4.8 Article

A 3D structural SARS-CoV-2-human interactome to explore genetic and drug perturbations

Journal

NATURE METHODS
Volume 18, Issue 12, Pages 1477-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41592-021-01318-w

Keywords

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Funding

  1. National Institute of General Medical Sciences [R01 GM124559, R01 GM125639]
  2. National Institute of Diabetes and Digestive and Kidney Diseases [R01 DK115398]
  3. Eunice Kennedy Shriver National Institute of Child Health and Human Development [R01 HD082568]
  4. National Human Genome Research Institute [UM1 HG009393]
  5. NSF [DBI-1661380]
  6. Simons Foundation Autism Research Initiative [575547]
  7. Cornell Rapid Research Response to SARS-CoV-2 Seed Grant
  8. National Institutes of Health [R01AI35270]
  9. William Strong COVID-19 Biobank

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The emergence of new viral agents is driven by evolution of interactions between viral proteins and host targets, leading to increased infectivity of viruses such as SARS-CoV-2 through rapid evolution. State-of-the-art interface prediction and molecular docking were used to construct a three-dimensional structural interactome between SARS-CoV-2 and human, facilitating the study of how pathogen-host interactions impact transmission and virulence. The resource provided aims to aid in the development and testing of informed hypotheses for understanding the etiology and treatments of SARS-CoV-2.
Emergence of new viral agents is driven by evolution of interactions between viral proteins and host targets. For instance, increased infectivity of SARS-CoV-2 compared to SARS-CoV-1 arose in part through rapid evolution along the interface between the spike protein and its human receptor ACE2, leading to increased binding affinity. To facilitate broader exploration of how pathogen-host interactions might impact transmission and virulence in the ongoing COVID-19 pandemic, we performed state-of-the-art interface prediction followed by molecular docking to construct a three-dimensional structural interactome between SARS-CoV-2 and human. We additionally carried out downstream meta-analyses to investigate enrichment of sequence divergence between SARS-CoV-1 and SARS-CoV-2 or human population variants along viral-human protein-interaction interfaces, predict changes in binding affinity by these mutations/variants and further prioritize drug repurposing candidates predicted to competitively bind human targets. We believe this resource (http://3D-SARS2.yulab.org) will aid in development and testing of informed hypotheses for SARS-CoV-2 etiology and treatments.

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