Evidence map›Paper›PMID 36854032›Full record

ArticlePLoS computational biology2023

Shapify: Paths to SARS-CoV-2 frameshifting pseudoknot.

Luke Trinity, Ian Wark, Lance Lansing, Hosna Jabbari, Ulrike Stege

Open access · goldFull text read
In one paragraph

Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Luke TrinityDepartment of Computer Science, University of Victoria, Victoria, British Columbia, Canada.ORCID 0000-0002-1578-7964
Ian WarkDepartment of Computing Science, University of Alberta, Edmonton, Alberta, Canada.
Lance LansingDepartment of Computer Science, University of Victoria, Victoria, British Columbia, Canada.
Hosna JabbariDepartment of Computer Science, University of Victoria, Victoria, British Columbia, Canada.ORCID 0000-0002-7155-2297
Ulrike StegeDepartment of Computer Science, University of Victoria, Victoria, British Columbia, Canada.ORCID 0000-0001-9466-7196
University of Victoria · CAUniversity of Alberta · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple coronaviruses including MERS-CoV causing Middle East Respiratory Syndrome, SARS-CoV causing SARS, and SARS-CoV-2 causing COVID-19, use a mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to replicate. SARS-CoV-2 possesses a unique RNA pseudoknotted structure that stimulates -1 PRF. Targeting -1 PRF in SARS-CoV-2 to impair viral replication can improve patients' prognoses. Crucial to developing these therapies is understanding the structure of the SARS-CoV-2 -1 PRF pseudoknot. Our goal is to expand knowledge of -1 PRF structural conformations. Following a structural alignment approach, we identify similarities in -1 PRF pseudoknots of SARS-CoV-2, SARS-CoV, and MERS-CoV. We provide in-depth analysis of the SARS-CoV-2 and MERS-CoV -1 PRF pseudoknots, including reference and noteworthy mutated sequences. To better understand the impact of mutations, we provide insight on -1 PRF pseudoknot sequence mutations and their effect on resulting structures. We introduce Shapify, a novel algorithm that given an RNA sequence incorporates structural reactivity (SHAPE) data and partial structure information to output an RNA secondary structure prediction within a biologically sound hierarchical folding approach. Shapify enhances our understanding of SARS-CoV-2 -1 PRF pseudoknot conformations by providing energetically favourable predictions that are relevant to structure-function and may correlate with -1 PRF efficiency. Applied to the SARS-CoV-2 -1 PRF pseudoknot, Shapify unveils previously unknown paths from initial stems to pseudoknotted structures. By contextualizing our work with available experimental data, our structure predictions motivate future RNA structure-function research and can aid 3-D modeling of pseudoknots.

Indexed as

COVID-19SARS-CoV-2HumansMolecular ConformationNucleic Acid ConformationRNA, ViralRNA, Viral

Identifiers

PMID36854032
PMCPMC10004594
OpenAlexW4322623665

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read48
identifiers read19
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 Socratic graph.