Pf-PeptideFilter: An Interactive Catalogue of Peptide Vaccine Candidates for Plasmodium falciparum

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Abstract In the last decade, there has been substantial progress in vaccine development for malaria, with two WHO-recommended vaccines now available–RTS,S/AS01 (Mosquirix) and R21/Matrix-M. While these vaccines represent significant milestones, their partial efficacy underscores the need to develop next-generation vaccine approaches capable of broader, longer-lasting protection. Peptide vaccines are a promising strategy, as they focus on short, synthetic peptides specifically selected to trigger a T-cell immune response. However, developing effective peptide vaccines for malaria remains challenging, due to the extensive genetic diversity of Plasmodium falciparum. Currently, tools for comparing and prioritising immunogenic targets remain limited, and existing approaches overlook key factors, including genetic variation, lifecycle-stage expression, and peptide-level properties, each of which are critical for vaccine efficacy. To address these gaps, we developed Pf-PeptideFilter, an interactive web-based application and curated database designed for filtering peptide vaccine targets across the P. falciparum genome. By integrating population-scale genomic information (Pf7), liver-stage transcriptomics, and other biological annotations, Pf-PeptideFilter enables users to interactively filter potential vaccine candidates from the P. falciparum genome, based on several criteria relevant to vaccine design. The app allows users to prioritise candidate genes and peptides with immunogenic potential and export shortlists for incorporation into experimental workflows, offering an interactive platform for rational peptide vaccine design in P. falciparum . Author Summary Malaria vaccines are challenging to design because the parasite responsible for most infections, Plasmodium falciparum , is highly genetically diverse. If a vaccine targets part of the parasite proteome that varies between strains, it may protect against only a subset of parasites and perform poorly across regions. Peptide vaccines offer a promising approach, by focusing immune responses on short, synthetic peptides selected to trigger T-cell immunity. However, identifying which peptides to include in a vaccine is difficult, as the parasite genome contains thousands of genes and huge numbers of potential peptide targets. Here, we introduce Pf-PeptideFilter, an interactive tool that helps researchers prioritise peptide vaccine candidates using a series of biologically relevant filters. We integrate population-scale genome variation from thousands of parasite samples with information on gene expression during liver infection, similarity to human proteins, and conservation across related parasite species. Users can adjust filtering thresholds and immediately see how these choices affect which genes and peptides are retained. Pf-PeptideFilter generates downloadable shortlists designed to support experimental follow-up, providing a robust and transparent platform for the early stages of vaccine design.

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