In Silico Prediction of Plasmodium falciparum PfRipr Epitopes as Vaccine Candidates

Abstract

Abstract Background The global malarial death toll in 2020 was ~627,000, 77% of which occurred in children <5 years of age. Plasmodium falciparum is the most lethal parasite of its genus but has evaded vaccine development due to its complex life cycle and redundant invasion mechanisms. Epitope-based vaccines hold significant promise due to their ability to target dominant and/or conserved regions in highly antigenically variable pathogens, including malaria. The recently characterized P. falciparum merozoite Rh5 interacting protein (PfRipr) is nonredundant, highly conserved, and essential for erythrocyte invasion, making it an ideal target for a bloodstage malaria vaccine. (Figure 1) We sought to analyze P. falciparum sequences from highly endemic areas using bioinformatic approaches that identify candidate PfRipr epitope-based bloodstage vaccine antigens for inclusion in a multiantigen vaccine. Figure 1: Model of binding and insertion of PRCR complex to erythrocyte basigin in merozoite invasion. Adapted from Scally et al. 2022. (https://doi.org/10.1038/s41564-022-01261-2 , https://creativecommons.org/licenses/by/4.0/) Methods Using two P. falciparum sequence datasets from Burkina Faso and Uganda, we assessed the immunogenic potential of PfRipr epitopes for T-cell receptor binding and B-cell recognition. T-cell receptor binding was predicted using NetMHCpan and NetMHCIIpan searching against MHC I and II alleles with high regional frequencies. Using an in-silico 3D model of PfRipr predicted via AlphaFold, tertiary structures of all PfRipr sample sequences were predicted via SWISS-MODEL then analyzed by ElliPro to identify linear and discontinuous B-cell epitopes. (Figure 2) Putative epitopes were filtered using binding thresholds, allele coverage, conservation, antigenicity, and allergenicity. (Figure 3) Figure 2: Protocol for B-cell epitope prediction using AlphaFold for template modeling, Swiss-Model for homology-based modeling of sample sequences, and ElliPro for continuous and discontinuous epitope prediction. Figure 3: Protocol for sorting T-cell epitopes using Average Allele Coverage (percentage of alleles in which the protein sequence was identified as an epitope) and B-cell epitopes using ElliPro Score (Protrusion Index representing surface accessibility of the epitope). Results The Burkina Faso PfRipr dataset predicted 1729 unique T-cell and 51 unique B-cell epitopes, and 28 T-cell and 4 B-cell epitopes remained post-filtration. Epitope prediction using the Ugandan dataset predicted 576 unique T-cell and 53 unique B-cell epitopes, and 57 T-cell and 7 B-cell epitopes remained post-filtration. Between the two datasets, there were 19 matching epitopes with 7 MHC I, 9 MHC II, 1 linear, and 2 discontinuous. (Tables 1-2, Figure 4) These epitopes were used to design a multi-epitope-based vaccine construct with a Flagellin adjuvant and peptide linkers to separate functional regions for immune processing. (Figure 5) Figure 4: 3D model of PfRipr with labeled B-cell epitopes. Predicted tertiary structure adapted from AlphaFold database. (https://doi.org/10.1038/s41586-021-03819-2, https://doi.org/10.1093/nar/gkab1061, https://creativecommons.org/licenses/by/4.0/) Figure 5: Schematic representation of hypothetical multi-epitope vaccine construct. FliC is added to the N-terminus to stimulate and amplify immune response. The EAAAK linker is used to separate the bifunctional fusion protein domains. AAY linkers are used to amplify MHC I and II epitopes and prevent junctional epitope binding. GPGPG linkers between B-cell epitopes function to minimize junctional epitopes and retain conformational-dependent immunogenicity. A six amino acid Histidine (6H) chain was added to the C-terminus to aid during lab purification processes. Conclusions Immunoinformatic tools employed in sequence identified candidate PfRipr epitopes used to design a bloodstage vaccine construct against P. falciparum. To validate their predicted immunogenicity, epitopes can be further investigated using in silico protein stabilization and docking simulations, in vitro methods such as HLA stabilization or T-cell activation assays, and in vivo methods using transgenic mouse models. The pipeline of immunoinformatic analyses formulated in this project can be further applied to a larger database of diverse P. falciparum sequences collected from other malaria endemic regions to develop vaccines effective against circulating strains.