Immunoinformatics approach to epitope-based vaccine design against the SARS-CoV-2 in Bangladeshi patients

Abstract

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic which has brought a great challenge to public health. After the first emergence of novel coronavirus SARS-CoV-2 in the city of Wuhan, China, in December 2019. As of March 2020, SARS-CoV-2 was first reported in Bangladesh and since then the country has experienced a steady rise in infections, resulting in 13,355,191 cases and 29,024 deaths as of 27 February 2022. Bioinformatics techniques are used to predict B cell and T cell epitopes from the new SARS-CoV-2 spike glycoprotein in order to build a unique multiple epitope vaccine. The immunogenicity, antigenicity scores, and toxicity of these epitopes were evaluated and chosen based on their capacity to elicit an immune response.

Result: The best multi-epitope of the possible immunogenic property was created by combining epitopes. EAAAK, AAY, and GPGPG linkers were used to connect the epitopes. In several computer-based immune response analyses, this vaccine design was found to be efficient, as well as having high population coverage.

Conclusion: This research is entirely reliant on the development of epitope-based vaccines, and these in silico findings would represent a major step forward in the development of a vaccine that might eradicate SARS-CoV-2 in Bangladeshi patients.

Keywords: B cell; Epitope; Immunoinformatics; SARS-CoV-2; T cell; Vaccine.

Fig. 1

Experimental diagram for epitope-based vaccine design

Fig. 2

Protein secondary structure prediction: H (helix), E (strands), and C (coils)

Fig. 3

Graphical and 3D view of vaccine construction. 50 s ribosomal protein, EAAAL Linker, CPGPG Linker, and AAY Linker are shown

Fig. 4

Validation of the final vaccine 3D models (A, B). PROSA 3D structure validation showing corresponding Z-score (− 8.77) (C). Ramachandran plot shows most favored (87.5%), allowed (12.5%), generously allowed (0.0%), and disallowed regions (0.0%) respectively (D)

Fig. 5

TLR-4 (PDB ID: 4G8A) vaccine docked complex. A The TLR-4 (receptor) is shown in light green, while the purple color represents the multi-epitope subunit vaccine. B Graphical representation of hydrogen bonds interaction between TLR-4 (ChainA) and vaccine complex(ChainB)

Fig. 6

MD simulation of multi-epitope vaccine complexed with the TLR-4 a MNA mobility, b deformability, c B-factor, d eigen values, e variance, f co-variance map red (correlated) and white (uncorrelated) or blue (anti-correlated) movements, and g elastic network

Fig. 7

Codon optimization of design vaccine show sequence before adaptation and after adaptation

Fig. 8

Vaccine immune simulation through C-ImmSim server shows production of antibodies, B cell and T cell population and cytokine production