1. Modelling, comparison, and analysis of proteomes Ram Samudrala University of Washington

2. What is 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: - figure out what it looks like (structure or form) - understand what it does (function) Repeat for all proteins in a system Understand the relationships between all of them ANNOTATION { EXPRESSION + INTERACTION }

3. Pragmatic reasons: - rational drug design and treatment of disease - protein and genetic engineering - build networks to model cellular pathways - study organismal function and evolution ? Why should we model proteomes? Intellectual challenge: Because it’s there!

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

5. Bioverse – explore relationships among molecules and systems Jason McDermott http://bioverse.compbio.washington.edu

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

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

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

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

10. Bioverse – V. cholerae predicted protein interaction network Jason McDermott

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

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

13. Bioverse – organisation of the interaction networks Jason McDermott C i = 2n/k i (k i -1)

14. Bioverse – viewer Aaron Chang

15. Take home message 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