Vaccine Design

Computational pipeline for designing peptide/subunit vaccine candidates through epitope prediction, population coverage optimization, and immunogenicity assessment.

Reasoning Strategy

Vaccine design requires presenting the right epitopes to elicit protective immunity — not just any immune response, but one that is neutralizing, durable, and broadly applicable. For T-cell vaccines, the core tool is MHC binding prediction (IEDB tools): predict peptide-MHC affinity across multiple HLA alleles, then select epitopes with broad coverage of the target population. For antibody vaccines, prioritize surface-exposed conserved regions — a deeply buried or hypervariable region makes a poor antibody target. MHC binding does not equal immunogenicity; many good binders are not immunogenic in vivo due to tolerance, poor processing, or lack of T-cell help. A multi-epitope strategy (combining MHC-I for CD8+ CTL response, MHC-II for CD4+ helper response, and B-cell epitopes for antibody induction) is more robust than any single epitope. Conservation across pathogen strains is critical — an epitope that mutates under immune pressure (like HIV envelope hypervariable regions) is a poor vaccine target.

LOOK UP DON'T GUESS: Do not predict MHC binding or population coverage from memory — use IEDB_predict_mhci_binding / IEDB_predict_mhcii_binding for T-cell predictions, IEDB_predict_bcell_epitopes for antibody (B-cell) epitope prediction, and iedb_search_epitopes for validated experimental data. Do not assume what's on the pathogen surface; retrieve annotated sequences from UniProt or BVBRC.

Key principles:

1. Epitope-driven — vaccines work by presenting epitopes to T/B cells; start with epitope prediction
2. Population coverage matters — HLA diversity means no single epitope covers everyone; design for breadth
3. Multi-epitope is better — combine CD8+ (MHC-I) and CD4+ (MHC-II) epitopes for robust immunity
4. Conservation = broad protection — conserved epitopes across strains provide cross-protective immunity
5. Evidence grading — T1: clinical trial data, T2: in-vivo immunogenicity, T3: in-vitro binding, T4: computational prediction only