Evidence map›Paper›PMID 32218151›Full record

ArticleViruses2020

Structural Genomics of SARS-CoV-2 Indicates Evolutionary Conserved Functional Regions of Viral Proteins.

Suhas Srinivasan, Hongzhu Cui, Ziyang Gao, Ming Liu, Senbao Lu, Winnie Mkandawire, Oleksandr Narykov, Mo Sun, Dmitry Korkin

Abstract read
In one paragraph

Article in Viruses, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 143 papers.

0numbers the graph read from it
0cells of the map it votes in
143citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

143 citing papers in PubMed.

  1. Real-time spatiotemporal tracking of infectious outbreaks in confined environments with a host-pathogen agent-based system.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. bioRxiv : the preprint server for biology · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Zebrafish (International journal of molecular sciences · 2024
    Review
  9. Article
  10. Local genetic adaptation to habitat in wild chimpanzees.bioRxiv : the preprint server for biology · 2024
    Article
  11. Review
  12. Tracking the COVID-19 vaccines: The global landscape.Human vaccines & immunotherapeutics · 2023
    Review
  13. Article
  14. SARS-CoV-2 Mac1 is required for IFN antagonism and efficient virus replication in cell culture and in mice.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  15. Article
  16. Article
  17. Article
  18. Perturbation of the host cell CaCell death & disease · 2023
    Article
  19. Article
  20. Review

83 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Suhas SrinivasanData Science Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Hongzhu CuiBioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Ziyang GaoBioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Ming LiuBioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Senbao LuBioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Winnie MkandawireBioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Oleksandr NarykovComputer Science Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Mo SunBioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Dmitry KorkinData Science Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.

Funding

Functional characterization of genetic and post-transcriptional variation using machine learning methodsR21LM012772 · NLM · WORCESTER POLYTECHNIC INSTITUTE · PI KORKIN, DMITRY · 2018 to 2019
$353k
National Science Foundation 1458267NLM NIH HHS R21 LM012772U.S. National Library of Medicine LM012772-01A1
6 · The paper itself

Abstract

During its first two and a half months, the recently emerged 2019 novel coronavirus, SARS-CoV-2, has already infected over one-hundred thousand people worldwide and has taken more than four thousand lives. However, the swiftly spreading virus also caused an unprecedentedly rapid response from the research community facing the unknown health challenge of potentially enormous proportions. Unfortunately, the experimental research to understand the molecular mechanisms behind the viral infection and to design a vaccine or antivirals is costly and takes months to develop. To expedite the advancement of our knowledge, we leveraged data about the related coronaviruses that is readily available in public databases and integrated these data into a single computational pipeline. As a result, we provide comprehensive structural genomics and interactomics roadmaps of SARS-CoV-2 and use this information to infer the possible functional differences and similarities with the related SARS coronavirus. All data are made publicly available to the research community.

Indexed as

AnimalsBetacoronavirusBinding SitesBiological EvolutionChiropteraComputational BiologyConserved SequenceCoronavirus InfectionsCoronavirus Nucleocapsid ProteinsCOVID-19Genome, ViralGenomicsHumansLigandsModels, MolecularNucleocapsid ProteinsCoronavirus Nucleocapsid ProteinsLigandsnucleocapsid phosphoprotein, SARS-CoV-2Nucleocapsid ProteinsPhosphoproteinsSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Viral Envelope ProteinsViral Matrix ProteinsViral Proteins2019-nCoV2019 novel coronavirusCOVID-19interactomeprotein-protein interactionsSARS-CoV-2structural genomics

Identifiers

PMID32218151
PMCPMC7232164

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.