article · Frontiers in Microbiology
Computational methods and reverse vaccinology were used to design a multi-epitope-based peptide vaccine candidate targeting emerging variants of SARS-CoV-2, including Delta, Lambda, Iota, Omicron, and Kappa. The design process focused on the viral spike glycoprotein, identifying dual-purpose B-cell and T-cell epitopes that were screened for antigenicity, allergenicity, and global population coverage. Selected epitopes were assembled into a single construct alongside linkers and adjuvants. Subsequent evaluations examined the physicochemical characteristics, secondary structure, and three-dimensional model of the vaccine, which was refined and validated. In silico investigations confirmed binding interactions between the vaccine candidate and Toll-like receptors, alongside simulated immune profiling. Finally, codon optimisation was carried out to assess compatibility for expression in an Escherichia coli vector, and computer simulations tested the overall stability and conformational behaviour of the resulting protein complex.
Emerging variants of SARS-CoV-2 can diminish the effectiveness of existing vaccines and treatments. By applying computational tools and reverse vaccinology, researchers can rapidly evaluate multiple viral mutations simultaneously. This allows the preliminary design of targeted peptide candidates that cover diverse viral strains and broad human populations prior to undertaking costly and time-consuming laboratory synthesis.
This work represents an early-stage computational design that could serve vaccine developers and biopharmaceutical researchers seeking multi-variant coronavirus antigens. The candidate is distant from practical application, as the findings rely entirely on in silico modelling and simulated immune profiles. Real-world development would require laboratory synthesis, in vitro validation, expression in microbial vectors, and formal pre-clinical safety and efficacy trials before any therapeutic product can emerge.
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Many countries around the world are facing severe challenges due to the recently emerging variants of SARS-CoV-2. Over the last few months, scientists have been developing treatments, drugs, and vaccines to subdue the virus and prevent its transmission. In this context, a peptide-based vaccine construct containing pathogenic proteins of the virus known to elicit an immune response was constructed. An analysis of the spike protein-based epitopes allowed us to design an "epitope-based subunit vaccine" against coronavirus using the approaches of "reverse vaccinology" and "immunoinformatics." Computational experimentation and a systematic, comprehensive protocol were followed with an aim to develop and design a multi-epitope-based peptide (MEBP) vaccine candidate. Our study attempted to predict an MEBP vaccine by introducing mutations of SARS-CoV-2 (Delta, Lambda, Iota, Omicron, and Kappa) in Spike glycoprotein and predicting dual-purpose epitopes (B-cell and T-cell). This was followed by screening the selected epitopes based on antigenicity, allergenicity, and population coverage and constructing them into a vaccine by using linkers and adjuvants. The vaccine construct was analyzed for its physicochemical properties and secondary structure prediction, and a 3D structure was built, refined, and validated. Furthermore, the peptide-protein interaction of the vaccine construct with Toll-like receptor (TLR) molecules was performed. Immune profiling was performed to check the immune response. Codon optimization of the vaccine construct was performed to obtain the GC content before cloning it into the <i>E. coli</i> genome, facilitating its progression it into a vector. Finally, an <i>in-silico</i> simulation of the vaccine-protein complex was performed to comprehend its stability and conformational behavior.
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DOI: 10.3389/fmicb.2023.1251716
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