Evidence map›Paper›PMID 34234921›Full record

ArticleComputational and structural biotechnology journal2021

Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses.

Christopher A Beaudoin, Arian R Jamasb, Ali F Alsulami, Liviu Copoiu, Andries J van Tonder, Sharif Hala, Bridget P Bannerman, Sherine E Thomas, Sundeep Chaitanya Vedithi, Pedro H M Torres and 1 more

Open access · goldAbstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
2.2field-weighted citation impact, top 10% of its field
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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 38 citations in OpenAlex.

  1. Pooled it
  2. SARS-CoV-2 cell entry beyond the ACE2 receptor.Molecular biology reports · 2022
    Pooled it
  3. Article
  4. Review
  5. Review
  6. Structural proteins of human coronaviruses: what makes them different?Frontiers in cellular and infection microbiology · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. [Antiphospholipid autoantibodies and Covid-19].Revue francophone des laboratoires : RFL · 2022
    Article
  15. Article
  16. Article
  17. Review
  18. Are There Hidden Genes in DNA/RNA Vaccines?Frontiers in immunology · 2022
    Article
  19. Can the SARS-CoV-2 Spike Protein Bind Integrins Independent of the RGD Sequence?Frontiers in cellular and infection microbiology · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 3 countries.

Christopher A BeaudoinDepartment of Biochemistry, Sanger Building, University of Cambridge, Tennis Court Rd, Cambridge CB2 1GA, United Kingdom.
Arian R JamasbDepartment of Biochemistry, Sanger Building, University of Cambridge, Tennis Court Rd, Cambridge CB2 1GA, United Kingdom.
Ali F AlsulamiDepartment of Biochemistry, Sanger Building, University of Cambridge, Tennis Court Rd, Cambridge CB2 1GA, United Kingdom.
Liviu CopoiuDepartment of Biochemistry, Sanger Building, University of Cambridge, Tennis Court Rd, Cambridge CB2 1GA, United Kingdom.
Andries J van TonderDepartment of Veterinary Medicine, University of Cambridge, Madingley Rd, Cambridge CB3 0ES, United Kingdom.
Sharif HalaKing Abdullah International Medical Research Centre - Ministry of National Guard Health Affairs, Jeddah, Saudi Arabia.
Bridget P BannermanDepartment of Biochemistry, Sanger Building, University of Cambridge, Tennis Court Rd, Cambridge CB2 1GA, United Kingdom.
Sherine E ThomasDepartment of Biochemistry, Sanger Building, University of Cambridge, Tennis Court Rd, Cambridge CB2 1GA, United Kingdom.
Sundeep Chaitanya VedithiDepartment of Biochemistry, Sanger Building, University of Cambridge, Tennis Court Rd, Cambridge CB2 1GA, United Kingdom.
Pedro H M TorresLaboratório de Modelagem e Dinâmica Molecular, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
Tom L BlundellDepartment of Biochemistry, Sanger Building, University of Cambridge, Tennis Court Rd, Cambridge CB2 1GA, United Kingdom.
University of Cambridge · GBKing Saud bin Abdulaziz University for Health Sciences · SAUniversidade Federal do Rio de Janeiro · BR

Funding

Wellcome Trust
6 · The paper itself

Abstract

Viruses often encode proteins that mimic host proteins in order to facilitate infection. Little work has been done to understand the potential mimicry of the SARS-CoV-2, SARS-CoV, and MERS-CoV spike proteins, particularly the receptor-binding motifs, which could be important in determining tropism and druggability of the virus. Peptide and epitope motifs have been detected on coronavirus spike proteins using sequence homology approaches; however, comparing the three-dimensional shape of the protein has been shown as more informative in predicting mimicry than sequence-based comparisons. Here, we use structural bioinformatics software to characterize potential mimicry of the three coronavirus spike protein receptor-binding motifs. We utilize sequence-independent alignment tools to compare structurally known protein models with the receptor-binding motifs and verify potential mimicked interactions with protein docking simulations. Both human and non-human proteins were returned for all three receptor-binding motifs. For example, all three were similar to several proteins containing EGF-like domains: some of which are endogenous to humans, such as thrombomodulin, and others exogenous, such as

Indexed as

Coronavirus spike proteinCOVID-19Infectious diseaseMERS-CoVSARS-CoVSARS-CoV-2Structural bioinformaticsViral host mimicry

Identifiers

PMID34234921
PMCPMC8249111
OpenAlexW3174761936

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.