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Modelling proteomes An integrated computational framework for systems biology research

Modelling proteomes An integrated computational framework for systems biology research Ram Samudrala University of Washington. How does the genome of an organism specify its behaviour and characteristics?. Proteome – all proteins of a particular system. ~60,000 in human. ~60,000 in rice.

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Modelling proteomes An integrated computational framework for systems biology research

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  1. Modelling proteomes An integrated computational framework for systems biology research Ram Samudrala University of Washington How does the genome of an organism specify its behaviour and characteristics?

  2. Proteome – all proteins of a particular system ~60,000 in human ~60,000 in rice ~4500 in bacteria like Salmonella and E. coli Several thousand distinct sequence families

  3. Modelling proteomes – understand the structure of individual proteins A few thousand distinct structural folds

  4. Modelling proteomes – understand their individual functions Thousands of possible functions

  5. Modelling proteomes – understand their expression Different expression patterns based on time and location

  6. Modelling proteomes – understand their interactions Interactions and expression patterns are interdependent with structure and function

  7. CASP6 prediction (model1) for T0215 5.0 Å Cα RMSD for all 53 residues Ling-Hong Hung/Shing-Chung Ngan

  8. CASP6 prediction (model1) for T0281 4.3 Å Cα RMSD for all 70 residues Ling-Hong Hung/Shing-Chung Ngan

  9. CASP6 prediction (model1) for T0231 1.3 Å Cα RMSD for all 137 residues (80% ID) Tianyun Liu

  10. CASP6 prediction (model1) for T0271 2.4 Å Cα RMSD for all 142 residues (46% ID) Tianyun Liu

  11. Prediction of HIV-1 protease-inhibitor binding energies with MD Can predict resistance/susceptibility to six FDA approved inhibitors with 95% accuracy in conjunction with knowledge-based methods http://protinfo.compbio.washington.edu/pirspred/ Ekachai Jenwitheesuk

  12. Prediction of protein interaction networks Target proteome Interacting protein database 85% protein a protein A experimentally determined interaction predicted interaction protein B protein b 90% Assign confidence based on similarity and strength of interaction Key paradigm is the use of homology to transfer information across organisms; not limited to yeast, fly, and worm Consensus of interactions helps with confidence assignments Jason McDermott

  13. E. coli predicted protein interaction network Jason McDermott

  14. M. tuberculosis predicted protein interaction network Jason McDermott

  15. C. elegans predicted protein interaction network Jason McDermott

  16. H. sapiens predicted protein interaction network Jason McDermott

  17. Network-based annotation for C. elegans Jason McDermott

  18. Identifying key proteins on the anthrax predicted network Articulation point proteins Jason McDermott

  19. Identification of virulence factors Jason McDermott

  20. Bioverse – explore relationships among molecules and systems http://bioverse.compbio.washington.edu Jason McDermott/Michal Guerquin/Zach Frazier

  21. Bioverse – explore relationships among molecules and systems http://bioverse.compbio.washington.edu Jason McDermott/Michal Guerquin/Zach Frazier

  22. Bioverse – explore relationships among molecules and systems http://bioverse.compbio.washington.edu Jason McDermott/Michal Guerquin/Zach Frazier

  23. Bioverse – explore relationships among molecules and systems http://bioverse.compbio.washington.edu Jason McDermott/Michal Guerquin/Zach Frazier

  24. Bioverse - Integrator Aaron Chang

  25. Where is all this going? + + Computational biology Structural genomics Functional genomics Take home message Prediction of protein structure, function, and networks may be used to model whole genomes to understand organismal function and evolution

  26. Acknowledgements Aaron Chang Chuck Mader David Nickle Ekachai Jenwitheesuk Gong Cheng Jason McDermott Kai Wang Ling-Hong Hung Mike Inouye Michal Guerquin Stewart Moughon Shing-Chung Ngan Tianyun Liu Zach Frazier National Institutes of Health National Science Foundation Searle Scholars Program (Kinship Foundation) UW Advanced Technology Initiative in Infectious Diseases http://bioverse.compbio.washington.edu http://protinfo.compbio.washington.edu

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