1. Advanced Bioinformatics
Lecture 3: Protein-protein interaction
ZHU FENG
Innovative Drug Research Centre in CQU
创新药物研究与生物信息学实验室

2. Table of Content Protein-protein interaction
Interaction representations
Method A: Two-hybrid assay
Method B: Affinity purification
Spoke and matrix models of PPI 2

3. Protein–protein interaction (PPI)
The horseshoe shaped ribonuclease inhibitor (shown as wireframe) forms a protein–protein interaction with the ribonuclease protein. The contacts (non-covalent interaction) between the two proteins are shown as colored patches. 3

4. Central importance for processes in cell
Signal transduction: signals from the exterior of a cell are mediated inside by PPI of the signaling molecules.
Protein transportation: from cytoplasm to nucleus or vice versa in the case of the nuclear pore importins.
Protein modification: a protein kinase will add a phosphate to a target protein.
Chain interaction: proteins with SH2 domains only bind to other proteins when they are phosphorylated on the amino acid tyrosine while specifically recognize acetylated lysines. 4

5. Interaction representation
Enzyme + Substrate
Kinase-ATP complex + inactive-enzyme ==> Kinase + ADP + active enzyme K P
ATP
ADP
One representation 5

6. Interaction representation Another representation
Inactive enzyme
Kinase-ATP complex
Active enzyme
ADP
Another representation 6

7. … Generalization of the representationB … C D E F
A biomolecule’s function can be defined by the things that it interacts with and the new (or altered) molecules that result from that interaction.
Makes it easy to focus on the interaction part 7

8. The minimal record has 10 pieces of information
A simple record A B
01. Short label for A 02. Short label for B 03. Molecule type for A 04. Molecule type for B
05. Database reference for A 06. Database reference for B 07. Where A comes from 08. Where B comes from
09. Interaction Kinetics
10. Publication reference
The minimal record has 10 pieces of information 8

9. You can view this record in BIND (http://bind.ca/) with ID: 263509
An example record A B
01. EGF EGFR 03. Protein Protein
05. OMIM: OMIM: Homo sapiens Homo sapiens
09. Equilibrium dissociation constant (Kd) = 130 nM
10. Cancer Cell 7(4): , 2005
You can view this record in BIND ( with ID: 9

10. BIND stores molecular interaction data10

11. BIND interaction types
Specify method used to confirm the interaction, what method? 11

12. Methods for detecting interactions
Many interactions in BIND originates from high-throughput experiments designed to detect interactions between proteins
The most common methods are
Two-hybrid assay
Affinity purification 12

13. Methods comparison
Yeast two hybrid screens allow for interactions between proteins that are never expressed in the same time and place, lowering the specificity, but better indicate non-specific tendencies towards sticky interactions
Affinity purification better indicates functional in vivo protein-protein interactions. 13

14. Method A: Two-hybrid assay
Transcription activation domain (AD) 1.
Transcriptional activator (TA) 2. 3.
Gene
Promoter
DNA-binding domain (BD) 4.
Fields S, et al. Nature Jul 20;340(6230):245-6. 14

15. Two-hybrid assay
SNF4 1.
SNF1 B A 2. 3.
UASG
Reporter Gene 4. 15

16. Two-hybrid assay 16

17. Two-hybrid assay 17

18. Some two-hybrid caveats Does the DBD-fusion have activity by itself?1. A 2. 3. 4.
Does the DBD-fusion have activity by itself? 18

19. Some two-hybrid caveats1. C B A 2. 3. 4.
Is the ‘interaction’ mediated by some other protein? 19

20. Some two-hybrid caveats Is the ‘interaction’ bi-directional?1. B A 2. 3. 4.
Is the ‘interaction’ bi-directional? 20

21. Method B: Affinity purification
This molecule will bind the ‘tag’ A
Tag modification (e.g. HA/GST/His)
Protein of interest 21

22. Affinity purification
The cell A 22

23. Affinity purification
Lots of other untagged proteins A B
Naturally binding protein 23

24. Affinity purification
Ruptured membranes A B
Cell extract 24

25. Affinity purificationB
Untagged proteins go through fastest (flow-through) 25

26. Affinity purificationB
Tagged complexes are slower and come out later (eluate) 26

27. Some affinity purification caveats
Firstly, this is only a representation of observation
You can only tell what proteins are in the eluate
You can’t tell how they are connected If there is only one other protein present (B), then its likely that A and B are directly interacting
But, what if I told you that two other proteins (B and C) were present along with A … B A C B 27

28. Complex with unknown binding topologyA A A B C B C B C
Which of these models is correct?
The complex described by this experimental result is said to have an unknown topology. 28

29. Complexes with unknown stoichiometry Here’s another possibility?
The complex described by this experimental result is also said to have unknown stoichiometry. 29

30. Spoke and matrix models of PPI
Possible Actual
Topology
Spoke
Matrix
Simple, intuitive, more accurate, but can misrepresent
Theoretical max. no. of interactions, but many FPs
Bader GD, et al. Nat Biotechnol (10):991-7. 30

31. Synthetic genetic interactions in yeast
Cell Polarity
Cell Wall Maintenance
Cell Structure
Mitosis
Chromosome Structure
DNA Synthesis
DNA Repair
Unknown
Others 31

32. Network of the human interactome
Each point represents a protein and each line between them is an interaction 32

33. Network motifs found in networks
The feed-forward loop, bi-fan and biparallel are over-represented, whereas feedback loop is under-represented in gene regulatory networks and neuronal connectivity networks. 33

34. Yeast interactome project34

35. Interactome data analysis (1)
Validation of interactome’s coverage and quality
Interactomes are never complete, given the limitations of experimental methods. For instance, it has been estimated that typical Y2H screens detect only 25% or so of all interactions in an interactome.
The coverage of an interactome can be assessed by comparing it to benchmarks of well-known interactions that have been found and validated by independent assays. 35

36. Interactome data analysis (2)
Protein function prediction
Assumption: uncharacterized proteins have similar functions as their interacting proteins. For example, YbeB with unknown function was found to interact with ribosomal proteins and later shown to be involved in translation.
Although such predictions may be based on single interactions, usually several interactions are found. Thus, the whole network of interactions can be used to predict protein functions, given that certain functions are usually enriched among the interactors. 36

37. Interactome data analysis (3)
Perturbations and disease
The topology of an interactome makes it possible to predict how a network reacts to the perturbation (e.g. removal) of nodes (proteins) or edges (interactions).
Mutations of genes (and thus their proteins) can cause perturbations of networks and thus disease. 37

38. Interactome data analysis (4)
Network structure and modules
The distribution of properties among the proteins of an interactome has revealed functional modules within a network that indicate specialized subnetworks.
Such modules can be purely functional, as in a signaling pathway, or structural, as in a protein complex. In fact, it is a formidable task to identify protein complexes in an interactome, given that typically no affinities are known. 38

39. Any questions? Thank you!
Projects Q&A!
Biological pathway simulation
2. Computer-aided anti-cancer drug design
3. Disease-causing mutation on drug target
Any questions? Thank you! 39