Considering epitopes conservity in targeting SARS-CoV-2 mutations in variants: a novel immunoinformatics approach to vaccine design

Discovering conserved epitopes of Monkeypox: Novel immunoinformatic and machine learning approaches

The Monkeypox virus, an Orthopoxvirus with zoonotic origins, has been responsible for a growing number of human infections reminiscent of smallpox since May 2022, as reported by the World Health Organization. As of now, there are no established medical treatments for managing Monkeypox infections. In this study, we used machine learning to select conserved epitopes. Proteins were determined using Reverse Vaccinology and Gene Ontology subcellular localization, and their epitopes were predicted. NextClade was used to calculate the number of mutations in each amino acid position using 2433 Monkeypox sequences. The Unsupervised Nearest Neighbor machine learning algorithm and ideal matrix [0 0] were used to calculate the conservancy score of epitopes. Six proteins were determined for epitope prediction. Finally, 47 MHC-I epitopes, 5 MHC-II epitopes, and 10 Linear B cell epitopes were discovered. Our method can select epitopes for vaccine design to prevent viruses with accelerated evolution and high mutation rate.

SARS-CoV-2 Spike protein peptides displayed in the Pyrococcus furiosus RAD system preserve epitopes antigenicity, immunogenicity, and virus-neutralizing activity of antibodies

Amongst the potential contribution of protein or peptide-display systems to study epitopes with relevant immunological features, the RAD display system stands out as a highly stable scaffold protein that allows the presentation of constrained target peptides. Here, we employed the RAD display system to present peptides derived from the SARS-CoV-2 Spike (S) protein as a tool to detect specific serum antibodies and to generate polyclonal antibodies capable of inhibiting SARS-CoV-2 infectivity in vitro. 44 linear S-derived peptides were genetically fused with the RAD scaffold (RAD-SCoV-epitopes) and screened for antigenicity with sera collected from COVID-19-infected patients. In a second step, selected RAD-SCoV-epitopes were used to immunize mice and generate antibodies. Phenotypic screening showed that some of these antibodies were able to recognize replicating viral particles in VERO CCL-81 and most notably seven of the RAD-SCoV-epitopes were able to induce antibodies that inhibited viral infection. Our findings highlight the RAD display system as an useful platform for the immunological characterization of peptides and a potentially valuable strategy for the design of antigens for peptide-based vaccines, for epitope-specific antibody mapping, and for the development of antibodies for diagnostic and therapeutic purposes.

Bioinformatics approach for the construction of multiple epitope vaccine against omicron variant of SARS-CoV-2

The World Health Organization categorized SARS-CoV-2 as a variant of concern, having numerous mutations in spike protein, which have been found to evade the effect of antibodies stimulated by the COVID-19 vaccine. The susceptibility to omicron variant by immunization-induced antibodies are direly required for risk evaluation. To avoid the risk of arising viral illness, the construction of a specific vaccine that triggers the production of targeted antibodies to combat infection remains highly imperative. The aim of the present study is to develop a particular vaccine exploiting bioinformatics approaches which can target B- and T-cells epitopes. Through this approach, novel epitopes of the S protein-SARS-CoV-2 were predicted for the development of a multiple epitope vaccine. Multiple epitopes were selected on the basis of toxicity, immunogenicity and antigenicity, and vaccine subunit was constructed having potential immunogenic properties. The epitopes were linked with 3 types of linker EAAAK, AAY and GPGPG for vaccine construction. Subsequently, vaccine structure was docked with the receptor and cloned in a pET-28a (+) vector. The constructed vaccine was ligated in pET-28a (+) vector in E. coli using the SnapGene tool for the expression study and a good immune response was observed. Several computational tools were used to predict and analyze the vaccine constructed by using spike protein sequence of omicrons. The current study identified a Multi-Epitope Vaccine (MEV) as a significant vaccine candidate that could potentially help the global world to combat SARS-CoV-2 infections.