1. MODELLING INTERACTOMES
RAM SAMUDRALA
ASSOCIATE PROFESSOR
UNIVERSITY OF WASHINGTON
How does the genome of an organism specify
its behaviour and characteristics?

2. STRUCTURE Liu/Hong-Hung/Ngan
0.5 Å Cα RMSD for 173 residues (60% identity)
T0290 – peptidyl-prolyl isomerase from H. sapiens
T0288 – PRKCA-binding from H. sapiens
2.2 Å Cα RMSD for 93 residues (25% identity)
T0332 – methyltransferase from H. sapiens
2.0 Å Cα RMSD for 159 residues (23% identity)
T0364 – hypothetical from P. putida
5.3 Å Cα RMSD for 153 residues (11% identity)
Liu/Hong-Hung/Ngan

3. FUNCTION Wang/Cheng Ion binding energy prediction with a
correlation of 0.7
Calcium ions predicted
to < 0.05 Å RMSD
in 130 cases
Meta-functional signature
accuracy
Meta-functional signature for DXS model from M. tuberculosis
Wang/Cheng

4. INTERACTION
Transcription factor bound to DNA promoter regulog model from S. cerevisiae
Prediction of binding energies of HIV protease mutants and inhibitors using docking with dynamics
BtubA/BtubB interolog model from P. dejongeii
(35% identity to eukaryotic tubulins)
McDermott/Wichadakul/Staley/Horst/Manocheewa/Jenwitheesuk/Bernard

5. SYSTEMS McDermott/Wichadakul
Example predicted protein interaction network from M. tuberculosis
(107 proteins with 762 unique interactions)
Proteins PPIs TRIs
H. sapiens 26, , ,807 1,045,622
S. cerevisiae , , , ,456
O.sativa (6) , , , ,990
E. coli , , ,619
In sum, we can predict functions for more than 50% of a proteome, approximately ten million protein-protein and protein-DNA interactions with an expected accuracy of 50%
McDermott/Wichadakul

6. SYSTEMS McDermott/Wichadakul
Combining protein-protein and protein-DNA interaction networks to determine regulatory circuits
McDermott/Wichadakul

7. INFRASTRUCTURE http://bioverse.compbio.washington.edu
~500,000 molecules over 50+proteomes served using a 1.2 TB PostgreSQL database and a sophisticated AJAX webapplication and XML-RPC API
Guerquin/Frazier

8. INFRASTRUCTURE
Guerquin/Frazier

9. INFRASTRUCTURE http://bioverse.compbio.washington.edu/integrator
Chang/Rashid

10. APPLICATION: DRUG DISCOVERY
HSV
CMV
KHSV
Jenwitheesuk

11. APPLICATION: DRUG DISCOVERY
Computionally predicted broad spectrum human herpesvirus protease inhibitors is effective in vitro
against members from all three classes and is comparable or better than anti-herpes drugs
HSV
KHSV
CMV
Our protease inhibitor acts synergistically with acylovir (a nucleoside analogue that inhibits replication)
and it is less likely to lead to resistant strains compared to acylovir
HSV
Lagunoff

12. APPLICATION: NANOTECHNOLOGY
Oren/Sarikaya/Tamerler

13. MODELLING PROTEIN AND PROTEOME STRUCTURE FUNCTION AT
FUTURE
Structural
genomics
Functional
genomics +
Computational
biology +
MODELLING PROTEIN AND PROTEOME STRUCTURE FUNCTION AT
THE ATOMIC LEVEL IS NECESSARY TO UNDERSTAND THE RELATIONSHIPS BETWEEN SINGLE MOLECULES, SYSTEMS, PATHWAYS, CELLS, AND ORGANISMS

14. Current group members: Past group members:
ACKNOWLEDGEMENTS
Baishali Chanda
Brady Bernard
Chuck Mader
David Nickle
Ersin Emre Oren
Ekachai Jenwitheesuk
Gong Cheng
Imran Rashid
Jason McDermott
Jeremy Horst
Ling-Hong Hung
Michal Guerquin
Rob Brasier
Rosalia Tungaraza
Shing-Chung Ngan
Siriphan Manocheewa
Somsak Phattarasukol
Stewart Moughon
Tianyun Liu
Weerayuth Kittichotirat
Zach Frazier
Kristina Montgomery, Program Manager
Current group members:
Aaron Chang
Duncan Milburn
Kai Wang
Marissa LaMadrid
Past group members:
James Staley
Mehmet Sarikaya/Candan Tamerler
Michael Lagunoff
Roger Bumgarner
Wesley Van Voorhis
Collaborators:
Funding agencies:
National Institutes of Health
National Science Foundation
Searle Scholars Program
Puget Sound Partners in Global Health
UW Advanced Technology Initiative
Washington Research Foundation
UW TGIF