1. University of Washington
Modelling proteomes
Ram Samudrala
University of Washington

2. { } What is a “proteome”? What does it mean to “model a proteome”?
All proteins of a particular system
(organelle, cell, organism)
What does it mean to “model a proteome”?
For any protein, we wish to:
ANNOTATION {
figure out what it looks like (structure or form)
understand what it does (function)
Repeat for all proteins in a system
EXPRESSION +
INTERACTION }
Understand the relationships between all of them

3. + + Computational aspects of functional genomics
structure based methods
microenvironment analysis
zinc binding site?
structure comparison
homology function? *
Bioverse
assign function to
entire protein space
sequence based methods
sequence comparison
motif searches
phylogenetic profiles
domain fusion analyses +
experimental data
single molecule + genomic/proteomic +

4. Bioverse – explore relationships among molecules and systems
Jason McDermott

5. Bioverse – explore relationships among molecules and systems
Jason Mcdermott

6. Bioverse – prediction of protein interaction networks
Target proteome
protein A
85%
predicted
interaction
protein B
90%
Interacting protein database
protein α
protein β
experimentally
determined
interaction
Assign confidence based on similarity and strength of interaction
Jason Mcdermott

7. Bioverse – E. coli predicted protein interaction network
Jason McDermott

8. Bioverse – M. tuberculosis predicted protein interaction network
Jason McDermott

9. Bioverse – C. elegans predicted protein interaction network
Jason McDermott

10. Bioverse – H. sapiens predicted protein interaction network
Jason McDermott

11. Bioverse – organisation of the interaction networks
Ci = 2n/ki(ki-1)
Jason McDermott

12. Bioverse – mapping pathways on the rice predicted network
Defense-related proteins
Jason McDermott

13. Bioverse – mapping pathways on the rice predicted network
Tryptophan biosynthesis
Jason McDermott

14. Bioverse – network-based annotation for C. elegans
Jason McDermott

15. Bioverse – viewer
Aaron Chang

16. Take home message Acknowledgements
Prediction of protein structure and function can
be used to model whole genomes to understand
organismal function and evolution
Acknowledgements
Aaron Chang
Ashley Lam
Ekachai Jenwitheesuk
Gong Cheng
Jason McDermott
Kai Wang
Ling-Hong Hung
Lynne Townsend
Marissa LaMadrid
Mike Inouye
Stewart Moughon
Shing-Chung Ngan
Yi-Ling Cheng
Zach Frazier