Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Previously submitted to: JMIR Bioinformatics and Biotechnology (no longer under consideration since Dec 18, 2022)

Date Submitted: Oct 19, 2021

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Immunoinformatics approaches to design: A novel multi-epitope vaccine candidate against SARS-CoV-2 and it’s in silico expression

  • Ravi Deval; 
  • Ayushi Saxena; 
  • Zeba Mueed; 
  • Dibyabhaba Pradhan; 
  • Pankaj Kumar Rai

ABSTRACT

Background:

SARS-CoV-2, belonging to the Coronaviridae family, is a novel RNA virus, known for causing fatal disease in humans called COVID-19. Researchers all around the world are keen on developing a precise treatment or vaccine against this deadly disease.

Objective:

The main objective of this paper is to design a novel multi-epitope vaccine candidate against SARS-CoV-2 using immunoinformatics tools.

Methods:

A consensus sequence was generated from various genomes of SARS-Cov-2 available from various countries of the outbreak at the ViPR database using JalView software. T cell and B cell epitopes were predicted by restricting them to certain HLA alleles using various servers (nHLApred, NetMHCIIpan v.3.1, ABCpred) and were validated using IEDB tools. Using these epitopes and adjuvant, a multi-epitope vaccine was constructed in-silicoand was later subjected to allergenicity, antigenicity and physicochemical properties profiling along with identification of conformational B-cell epitopes. The designed vaccine was evaluated via codon optimization by the Jcat server and finally, it’s in-silicoexpression was done in pET-28a(+) vector using snap-gene software.

Results:

A total of 18 epitopes (both T and B cell) were predicted that constituted vaccine construct along with adjuvant and end tag. Vaccine construct was validated and its best structure model was successfully docked with human Toll-like receptors. In-silico expression of the designed vector was also seen in pET-28a(+) plasmid.

Conclusions:

The designed novel vaccine candidate has been validated in-silico to elicit robust immune responses hence; it can be used as a potential model for further development of multi-epitope vaccines in the laboratory.


 Citation

Please cite as:

Deval R, Saxena A, Mueed Z, Pradhan D, Rai PK

Immunoinformatics approaches to design: A novel multi-epitope vaccine candidate against SARS-CoV-2 and it’s in silico expression

JMIR Preprints. 19/10/2021:34349

DOI: 10.2196/preprints.34349

URL: https://preprints.jmir.org/preprint/34349

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.