TAP tag is 21 kDa; large enough to affect folding, activity or interaction of the fusion protein with other proteins in the cell

14. Other tags HA, Flag and His Streptavidin binding peptide (SBP)
Anti-tag antibodies can interfere with MS analysis
Streptavidin binding peptide (SBP)
High affinity for streptavidin beads
10-fold increase in efficiency of purification compared to conventional TAP tag
Successfully used to identify components of complexes in the Wnt/b-catenin pathway
HA, FlAG and HIS tags are smaller than TAP, which may eliminate some issues of interference

15. Used Dsh-2 and Dsh-3 as bait proteins
The KLHL12-Cullin-3 ubiquitin ligase negatively regulates Wnt-b-catenin pathway by targeting Dishevelled for degradation
Nature Cell Biology 4: (2006)

16. Binding partners of Bruton’s tyrosine kinase
Role in lymphocyte development & B-cell maturation
Protein Science 20: (2011)

19. Databases of protein-protein interactions
MINT – Molecular Interaction Database
>240,000 interactions with 35,000 proteins
Covers multiple species
DIP -- Database of Interacting Proteins (UCLA)
>79,000 interactions with >27,000 proteins
CCSB – Proteomics base interactomes (Harvard)
Human, viruses, C. elegans, S. cerevisiae
Some unpublished data
IntAct – EBI molecular interaction database
Curated data from multiple sources

20. EBI IntAct Submit single or lists of proteins
Provides method and reference for interactions
List format, can download easily

21. STRING database Search Tool for the Retrieval of Interacting Genes
Integrates information from existing PPI data sources
Provides confidence scoring of the interactions
Periodically runs interaction prediction algorithms on newly sequenced genomes
v.10 covers >2000 organisms

22. Networks in STRING database
Starting protein
Nice graphical view
Not so easy to download lists of data

23. Networks can be expanded
3 indirect interactions

24. Information about the proteins

25. Accessing Interaction data
From a UniprotKB (reviewed record):

26. Transferring PPI annotation
Most of the high-throughput PPI work is done in model organisms
Can you transfer that annotation a homologous gene in a different organism?

27. Defining homologs
Orthologue of a protein is usually defined as the best-matching homolog in another species
Candidates with significant BLASTP E-value (<10-20)
Having ≥80% of residues in both sequences included in BLASTP alignment
Having one candidate as the best-matching homologue of the other candidate in corresponding organism

28. Interologs
If two proteins, A and B, interact in one organism and their orthologs, A’ and B’, interact in another species, then the pair of interactions A—B and A’—B’ are called interologs
Align the homologs (A & A’, B & B’) to each other.
Determine the percent identity and the E-value of both alignments
Then calculate the Joint identity and the Joint Evalue
Joint E-value
Joint identity

29. Transfer of annotation
Compared interaction datasets between yeast, worm and fly
Assessed chance that two proteins interact with each other based on their joint sequence identities
Performed similar analysis based on joint E-values
All protein pairs with JI ≥ 80% with a known interacting pair will interact with each other
More than half of protein pairs with JE  E-70 could be experimentally verified.
Yu, H. et. al. (2004) Genome Res. 14:
PMID:

30. Examples of Protein-Protein Interologs
In C. elegans, mpk-1 was experimentally shown to interact with 26 other proteins (by yeast 2-hybrid)
Ste5 is the homolog of Mpk-1 in S. cerevisiae
Based on the similarity between the interaction partners of mpk-1 and their closest homologs in S. cerevisiae, the interolog approach predicted 5 of the 6 subunits of the Ste5 complex in S. cerevisiae

31. This paper has been cited >100 times
Why the interest in predicting protein-protein interactions?
Determining protein-protein interactions is challenging and the high-throughput (genome-wide) methods are still difficult and expensive to conduct
Identifying candidate interaction partners for a targeted pull-down assay is a more viable strategy for most labs

32. BIPS: BIANA Interolog Prediction Server
Based on concept of interolog
Pre-defined alignments
Can submit list of proteins to get predicted interaction partners
Can filter predicted list to increase confidence

33. Today in computer lab Finding PPIs in your sublist using IntAct
Exploring a subset of PPIs using the STRING database
Prediction of interactions homologs using the BIPS server
Continue Exercise 5 on protein analyses by exploring possible PPI for your select genes