HLA-directed bioinformatics approach for genome-wide mapping of dengue CTL epitopes

Immunoinformatics aided approach for predicting potent cytotoxic T cell epitopes of respiratory syncytial virus

Respiratory syncytial virus (RSV) is an infectious viral pathogen that causing serious respiratory infection in adults and neonates. The only approved therapies for RSV are the monoclonal antibodies palivizumab and its derivative motavizumab. Both treatments are expensive and require a hospital setting for administration. A vaccine represents a safe, effective and cheaper alternative for preventing RSV infection. In silico prediction methods have proven to be valuable in speeding up the process of vaccine design. In this study, reverse vaccinology methods were used to predict the cytotoxic T lymphocytes (CTL) epitopes from the entire proteome of RSV strain A. From amongst 3402 predicted binders to 12 high frequency alleles from the Immune Epitope Database (IEDB), 567 had positive processing scores while 327 epitopes were predicted to be immunogenic. A thorough examination of the 327 epitopes for possible antigenicity, allergenicity and toxicity resulted in 95 epitopes with desirable properties. A BLASTp analysis revealed 94 unique and non-homologous epitopes that were subjected to molecular docking across the 12 high frequency alleles. The final dataset of 70 epitopes contained 13 experimentally proven and 57 unique epitopes from a total of 11 RSV proteins. From our findings on selected T-cell-specific RSV antigen epitopes, notably the four epitopes confirmed to exhibit stable binding by molecular dynamics. The prediction pipeline used in this study represents an effective way to screen the immunogenic epitopes from other pathogens.Communicated by Ramaswamy H. Sarma.

Designing of cytotoxic T lymphocyte-based multi-epitope vaccine against SARS-CoV2: a reverse vaccinology approach

SARS-CoV2 is a single-stranded RNA virus, gaining much attention after it out broke in China in December 2019. The virus rapidly spread to several countries around the world and caused severe respiratory illness to humans. Since the outbreak, researchers around the world have devoted maximum resources and effort to develop a potent vaccine that would offer protection to uninfected individuals against SARS-CoV2. Reverse vaccinology is a relatively new approach that thrives faster in vaccine research. In this study, we constructed Cytotoxic T Lymphocytes (CTL)-based multi-epitope vaccine using hybrid epitope prediction methods. A total of 121 immunogenic CTL epitopes were screened by various sequence-based prediction methods and docked with their respective HLA alleles using the AutoDock Vina v1.1.2. In all, 17 epitopes were selected based on their binding affinity, followed by the construction of multi-epitope vaccine by placing the appropriate linkers between the epitopes and tuberculosis heparin-binding hemagglutinin (HBHA) adjuvant. The final vaccine construct was modeled by the I-TASSER server and the best model was further validated by ERRAT, ProSA, and PROCHECK servers. Furthermore, the molecular interaction of the constructed vaccine with TLR4 was assessed by ClusPro 2.0 and PROtein binDIng enerGY prediction (PRODIGY) server. The immune simulation analysis confirms that the constructed vaccine was capable of inducing long-lasting memory T helper (Th) and CTL responses. Finally, the nucleotide sequence was codon-optimized by the JCAT tool and cloned into the pET21a (+) vector. The current results reveal that the candidate vaccine is capable of provoking robust CTL response against the SARS-CoV2.Communicated by Ramaswamy H. Sarma.

Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19

An immunoinformatics-based approach was used to identify potential multivalent subunit CTL vaccine candidates for SARS-CoV-2. Criteria for computational screening included antigen processing, antigenicity, allergenicity, and toxicity. A total of 2604 epitopes were found to be strong binders to MHC class I molecules when analyzed using IEDB tools. Further testing for antigen processing yielded 826 peptides of which 451 were 9-mers that were analyzed for potential antigenicity. Antigenic properties were predicted for 102 of the 451 peptides. Further assessment for potential allergenicity and toxicity narrowed the number of candidate CTL epitopes to 50 peptide sequences, 45 of which were present in all strains of SARS-CoV-2 that were tested. The predicted CTL epitopes were then tested to eliminate those with MHC class II binding potential, a property that could induce hyperinflammatory responses mediated by T_H2 cells in immunized hosts. Eighteen of the 50 epitopes did not show class II binding potential. To our knowledge this is the first comprehensive analysis on the proteome of SARS-CoV-2 for prediction of CTL epitopes lacking binding properties that could stimulate unwanted T_H2 responses. Future studies will be needed to assess these epitopes as multivalent subunit vaccine candidates which stimulate protective CTL responses against SARS-COV-2.