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MODELLING INTERACTOMES
RAM SAMUDRALA ASSOCIATE PROFESSOR UNIVERSITY OF WASHINGTON How does the genome of an organism specify its behaviour and characteristics?
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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
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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
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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
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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
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SYSTEMS McDermott/Wichadakul
Combining protein-protein and protein-DNA interaction networks to determine regulatory circuits McDermott/Wichadakul
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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
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INFRASTRUCTURE Guerquin/Frazier
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INFRASTRUCTURE http://bioverse.compbio.washington.edu/integrator
Chang/Rashid
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APPLICATION: DRUG DISCOVERY
HSV CMV KHSV Jenwitheesuk
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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
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APPLICATION: NANOTECHNOLOGY
Oren/Sarikaya/Tamerler
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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
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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
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