Computer‐aided design of T‐cell epitope‐based vaccines: addressing population coverage

Abstract

Epitope-based vaccines (EVs) make use of short antigen-derived peptides corresponding to immune epitopes, which are administered to trigger a protective humoral and/or cellular immune response. EVs potentially allow for precise control over the immune response activation by focusing on the most relevant - immunogenic and conserved - antigen regions. Experimental screening of large sets of peptides is time-consuming and costly; therefore, in silico methods that facilitate T-cell epitope mapping of protein antigens are paramount for EV development. The prediction of T-cell epitopes focuses on the peptide presentation process by proteins encoded by the major histocompatibility complex (MHC). Because different MHCs have different specificities and T-cell epitope repertoires, individuals are likely to respond to a different set of peptides from a given pathogen in genetically heterogeneous human populations. In addition, protective immune responses are only expected if T-cell epitopes are restricted by MHC proteins expressed at high frequencies in the target population. Therefore, without careful consideration of the specificity and prevalence of the MHC proteins, EVs could fail to adequately cover the target population. This article reviews state-of-the-art algorithms and computational tools to guide EV design through all the stages of the process: epitope prediction, epitope selection and vaccine assembly, while optimizing vaccine immunogenicity and coping with genetic variation in humans and pathogens.

Towards the first multi-epitope recombinant vaccine against Crimean-Congo hemorrhagic fever virus: A computer-aided vaccine design approach

“…Computer-aided vaccine design, which also called computational immunology, can provide an integrated pipeline for mapping potential Band T-cell epitopes, allergenic sites in studied antigens and prediction of HLA-epitope affinity. Thus, the approach could reduce the time and cost required for vaccine design [27][28][29]. In recent decade, computational design of epitope-based vaccine have been used for vaccine development against many infectious disease and even cancer.…”

In Silico Analysis of Epitope-Based Vaccine Candidates against Hepatitis B Virus Polymerase Protein

“…Conservative prediction intends to provide broader protection for multiple genotypes and species [31]. Immunogenicity prediction is used to select the epitopes that are able to elicit T-cell response, and population coverage prediction is based on the distribution of MHC types in different regions [66]. Finally, B-cell epitope vaccine design focus on protein structures in order to predict the epitopes that can induce humoral immunity [67].…”

DNA vaccine with discontinuous T‐cell epitope insertions into HSP65 scaffold as a potential means to improve immunogenicity of multi‐epitope Mycobacterium tuberculosis vaccine

“…Finally, PES gene was obtained through PCR using fragments 2 and 5 as template and T1/T7 as primers. Four epitopes, ESAT-6 1-20 , Ag85B 241-255 , PPE25 241-255 and PE19 [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] were genetically inserted into the HSP65 scaffold directly, whereas the linker (AAY, gccgcctac) fragment was connected to the 3 0 end of MTB10.4 [3][4][5][6][7][8][9][10][11] to enhance appropriate CTL epitope processing before insertion. The construct included a Kozak sequence at the N-terminus.…”

“…PPE25 and PE19 belong to the PE/PPE proteins, which are associated with the virulence, persistence, and pathogenesis of mycobacteria infection and play a key role in antigenic variation and immunodominance (22)(23)(24). A previous study demonstrated several marked CD4 þ T-cell immunodominant epitopes of the ESX-5-associated PE/PPE; here, we focused on the major Th1 epitope PPE25 241-255 and PE19 [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] (25). Moreover, CTL epitope MTB10.4 [3][4][5][6][7][8][9][10][11] was also selected to induce a specific CD8 þ T-cell response against mycobacterial infection (26,27).…”