A Structure-Informed Atlas of Human-Virus Interactions

Cell. 2019 Sep 5;178(6):1526-1541.e16. doi: 10.1016/j.cell.2019.08.005. Epub 2019 Aug 29.


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.

Keywords: evolution; immunology; protein structure; protein-protein interactions; systems biology; virology.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Atlases as Topic
  • Chlorocebus aethiops
  • Computer Simulation
  • Datasets as Topic
  • HEK293 Cells
  • Host-Pathogen Interactions*
  • Humans
  • MCF-7 Cells
  • Protein Interaction Mapping*
  • Proteome / chemistry
  • Proteome / metabolism*
  • Vero Cells
  • Viral Proteins / chemistry
  • Viral Proteins / metabolism*
  • Zika Virus / physiology*


  • Proteome
  • Viral Proteins