1. PROTEIN-PROTEIN
INTERACTIONS
PRESENTED BY: Priyanka

2. INTRODUCTION
• The human genome has been called the
"blueprint of life," but it's really more of a
parts list.
• Cellular architecture is better defined by its
complexes, the molecular machines that
actually make a cell, a cell.
• Protein–protein interactions occur when two
or more proteins bind together, often to carry
out their biological function.

3. • The protein –protein interaction have commonly
been termed the ‘INTERACTOME’ by scientists.
• French researchers first coined the term
"interactome" in 1999; the first protein-protein
interactome data appeared in 2000.
• Today the field—like the 11-year-old it is—is
maturing rapidly. Interactome research has
racked up more than 560 publications, and
databases now house interactions numbering in
the hundreds of thousands.

4. WHY IS STUDY OF INTERACTOME
IMPORTANT?
• Proteins, like humans, are social animals. From
DNA replication to protein degradation, the
work of the cell is accomplished mostly by
macromolecular complexes—a fact that
researchers, awash in genome sequence data.

5. • Unlike biological pathways, which represent a
sequence of molecular interactions leading to a final
result — for example, a signalling cascade — networks
are interlinked.
• Represented as starbursts of protein 'nodes' linked by
interaction 'edges' to form intricate constellations, they
provide insight into the mechanisms of cell functions.
• Furthermore, placing proteins encoded by disease
genes into these networks will let researchers
determine the best candidates for assessing disease
risk and targeting with therapies.
• Therefore, finding interaction partners for a protein can
reveal its function. To that end, researchers are now
building entire networks of protein–protein
interactions.

6. • The human genome project effort identified 30,000
genes, but that is not the end goal. How the genes
work in pathways and how these pathways function in
disease states and development is the end goal. To
accomplish this it is necessary to systematically map
gene and protein interactions.
• Unlike the genome, the interactome — the set of
protein-to-protein interactions that occurs in a cell — is
dynamic. The interactome may be tougher to solve
than the genome, but the information, is crucial for a
complete understanding of biology.

7. CATEGORIES OF PIP
• STABLE: these are those interactions which are
associated with proteins that are purified as
multi- subunit complexes.
Ex. Haemoglobin, RNA polymerase.
• TRANSIENT: these are on/off temporary in nature
and typically requires a specific set of conditions
that promote the interaction.
These are expected to control majority of cellular
processes.

8. METHODS FOR DETECTING PIP
• There are two main approaches for detecting
interacting proteins:
1. IN VIVO METHODS:
• Yeast two hybrid system
2. IN VITRO METHODS:
• IMMUNOPRECIPITATION(IP)/ Co-IP

9. YEAST TWO HYBRID SYSTEM
• The most frequently used binary method is the
yeast two-hybrid (Y2H) system. It has variations
involving different reagents, and has been
adapted to high-throughput screening.
• The strategy interrogates two proteins, called
bait and prey, coupled to two halves of a
transcription factor and expressed in yeast.
• If the proteins make contact, they reconstitute a
transcription factor that activates a reporter
gene.

11. CO-IMMUNOPRECIPITATION (coIP)
• The most common co-complex method is coimmunoprecipitation (coIP) .
• Co-immunoprecipitation (co-IP) is a popular
technique for protein interaction discovery. Co-IP
is conducted in essentially the same manner as
an immunoprecipitation (IP) of a single protein,
except that the target protein precipitated by the
antibody, also called the "bait", is used to coprecipitate a binding partner/protein complex, or
"prey", from a lysate.

13. DATABASES
• Protein–protein interactions are only the raw material
for networks. To build a network, researchers typically
combine interaction data sets with other sources of
data. Primary databases that contain protein–protein
interactions include DIP (http://dip.doe-mbi.ucla.edu),
BioGRID, IntAct (http://www.ebi.ac.uk/intact) and
MINT (http://mint.bio.uniroma2.it).
• These databases have committed to making records
available through a common language called PSICQUIC,
to maximize access.

14. CONCLUSION
• The predictve power of the interactome model
allows us to examine the organization and
coordination of multiple complex cellular
processes and determine how they are organized
into pathways.
• The interactome model can be used to predict
poorly characterized proteins into their functional
context according to their interacting partners
within a module.
• One-to-many relationship can be used for
pathway discovery.

15. REFERENCES
•
•
•
•
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Principles of protein-protein interaction
Susan Jones and Janet M. Thornton
Biomolecular Structure and Modelling Unit,Department of Biochemistry and
Molecular Biology, University College, Gower Street, London WC1E 6BT, England
Proc. Natl. Acad. Sci. USA
Vol. 93, pp. 13-20, January 1996
Thermo Scientific Pierce Protein Interaction Technical Handbook volume 2
"Lethality and centrality in protein networks," Jeong H, Nature , 2001 Vol 411, 412"Evidence for dynamically organized modularity in the yeast interactome," Han JDJ, Nature , 2004
Protein interactions: is seeing believing?
Joel P. Mackay , Margaret Sunde, Jason A. Lowry, Merlin Crossley and Jacqueline M.
Matthews
School of Molecular and Microbial Biosciences, Building G08, University of Sydney, NSW
2006, Australia
Protein–protein interactions: Interactome under construction
Laura Bonetta Nature 468, 851–854 (09 December 2010) doi:10.1038/468851a
Published online 08 December 2010

16. •
Interactome Networks and Human Disease
Marc Vidal,1,2,* Michael E. Cusick,1,2 and Albert-La´ szlo´ Baraba´ si1,3,4,*
1. Center for Cancer Systems Biology (CCSB) and Department of Cancer
Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
2. Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
3. Center for Complex Network Research (CCNR) and Departments of
Physics, Biology and Computer Science, Northeastern University,
Boston, MA 02115, USA
4. Department of Medicine, Brigham and Women’s Hospital, Harvard Medical
School, Boston, MA 02115, USA
*Correspondence: marc_vidal@dfci.harvard.edu (M.V.), alb@neu.edu (A.-L.B.)
DOI 10.1016/j.cell.2011.02.016
• Boone, C., Bussey, H., and Andrews, B.J. (2007). Exploring genetic interactions
and networks with yeast. Nat. Rev. Genet. 8, 437–449.
• On the structure of protein–protein interaction Networks A. Thomas, R.
Cannings, N.A.M. Monk, and C. Cannings. Biochemical Society Transactions (2003)
Volume 31, part 6.