Title: Essential Bioinformatics and Biocomputing (LSM2104: Section I) Biological Databases and Bioinformatics Software Prof. Chen Yu Zong Tel: 6874-6877 Email: csccyz@nus.edu.sg http://xin.cz3.nus.edu.sg Room 07-24, level 7, SOC1, NUS January 2003
1Advanced Bioinformatics Lecture 3
Protein-protein interaction
ZHU FENG zhufeng_at_cqu.edu.cn http//idrb.cqu.edu.cn
/ Innovative Drug Research Centre in CQU
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2Table of Content
- Protein-protein interaction
- Interaction representations
- Method A Two-hybrid assay
- Method B Affinity purification
- Spoke and matrix models of PPI
2
3Proteinprotein interaction (PPI)
The horseshoe shaped ribonuclease inhibitor
(shown as wireframe) forms a proteinprotein
interaction with the ribonuclease protein. The
contacts (non-covalent interaction) between the
two proteins are shown as colored patches.
3
4Central 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
5Interaction representation
Enzyme Substrate Kinase-ATP complex
inactive-enzyme gt Kinase ADP active enzyme
K
P
ATP
ADP
5
6Interaction representation
Kinase-ATPcomplex
Inactiveenzyme
Activeenzyme
ADP
Another representation
6
7Generalization of the representation
B
A
C
D
E
F
A biomolecules 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
8A simple record
B
A
01. Short label for A 02. Short label for B03.
Molecule type for A 04. Molecule type for B 05.
Database reference for A 06. Database reference
for B07. Where A comes from 08. Where B comes
from 09. Interaction Kinetics 10. Publication
reference
The minimal record has 10 pieces of information
8
9An example record
B
A
01. EGF 02. EGFR03. Protein 04. Protein 05.
OMIM 131530 06. OMIM 13155007. 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
9
10BIND stores molecular interaction data
10
11BIND interaction types
Specify method used to confirm the interaction,
what method?
11
12Methods 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
13Methods 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
14Method A Two-hybrid assay
Transcription activation domain (AD)
1.
Transcriptional activator (TA)
3.
2.
Gene
Promoter
DNA-binding domain (BD)
4.
Fields S, et al. Nature. 1989 Jul
20340(6230)245-6.
14
15Two-hybrid assay
SNF4
1.
B
SNF1
A
3.
2.
UASG
Reporter Gene
4.
15
16Two-hybrid assay
16
17Two-hybrid assay
17
18Some two-hybrid caveats
1.
A
3.
2.
4.
Does the DBD-fusion have activity by itself?
18
19Some two-hybrid caveats
1.
B
C
A
3.
2.
4.
Is the interaction mediated by some other
protein?
19
20Some two-hybrid caveats
1.
B
A
3.
2.
4.
Is the interaction bi-directional?
20
21Method B Affinity purification
This molecule will bind the tag
A
Tag modification(e.g. HA/GST/His)
Protein of interest
21
22Affinity purification
The cell
A
22
23Affinity purification
Lots of other untagged proteins
A
B
Naturally binding protein
23
24Affinity purification
Ruptured membranes
A
B
Cell extract
24
25Affinity purification
A
B
Untagged proteins go through fastest
(flow-through)
25
26Affinity purification
A
B
Tagged complexes are slower and come out later
(eluate)
26
27Some affinity purification caveats
A
Firstly, this is only a representation of
observation You can only tell what proteins are
in the eluate You cant tell how they are
connectedIf 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
28Complex with unknown binding topology
A
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
29Complexes with unknown stoichiometry
A
A
B
C
Heres another possibility? The complex described
by this experimental result is also said to have
unknown stoichiometry.
29
30Spoke 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. 2002
20(10)991-7.
30
31Synthetic genetic interactions in yeast
31
32Network of the human interactome
Each point represents a protein and each line
between them is an interaction
32
33Network 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
34Yeast interactome project
34
35Interactome data analysis (1)
- Validation of interactomes 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
36Interactome 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
37Interactome 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
38Interactome 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
39Projects QA!
Biological pathway simulation
2. Computer-aided anti-cancer drug design
3. Disease-causing mutation on drug target
Any questions? Thank you!
39