PROTEIN INTERACTION NETWORK – INFERENCE TOOL DIVYA RAO CANDIDATE FOR MASTER OF SCIENCE IN BIOINFORMATICS ADVISOR: Dr. FILIPPO MENCZER CAPSTONE PROJECT.

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Presentation transcript:

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 Background PIN-IT Sample Results Future Work References Acknowledgements April 20, 2006 Slide 2 of 19

Definitions Proteins are complex, high- molecular weight organic compounds Protein interactions are associations between protein molecules Examples: enzymes, hormones, transcription factors, antibodies, structural proteins  Outline  Background  Definitions  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 3 of 19

Experimental Approaches Immunoprecipitation  Outline  Background  Experiments  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 4 of 19

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  Outline  Background  Experiments  PIN-IT  Results  Future Work  References  Acknowledgements A a Species 1 Species 2 April 20, 2006 Slide 5 of 19 a b B b Species 3

Yeast Two Hybrid Bait & prey Transcription: DNA -> RNA Two haploid yeasts Benefit: – yeast can express genes from almost any species Limitation: –Mutations – false positives – May not detect weak or rapid interactions  Outline  Background  Experiments  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 6 of 19

PRISM  Outline  Background  Other Tools  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 7 of 19

ADVICE  Background  Other Tools April 20, 2006 Slide 8 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  Outline  Background  Motivation  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 9 of 19

Protein Interaction Network Inference Tool Infer protein-protein interactions –Known protein interactions –Protein similarity  Outline  Background  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 10 of 19

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  Outline  Background  PIN-IT  Data Sources  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 11 of 19

 Outline  Background  PIN-IT  Data DIPBINDPIN-IT Number of proteins Number of Interactions Number of Organisms PIN-IT Data April 20, 2006 Slide 12 of 19

BLAST Basic Local Alignment Search Tool..AGTTAC.. I I I 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  Outline  Background  PIN-IT  BLAST  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 13 of 19

Calculating Inference A I B xy S D Where: r is the false positive rate E is the e-value from BLAST n is the size of the dataset April 20, 2006 Slide 14 of 19

Demo PIN-IT  Outline  Background  PIN-IT  Demo  Results  Future Work  References  Acknowledgments April 20, 2006 Slide 15 of 19

 Outline  Background  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 16 of 19 Results Interacts with mRNAs encoding membrane- associated proteins Putative integral membrane E3 ubiquitin ligase Putative integral membrane, negative regulation of amino acid uptake Has roles in maintenance of cell wall integrity

Future Work 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  Outline  Background  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 17 of 19

References Campbell, M. A., Heyer, L.A. Discovering Genomics, Proteomics & Bioinformatics. India: Pearson Education, 2004, pp Ito T, et al.: "A comprehensive two-hybrid analysis to explore the yeast protein interactome,". Proc Natl Acad Sci 2001, 98: Titz B, et al.: "What do we learn from high-throughput protein interaction data?". Expert Rev Proteomics 2004, 1: Giot L, et al.: "A protein interaction map of Drosophila melanogaster,". Science : 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): Tan, Soon-Heng, Zhang, Zhuo, Ng, See-Kiong ADVICE: Automated Detection and Validation of Interaction by Co- Evolution Nucl. Acids Res : W69-72 Protein Interactions by Structural Matching (PRISM): Automated Detection and Validation of Interaction by Co-Evolution (ADVICE): DIP: BIND: Immunoprecipitation Image: Yeast Two Hybrid system image:  Outline  Background  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 18 of 19

Acknowledgements Dr. Filippo Menczer Dr. Haixu Tang Dr. Alessandro Flammini Dr. Sun Kim Dr. Mehmet Dalkilic Dr. Gary Wiggins Linda Hostetter  Outline  Background  PIN-IT  Results  Future Work  References  Acknowledgements April 20, 2006 Slide 19 of 19

Query April 20, 2006

Query Results

Node Information

April 20, 2006 Query Results

Interaction Edge Information April 20, 2006

Query Results

Similarity Edge Information April 20, 2006

Query Results

Inference Edge Information April 20, 2006