Transcript Slide 1

PROTEIN INTERACTION
NETWORK – INFERENCE TOOL
DIVYA RAO
CANDIDATE FOR MASTER OF SCIENCE IN
BIOINFORMATICS
ADVISOR: Dr. FILIPPO MENCZER
CAPSTONE PROJECT PRESENTATION
SCHOOL OF INFORMATICS - INDIANA UNIVERSITY
April 20, 2006
 Outline
Outline
 Background
 PIN-IT
 Sample Results
 Future Work
 References
 Acknowledgements
Slide 2 of 19
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Background
PIN-IT
Sample Results
Future Work
References
Acknowledgements
April 20, 2006
 Outline
 Background
 Definitions
 PIN-IT
 Results
 Future Work
 References
 Acknowledgements
Slide 3 of 19
Definitions
• Proteins are complex, highmolecular weight organic
compounds
• Protein interactions are
associations between protein
molecules
• Examples: enzymes, hormones,
transcription factors, antibodies,
structural proteins
April 20, 2006
 Outline
 Background
Experimental Approaches
Experiments
 PIN-IT
 Results
• Immunoprecipitation
 Future Work
 References
 Acknowledgements
http://www.molecularstation.com/protein/immunoprecipitation/
Slide 4 of 19
April 20, 2006
 Outline
 Background
Experiments
 PIN-IT
 Results
 Future Work
 References
 Acknowledgements
High Throughput
Experiments
• DNA sequence analysis
– Homology & Orthology
– Limited to proteins encoded by a
single gene in one species or two
or more genes in another
a
A
b
B
Species 2
a
Species 1
Slide 5 of 19
b
Species 3
April 20, 2006
Yeast Two
Hybrid
 Outline
 Background
Experiments
• Bait & prey
• Transcription:
DNA -> RNA
• Two haploid
yeasts
• Benefit:
 PIN-IT
 Results
 Future Work
 References
 Acknowledgements
– yeast can
express
genes from
almost any
species
• Limitation:
– Mutations –
false positives
– May not
detect weak
or rapid
interactions
Slide 6 of 19
http://www.biochem.arizona.edu/classes/bioc568/bioc568.htm
April 20, 2006
 Background
Other Tools
 PIN-IT
 Results
 Future Work
 References
 Acknowledgements
Slide 7 of 19
PRISM
http://gordion.hpc.eng.ku.edu.tr/prism/tutorial.php#predictions.php
 Outline
April 20, 2006
 Background
ADVICE
Other Tools
Slide 8 of 19
http://advice.i2r.a-star.edu.sg/doc/flowchart.gif
April 20, 2006
 Outline
 Background
Motivation
 PIN-IT
 Results
 Future Work
 References
 Acknowledgements
Slide 9 of 19
Motivation
• Interaction maps can be used
to reveal drug targets
– BCL6 in humans causes B-cell
non-Hodgkin lymphoma. In the
fruitfly the BCL6 ortholog binds
calcineurin phosphatases
– Hubs vs. peripheral proteins
April 20, 2006
 Outline
 Background
 PIN-IT
 Results
 Future Work
 References
 Acknowledgements
Slide 10 of 19
Protein Interaction
Network Inference Tool
• Infer protein-protein interactions
– Known protein interactions
– Protein similarity
April 20, 2006
 Outline
 Background
 PIN-IT
Data Sources
 Results
 Future Work
 References
 Acknowledgements
PIN-IT Data sources
• Database of Interacting Proteins (DIP)
• Biomolecular Interaction Network
Database (BIND)
• Proteins with GI numbers, Taxon ID &
experimental source
• False positive rate
– Immunoprecipitation, r = 0.1
– Yeast Two Hybrid, r = 0.6
Slide 11 of 19
April 20, 2006
PIN-IT Data
 Outline
 Background
 PIN-IT
 Data
Number of
proteins
Number of
Interactions
Number of
Organisms
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DIP
BIND
PIN-IT
18826
27809
43573
54172
44354
94659
109
1020
1033
April 20, 2006
 Outline
 Background
 PIN-IT
BLAST
 Results
 Future Work
 References
 Acknowledgements
BLAST
• Basic Local Alignment Search Tool
..AGTTAC..
