Designing a multi-epitope peptide based vaccine against SARS-CoV-2

  1. Abhishek Singh
  2. Mukesh Thakur
  3. Lalit Kumar Sharma
  4. Kailash Chandra

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

COVID-19 pandemic has resulted in 16,114,449 cases with 646,641 deaths from the 217 countries, or territories as on July 27th 2020. Due to multifaceted issues and challenges in the implementation of the safety and preventive measures, inconsistent coordination between societies-governments and most importantly lack of specific vaccine to SARS-CoV-2, the spread of the virus that initially emerged at Wuhan is still uprising after taking a heavy toll on human life. In the present study, we mapped immunogenic epitopes present on the four structural proteins of SARS-CoV-2 and we designed a multi-epitope peptide based vaccine that, demonstrated a high immunogenic response with a vast application on world’s human population. On codon optimization and in-silico cloning, we found that candidate vaccine showed high expression in E. coli and immune simulation resulted in inducing a high level of both B-cell and T-cell mediated immunity. The results predicted that exposure of vaccine by administrating three injections significantly subsidized the antigen growth in the system. The proposed candidate vaccine found promising by yielding desired results and hence, should be validated by practical experimentations for its functioning and efficacy to neutralize SARS-CoV-2.

Article activity feed

  1. Version published to 10.1038/s41598-020-73371-y
  2. ScreenIT

    SciScore for 10.1101/2020.04.15.040618: (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: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The lack of knowledge regarding the response of the immune system against viral infection is one of the major limitations in the path of vaccine development for SARS-CoV-2. This study is the piolt attempt in describing the potential immunogenic target over the structural proteins and proposes a novel multi-epitope vaccine construct, by providing new rays of hope in the initial phase of vaccine development. Certain criteria like poor antigenicity, allergenicity, low affinity towards the immune cells, autoimmunity and oversize that could influence the effectiveness, have been evaluated on the proposed vaccine construct following various computational and immunoinformatics approach. The retrieved structural proteins and their antigenicity score suggested that the Envelop protein is the most potent protein to generate immune response considering its role in viral assembly. Since, immunity against any pathogen is prominently dependent, how it gets recognized by B cells and T cells. We identified epitopes corresponding to B cells and T cells in each structural protein so that both humoral and cellular immunity can be induced with the exposure of vaccine construct. The proposed vaccine construct is designed based on the epitopes that have been selected with the most robust criteria,e.g. their nature of antigenic, non-allergic, 100% conserved among the target proteins, their affinity for multiple alleles, no homology with any of the human proteins, their worldwide coverage of human p...

    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.
    • No funding statement was detected.
    • 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.

  3. Version published to 10.1101/2020.04.15.040618 on bioRxiv