Anti-frameshifting ligand active against SARS coronavirus-2 is resistant to natural mutations of the frameshift-stimulatory pseudoknot

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

The coronavirus SARS-CoV-2 causing the COVID-19 pandemic uses −1 programmed ribosomal frameshifting (−1 PRF) to control the expression levels of key viral proteins. Because modulating −1 PRF can attenuate viral propagation, ligands binding to the viral RNA pseudoknot that stimulates −1 PRF may prove useful as therapeutics. Mutations in the pseudoknot have been observed over the course of the pandemic, but how they affect −1 PRF and the activity of inhibitors is unknown. Cataloguing natural mutations in all parts of the SARS-CoV-2 pseudoknot, we studied a panel of 6 mutations in key structural regions. Most mutations left the −1 PRF efficiency unchanged, even when base-pairing was disrupted, but one led to a remarkable three-fold decrease, suggesting that SARS-CoV-2 propagation may be less sensitive to modulation of −1 PRF efficiency than some other viruses. Examining the effects of one of the few small-molecule ligands known to suppress −1 PRF significantly in SARS-CoV, we found that it did so by similar amounts in all SARS-CoV-2 mutants tested, regardless of the basal −1 PRF efficiency, indicating that the activity of anti-frameshifting ligands can be resistant to natural pseudoknot mutations. These results have important implications for therapeutic strategies targeting SARS-CoV-2 through modulation of −1 PRF.

Article activity feed

  1. SciScore for 10.1101/2020.06.29.178707: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.