I II I
..ACTTAG..
• Smith-Waterman algorithm
• E-value
– # of different alignments with scores
equivalent to or better than S that are
expected to occur in a database by chance
• Orthologus proteins
• BLASTP
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April 20, 2006
Calculating Inference
I
B
A
S
y
D
x
I ( A, B )  1   rexp( A, B )
Where:
S ( A , x )  E( A , x )  n
r is the false positive rate
D( x , y )  S ( A, x )  I ( A, B )  S ( B , y )
E is the e-value from BLAST
n is the size of the dataset
suggest( a  , b  )  arg m ax D( a ,b )
( a ,b )
Slide 14 of 19
April 20, 2006
 Outline
 Background
Demo
 PIN-IT
Demo
 Results
• PIN-IT
 Future Work
 References
 Acknowledgments
Slide 15 of 19
April 20, 2006
Results
 Outline
 Background
 PIN-IT
 Results
 Future Work
Putative integral
membrane E3 ubiquitin
ligase
Interacts with mRNAs
encoding membraneassociated proteins
 References
 Acknowledgements
Slide 16 of 19
6324320
6322550
6321260
6323766
Has roles in maintenance
of cell wall integrity
Putative integral
membrane, negative
regulation of amino acid
uptake
April 20, 2006
 Outline
 Background
Future Work
 PIN-IT
 Results
 Future Work
 References
 Acknowledgements
Slide 17 of 19
• Allow for the user to upload
their protein sequences and
interactions
• Better estimation of
experimental false positive rates
• Work with biologists to validate
the tool and fine-tune the
parameters
April 20, 2006
References
 Outline
 Background
 PIN-IT
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 Results
 Future Work
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 References
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 Acknowledgements
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Slide 18 of 19
Campbell, M. A., Heyer, L.A. Discovering Genomics, Proteomics &
Bioinformatics. India: Pearson Education, 2004, pp176-183.
Ito T, et al.: "A comprehensive two-hybrid analysis to explore the yeast
protein interactome,".
Proc Natl Acad Sci 2001, 98:4569-74.
Titz B, et al.: "What do we learn from high-throughput protein interaction
data?".
Expert Rev Proteomics 2004, 1:111-21.
Giot L, et al.: "A protein interaction map of Drosophila melanogaster,".
Science 2003 302: 1727-1736
Aytuna,A.S, Gursoy,A. Keskin,O., (2005). Prediction of protein-protein
interactions by combining structure and sequence conservation in protein
interfaces. Bioinformatics 21(12):2850-2855
Tan, Soon-Heng, Zhang, Zhuo, Ng, See-Kiong
ADVICE: Automated Detection and Validation of Interaction by CoEvolution
Nucl. Acids Res. 2004 32: W69-72
Protein Interactions by Structural Matching (PRISM):
http://gordion.hpc.eng.ku.edu.tr/prism/index.php
Automated Detection and Validation of Interaction by Co-Evolution
(ADVICE): http://advice.i2r.a-star.edu.sg/
DIP: http://dip.doe-mbi.ucla.edu/
BIND: http://www.bind.ca/Action
Immunoprecipitation Image:
http://www.molecularstation.com/protein/immunoprecipitation/
Yeast Two Hybrid system image:
http://www.biochem.arizona.edu/classes/bioc568/bioc568.htm
April 20, 2006
 Outline
Acknowledgements
 Background
 PIN-IT
 Results
 Future Work
 References
 Acknowledgements
Slide 19 of 19
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Dr. Filippo Menczer
Dr. Haixu Tang
Dr. Alessandro Flammini
Dr. Sun Kim
Dr. Mehmet Dalkilic
Dr. Gary Wiggins
Linda Hostetter
April 20, 2006
Query
April 20, 2006
Query Results
April 20, 2006
Node Information
Query Results
April 20, 2006
Interaction Edge Information
April 20, 2006
Query Results
April 20, 2006
Similarity Edge Information
April 20, 2006
Query Results
April 20, 2006
Inference Edge Information
April 20, 2006