Journal
CELL
Volume 178, Issue 6, Pages 1526-+Publisher
CELL PRESS
DOI: 10.1016/j.cell.2019.08.005
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Funding
- NIH [5R01GM109018-05, 5U54CA209997-03, 5R01GM030518-38, 5R01GM117591, S10OD012351, S10OD021764]
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While knowledge of protein-protein interactions (PPIs) is critical for understanding virus-host relationships, limitations on the scalability of high-throughput methods have hampered their identification beyond a number of well-studied viruses. Here, we implement an in silico computational framework (pathogen host interactome prediction using structure similarity [P-HIPSTer]) that employs structural information to predict similar to 282,000 pan viral-human PPIs with an experimental validation rate of similar to 76%. In addition to rediscovering known biology, P-HIPSTer has yielded a series of new findings: the discovery of shared and unique machinery employed across human-infecting viruses, a likely role for ZIKV-ESR1 interactions in modulating viral replication, the identification of PPIs that discriminate between human papilloma viruses (HPVs) with high and low oncogenic potential, and a structure-enabled history of evolutionary selective pressure imposed on the human proteome. Further, P-HIPSTer enables discovery of previously unappreciated cellular circuits that act on human-infecting viruses and provides insight into experimentally intractable viruses.
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