Exploring the SARS-CoV-2 structural proteins for multi-epitope vaccine development: an in-silico approach

ABSTRACT

Introduction

The ongoing life-threatening pandemic of coronavirus disease 2019 (COVID-19) has extensively affected the world. During this global health crisis, it is fundamentally crucial to find strategies to combat SARS-CoV-2. Despite several efforts in this direction and continuing clinical trials, no vaccine has been approved for it yet.

Methods

To find a preventive measure, we have computationally designed a multi-epitopic subunit vaccine using immuno-informatic approaches.

Results

The structural proteins of SARS-CoV-2 involved in its survival and pathogenicity were used to predict antigenic epitopes. The antigenic epitopes were capable of eliciting a strong humoral as well as cell-mediated immune response, our predictions suggest. The final vaccine was constructed by joining the all epitopes with specific linkers and to enhance their stability and immunogenicity. The physicochemical property of the vaccine was assessed. The vaccine 3D structure prediction and validation were done and docked with the human TLR-3 receptor. Furthermore, molecular dynamics simulations of the vaccine-TLR-3 receptor complex are employed to assess its dynamic motions and binding stability in-silico.

Conclusion

Based on this study, we strongly suggest synthesizing this vaccine, which further can be tested in-vitro and in-vivo to check its potency in a cure for COVID-19.

KEYWORDS:

• SARS-CoV-2
• vaccine
• epitopes
• spike glycoprotein
• nucleocapsid
• envelope

Author contribution

AK, PK, KUS, SK, TB: acquisition and interpretation of data, writing, and editing of the manuscript.

Acknowledgments

The authors would like to thank IIT Mandi for research facilities. RG is thankful to DBT, Govt. of India (BT/11/IYBA/2018/06) to RG. AK is supported from DBT, Govt. of India grant (BT/11/IYBA/2018/06). PK and SK were supported by MHRD-India for their funding. KUS and TB are grateful to the ICMR SRF and DST INSPIRE PhD fellowships, respectively.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.