The SARS-CoV-2 spike residues 616/644 and 1138/1169 delineate two antibody epitopes in COVID-19 mRNA COMINARTY vaccine (Pfizer/BioNTech)

The newly identified coronavirus SARS-CoV-2 is responsible for the worldwide pandemic COVID-19. Considerable efforts have been made for the development of effective vaccine strategies against COVID-19. The SARS-CoV-2 spike protein has been assigned as major antigen candidate for the development of COVID-19 vaccines. The COVID-19 mRNA BNT162b2 vaccine (comirnaty, Pfizer/BioNTech) is a lipid nanoparticle-encapsulated mRNA encoding a full-length and prefusion-stabilized SARS-CoV-2 spike protein. In the present study, synthetic peptide-based ELISA assays were performed to identify linear B cell epitopes that contribute to elicitation of antibody response in vaccinated individuals with comirnaty. The synthetic S2P6 peptide containing the spike residues 1138/1169 and to a lesser extent, the synthetic S1P4 peptide containing the spike residues 616/644 were recognized by the immune sera from comirnaty recipients but not COVID-19 recovered patients. The S2P6 peptide has been identified as immunogenic peptide in adult BALB/c mice that received protein-peptide conjugates in a prime-boost schedule. Based on our data, we propose that the synthetic S2P6 peptide and to a lesser extent the synthetic S1P4 peptide, would be of interest to measure the dynamic of antibody response to comirnaty vaccine. The synthetic S2P6 peptide is a SARS-CoV-2 spike peptide candidate for the development of peptide-based vaccines against COVID-19.

Immunogenicity and protectivity of the peptide candidate vaccine against SARS-CoV-2

Background: In 2020, the pandemic caused by novel coronavirus infection has become one of the most critical global health challenges during the past century. The lack of a vaccine, as the most effective way to control the novel infection, has prompted the development of a large number of preventive products by the scientific community. We have developed a candidate vaccine (EpiVacCorona) against novel coronavirus infection caused by SARS-CoV-2 that is based on chemically synthesized peptides conjugated to a carrier protein and adsorbed on aluminum hydroxide and studied the specific activity of the developed vaccine. Aims: Study of the immunogenicity and protectivity of the peptide candidate vaccine EpiVacCorona. Materials and methods: the work was performed using standard molecular biological, virological and histological methods. Results: It was demonstrated that EpiVacCorona, when administered twice, spaced 14 days apart, to hamsters, ferrets, and non-human primates (African green monkeys, rhesus macaques) at a dose of 260 g, which is equal to one inoculation dose for humans, induces virus-specific antibodies in 100% of the animals. Experiments in hamsters showed this vaccine to be associated with the dose-dependent immunogenicity. The vaccine was shown to accelerate the elimination of the virus from the upper respiratory tract in ferrets and prevent the development of pneumonia in hamsters and non-human primates following a respiratory challenge with novel coronavirus. Conclusions: The results of a preclinical specific activity study indicate that the use of EpiVacCorona has the potential for human vaccination.

Identification of peptide candidate against COVID-19 through reverse vaccinology: An immunoinformatics approach

Novel corona virus disease 2019 (COVID-19) is emerging as a pandemic situation and declared as a global health emergency by WHO. Due to lack of specific medicine and vaccine, viral infection has gained a frightening rate and created a devastating state across the globe. Here authors have attempted to design epitope based potential peptide as a vaccine candidate using immunoinformatics approach. As of evidence from literatures, SARS-CoV-2 Spike protein is a key protein to initiate the viral infection within a host cell thus used here as a reasonable vaccine target. We have predicted a 9-mer peptide as representative of both B-cell and T-cell epitopic region along with suitable properties such as antigenic and non-allergenic. To its support, strong molecular interaction of the predicted peptide was also observed with MHC molecules and Toll Like receptors. The present study may helpful to step forward in the development of vaccine candidates against COVID-19.

Immunoinformatics Study on Early 4 Protein of Human Papillomavirus Type 16 for Cervical Cancer Vaccine Peptide Candidate

The aims of this study were to carry out testing of the early 4 protein of type 16 HPV through immunoinformatics meth-ods in an effort to get the peptide vaccine candidate for cervical cancer. The software used are IEDB-AR, CABSdock and Accelrys Discovery Study 4.5. Based on the analysis that sequence of ami-no acid lysine, leucine, leucine, glycine, serine, threonine, tryp-tophan, proline and threonine (KLLGSTWPT) and the sequence of amino acid tyrosine, tyrosine, valine, leucine, histidine, leucine, cysteine, leucine, alanine, alanine, threonine, lysine, tyrosine, pro-line and leucine (YYVLHLCLAATKYPL) are peptide vaccine can-didate for cervical cancer from the early 4 protein of HPV type 16

Purple: A Computational Workflow for Strategic Selection of Peptides for Viral Diagnostics Using MS-Based Targeted Proteomics

Emerging virus diseases present a global threat to public health. To detect viral pathogens in time-critical scenarios, accurate and fast diagnostic assays are required. Such assays can now be established using mass spectrometry-based targeted proteomics, by which viral proteins can be rapidly detected from complex samples down to the strain-level with high sensitivity and reproducibility. Developing such targeted assays involves tedious steps of peptide candidate selection, peptide synthesis, and assay optimization. Peptide selection requires extensive preprocessing by comparing candidate peptides against a large search space of background proteins. Here we present Purple (Picking unique relevant peptides for viral experiments), a software tool for selecting target-specific peptide candidates directly from given proteome sequence data. It comes with an intuitive graphical user interface, various parameter options and a threshold-based filtering strategy for homologous sequences. Purple enables peptide candidate selection across various taxonomic levels and filtering against backgrounds of varying complexity. Its functionality is demonstrated using data from different virus species and strains. Our software enables to build taxon-specific targeted assays and paves the way to time-efficient and robust viral diagnostics using targeted proteomics.