Shapify: Paths to SARS-CoV-2 frameshifting pseudoknot.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
02 2023
02 2023
Historique:
received:
04
10
2022
accepted:
05
02
2023
revised:
10
03
2023
pubmed:
1
3
2023
medline:
15
3
2023
entrez:
28
2
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 36854032
doi: 10.1371/journal.pcbi.1010922
pii: PCOMPBIOL-D-22-01468
pmc: PMC10004594
doi:
Substances chimiques
RNA, Viral
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1010922Informations de copyright
Copyright: © 2023 Trinity et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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