PROTEIN-PROTEIN
INTERACTIONS
PRESENTED BY: Priyanka
INTRODUCTION
• The human genome has been called the
"blueprint of life," but it's really more of a
parts list.
• Cellular ...
• The protein –protein interaction have commonly
been termed the ‘INTERACTOME’ by scientists.
• French researchers first c...
WHY IS STUDY OF INTERACTOME
IMPORTANT?
• Proteins, like humans, are social animals. From
DNA replication to protein degrad...
• Unlike biological pathways, which represent a
sequence of molecular interactions leading to a final
result — for example...
• The human genome project effort identified 30,000
genes, but that is not the end goal. How the genes
work in pathways an...
CATEGORIES OF PIP
• STABLE: these are those interactions which are
associated with proteins that are purified as
multi- su...
METHODS FOR DETECTING PIP
• There are two main approaches for detecting
interacting proteins:
1. IN VIVO METHODS:
• Yeast ...
YEAST TWO HYBRID SYSTEM
• The most frequently used binary method is the
yeast two-hybrid (Y2H) system. It has variations
i...
CO-IMMUNOPRECIPITATION (coIP)
• The most common co-complex method is coimmunoprecipitation (coIP) .
• Co-immunoprecipitati...
DATABASES
• Protein–protein interactions are only the raw material
for networks. To build a network, researchers typically...
CONCLUSION
• The predictve power of the interactome model
allows us to examine the organization and
coordination of multip...
REFERENCES
•

•
•
•

•

Principles of protein-protein interaction
Susan Jones and Janet M. Thornton
Biomolecular Structure...
•

Interactome Networks and Human Disease
Marc Vidal,1,2,* Michael E. Cusick,1,2 and Albert-La´ szlo´ Baraba´ si1,3,4,*
1....
Protein protein interactions
Protein protein interactions
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Protein protein interactions

  1. 1. PROTEIN-PROTEIN INTERACTIONS PRESENTED BY: Priyanka
  2. 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. 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. 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. 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. 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. 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. 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. 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.
  10. 10. 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.
  11. 11. 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.
  12. 12. 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.
  13. 13. REFERENCES • • • • • 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
  14. 14. • 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.
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