Evidence map›Paper›PMID 34253909›Full record

ArticleNature chemical biology2021

Mechanical strength of RNA knot in Zika virus protects against cellular defenses.

Meng Zhao, Michael T Woodside

Abstract read
PubMed Publisher
In one paragraph

Article in Nature chemical biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.5field-weighted citation impact, top 6% 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

32 citing papers in PubMed, 56 citations in OpenAlex.

  1. Article
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  9. Identifying the interactions conferring functional mechanical rigidity on RNase-resistant RNA from Zika virus.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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  13. Review
  14. Phosphorescent metallaknots of Au(I)-bis(acetylide) strands directed by Cu(I) π-coordination.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  15. Review
  16. Review
  17. Article
  18. A Genetic Circuit Design for Targeted Viral RNA Degradation.Bioengineering (Basel, Switzerland) · 2023
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  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Meng ZhaoDepartment of Physics, University of Alberta, Edmonton, Alberta, Canada.ORCID http://orcid.org/0000-0003-2573-6922
Michael T WoodsideDepartment of Physics, University of Alberta, Edmonton, Alberta, Canada. michael.woodside@ualberta.ca.ORCID http://orcid.org/0000-0003-4695-0397
University of Alberta · CA

Funding

CIHR MOP-142449
6 · The paper itself

Abstract

Unusual knot-like structures recently discovered in viral exoribonuclease-resistant RNAs (xrRNAs) prevent digestion by host RNases to create subgenomic RNAs enhancing infection and pathogenicity. xrRNAs are proposed to prevent digestion through mechanical resistance to unfolding. However, their unfolding force has not been measured, and the factors determining RNase resistance are unclear. Furthermore, how these knots fold remains unknown. Unfolding a Zika virus xrRNA with optical tweezers revealed that it was the most mechanically stable RNA yet observed. The knot formed by threading the 5' end into a three-helix junction before pseudoknot interactions closed a ring around it. The pseudoknot and tertiary contacts stabilizing the threaded 5' end were both required to generate extreme force resistance, whereas removing a 5'-end contact produced a low-force knot lacking RNase resistance. These results indicate mechanical resistance plays a central functional role, with the fraction of molecules forming extremely high-force knots determining the RNase resistance level.

Indexed as

RNA, ViralStress, MechanicalZika VirusRNA, Viral

Identifiers

PMID34253909
OpenAlexW3181057038

What OpenQuestion holds

Textmetadata
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.