Presence of a SARS-COV-2 protein enhances Amyloid Formation of Serum Amyloid A

  1. Asis K. Jana
  2. Augustus B. Greenwood
  3. Ulrich H. E. Hansmann

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

A marker for the severeness and disease progress of COVID-19 is overexpression of serum amyloid A (SAA) to levels that in other diseases are associated with a risk for SAA amyloidosis. In order to understand whether SAA amyloidosis could also be a long-term risk of SARS-COV-2 infections we have used long all-atom molecular dynamic simulations to study the effect of a SARS-COV-2 protein segment on SAA amyloid formation. Sampling over 40 µs we find that presence of the nine-residue segment SK9, located at the C-terminus of the Envelope protein, increases the propensity for SAA fibril formation by three mechanisms: it reduces the stability of the lipid-transporting hexamer shifting the equilibrium toward monomers, it increases the frequency of aggregation-prone configurations in the resulting chains, and it raises the stability of SAA fibrils. Our results therefore suggest that SAA amyloidosis and related pathologies may be a long-term risk of SARS-COV-2 infections.

Article activity feed

  1. Version published to 10.1101/2021.05.18.444723v2 on bioRxiv
  2. ScreenIT

    SciScore for 10.1101/2021.05.18.444723: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Using the AutoDock Vina software20, we have generated the start configurations for our simulations by docking the SK9-segments in a ratio 1:1 with the SAA chains in our models.
    AutoDock Vina
    suggested: (AutoDock Vina, RRID:SCR_011958)
    Finally, for our fibril models we have again identified SK9 binding positions by a global search using AutoDock Vina.
    AutoDock
    suggested: (AutoDock, RRID:SCR_012746)
    Simulation Protocol: All simulations are carried out using the GROMACS 2018 package22 and are employing the CHARMM 36m all-atom force field23 and TIP3P water21.
    GROMACS
    suggested: (GROMACS, RRID:SCR_014565)

    Results from OddPub: Thank you for sharing your data.

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  3. Version published to 10.1101/2021.05.18.444723v1 on bioRxiv