Identification and Validation of Peptides Specifying SARS-CoV-2 B-Cell Epitopes Eliciting Neutralizing Antibodies

Vaccination is an effective means of inducing immune protection to prevent transmissible diseases. During the Covid-19 pandemic, immunizations using traditional and novel vaccine platforms such as the inactivated SARSCo-V-2 vaccine, adenoviral-vectored, and nucleic acid-based mRNA vaccines have been relatively successful in controlling the rates of infection and hospitalizations. Nevertheless, the danger posed by the emergence of SARS-CoV-2 variants would set the stage for the design of next generation vaccines. To overcome the lack of efficacy of current vaccines against emerging SARS-CoV-2 variants, new vaccines must be able to overcome the reduced effectiveness of the current vaccines. Since the current Covid-19 vaccines are dependent on the whole S-protein of Wuhan strain as the antigen, mutations have rendered the current Covid-19 vaccines less effective against variants of concern (VoCs). Instead of using the whole S-protein, peptide-based epitopes could be predicted using immunoinformatic approaches, simulation of the 3D structures, overlapping peptides covering the whole length of the S-protein or peptide arrays based on synthetic peptide combinatorial libraries comprising peptides recognizable by monoclonal antibodies. B-cell epitopes were predicted, and immunogenicity of peptides was validated in mice by immunizing mice with peptides conjugated to keyhole limpet hemocyanin (KLH) mixed with Montanide 51 as an adjuvant. The immunogenicity of epitopes that could elicit peptide specific IgGs was determined by peptide-based ELISA. Neutralizing activities were determined by cPass and pseudovirus-based neutralization assays.