COVIEdb: A database for potential immune epitopes of coronaviruses

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

2019 novel coronavirus (2019-nCoV) has caused large-scale pandemic COVID-19 all over the world. It’s essential to find out which parts of the 2019-nCoV sequence are recognized by human immune system for vaccine development. And for the prevention of the potential outbreak of similar coronaviruses in the future, vaccines against immunogenic epitopes shared by different human coronaviruses are essential. Here we predict all the potential B/T-cell epitopes for SARS-CoV, MERS-CoV, 2019-nCoV and RaTG13-CoV based on the protein sequences. We found YFKYWDQTY in ORF1ab protein, VYDPLQPEL and TVYDPLQPEL in spike (S) protein might be pan-coronavirus targets for vaccine development. All the predicted results are stored in a database COVIEdb ( http://biopharm.zju.edu.cn/coviedb/ ).

Article activity feed

  1. SciScore for 10.1101/2020.05.24.096164: (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.