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Advanced Bioinformatics
Lecture 3: Protein-protein interaction
ZHU FENG
[email protected]
http://idrb.cqu.edu.cn/
Innovative Drug Research Centre in CQU
创新药物研究与生物信息学实验室
Table of Content
1. Protein-protein interaction
2. Interaction representations
3. Method A: Two-hybrid assay
4. Method B: Affinity purification
5. Spoke and matrix models of PPI
2
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.
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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.
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Interaction representation
Enzyme + Substrate
Kinase-ATP complex + inactive-enzyme ==> Kinase + ADP + active enzyme
K
P
ATP
ADP
One representation
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Interaction representation
Inactive
enzyme
Kinase-ATP
complex
Active
enzyme
ADP
Another representation
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Generalization of the representation
A
C
B
D
E
…
F
A biomolecule’s function can be defined by the things that it interacts
Makes
it easy
focus on
the interaction
part
with and
the new
(or toaltered)
molecules
that result
from that
interaction.
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A simple record
A
01. Short label for A
03. Molecule type for A
05. Database reference for A
07. Where A comes from
09. Interaction Kinetics
10. Publication reference
B
02. Short label for B
04. Molecule type for B
06. Database reference for B
08. Where B comes from
The minimal record has 10 pieces of information
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An example record
A
B
01. EGF
02. EGFR
03. Protein
04. Protein
05. OMIM: 131530
06. OMIM: 131550
07. Homo sapiens
08. Homo sapiens
09. Equilibrium dissociation constant (Kd) = 130 nM
10. Cancer Cell 7(4):301-311, 2005
You can view this record in BIND (http://bind.ca/) with ID: 263509
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BIND stores molecular interaction data
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BIND interaction types
Specify method used to confirm the interaction, what method?
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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
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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.
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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. 1989 Jul 20;340(6230):245-6.
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Two-hybrid assay
SNF4
1.
SNF1
UASG
B
A
2.
3.
Reporter Gene
4.
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Two-hybrid assay
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Two-hybrid assay
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Some two-hybrid caveats
1.
A
2.
3.
4.
Does the DBD-fusion have activity by itself?
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Some two-hybrid caveats
1.
C B
A
2.
3.
4.
Is the ‘interaction’ mediated by some other protein?
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Some two-hybrid caveats
1.
B
A
2.
3.
4.
Is the ‘interaction’ bi-directional?
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Method B: Affinity purification
A
Protein of
interest
This molecule will
bind the ‘tag’
Tag modification
(e.g. HA/GST/His)
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Affinity purification
The cell
A
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Affinity purification
Lots of other
untagged proteins
A
B
Naturally binding protein
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Affinity purification
Ruptured
membranes
A
B
Cell extract
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Affinity purification
A
B
Untagged proteins go through fastest (flow-through)
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Affinity purification
A
B
Tagged complexes are slower and come out later (eluate)
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Some affinity purification caveats
Firstly, this is only a representation of observation
A
You can only tell what proteins are in the eluate
B
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
A
B
C
But, what if I told you that two other proteins (B
and C) were present along with A …
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Complex with unknown binding topology
A
B
A
C
B
A
C
B
C
Which of these models is correct?
The complex described by this experimental result is said to have
an unknown topology.
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Complexes with unknown stoichiometry
A
B
A
C
Here’s another possibility?
The complex described by this experimental result is also said to
have unknown stoichiometry.
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Spoke and matrix models of PPI
Spoke
Simple, intuitive, more
accurate, but can
misrepresent
Possible Actual
Topology
Matrix
Theoretical max. no.
of interactions, but
many FPs
Bader GD, et al. Nat Biotechnol. 2002 20(10):991-7.
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Synthetic genetic interactions in yeast
Cell Polarity
Cell Wall Maintenance
Cell Structure
Mitosis
Chromosome Structure
DNA Synthesis
DNA Repair
Unknown
Others
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Network of the human interactome
Each point represents
a protein and each
line between them is
an interaction
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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.
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Yeast interactome project
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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.
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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.
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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.
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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.
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Projects Q&A!
1. Biological pathway simulation
2. Computer-aided anti-cancer drug design
3. Disease-causing mutation on drug target
Any questions? Thank you!
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