Cited by 133Bioinformatics and Genomic Networksvaccines and immunoinformatics approachesinterferon and immune responses

A structure-informed atlas of human-virus interactions

Open access
Lasso, Gorka, Mayer, Sandra V., Winkelmann, Evandro R., Chu, Tim, Elliot, Oliver, Patino-Galindo, Juan Angel, Park, Kernyu, Rabadan, Raul +2 more·2019·Cell

Abstract

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 ∼282,000 pan viral-human PPIs with an experimental validation rate of ∼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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Crossref · 10.1016/j.cell.2019.08.005

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  • Viral-human PPI data were added from P-HIPSTer to help explore PPIs between viral pathogens and human proteins.

    “Given the COVID-19 pandemic, viral-human PPI data were added from P-HIPSTer (20) to help explore PPIs between viral pathogens and human proteins.”

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Research works printed but not linked: 1

  1. Frank E, Hall MA, and Witten IH (2016). The WEKA Workbench Online Appendix for “Data Mining: Practical Machine Learning Tools and Techniques”, Fourth edn (Morgan Kaufmann).

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Authors
Lasso, G., Mayer, S. V., Winkelmann, E. R., Chu, T., Elliot, O., Patino-Galindo, J. A., Park, K., Rabadan, R., Honig, B., & Shapira, S. D.
Affiliations
  • Columbia University Irving Medical Center (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Honig, Barry
  • Shapira, Sagi D.
Venue
Cell
Publisher
Elsevier BV
Published
2019-09
Volume
178
Issue
6
Pages
1526-1541.e16
ISSN
0092-8674 (ISSN-L)
OpenAlex
W2970491619
Cited by
133
References
151
Citations by year
2026: 11 · 2025: 10 · 2024: 12 · 2023: 15 · 2022: 16 · 2021: 40 · 2020: 27 · 2019: 2
FWCI
7.03
Type
journal article
Language
en
Open access
Locations
  • Cell (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institutes of Health
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
  • Life Sciences › Immunology and Microbiology › Immunology › interferon and immune responses
Keywords
host-virus interaction, protein-protein interaction, structural similarity, interactome prediction, Zika virus, ESR1, human papillomavirus, oncogenicity, human proteome
MeSH terms
Zika Virus, Animals, Atlases as Topic, Chlorocebus aethiops, Computer Simulation, Humans, Vero Cells, Viral Proteins, Proteome, Protein Interaction Mapping, Host-Pathogen Interactions, HEK293 Cells, MCF-7 Cells, Datasets as Topic

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