OptiTope

OptiTope selects and optimizes sets of peptide epitopes to maximize predicted immunogenicity and binding to MHC molecules across individuals or populations for vaccine design.

Key Features:

• MHC Allele Probabilities: Considers the distribution of MHC alleles within a target population to prioritize epitopes with broad population coverage.
• Peptide Mutation Rates: Accounts for peptide mutation rates to avoid epitopes likely to lose binding affinity or immunogenicity.
• Maximum Number of Selected Peptides: Optimizes epitope selection subject to a specified maximum number of peptides reflecting economic and regulatory constraints.
• Individual-specific Optimization: Tailors epitope sets to individual MHC allele profiles to maximize predicted immunogenicity for specific patients.
• Population-level Optimization: Designs epitope sets optimized for target population MHC allele distributions, including ethnic populations.
• Provable Optimality: Produces an epitope set that is provably optimal under the supplied constraints.

Scientific Applications:

• Viral vaccine development: Selects immunogenic peptides derived from pathogen proteins to support vaccine design against viral infections.
• Cancer vaccine and immunotherapy: Identifies tumor-associated peptide epitopes to support cancer vaccine development and related immunotherapies.

Methodology:

Computational algorithms evaluate and rank potential epitopes based on predicted immunogenicity and binding affinity to MHC molecules, integrating data on allele frequencies, peptide mutation rates, and regulatory constraints to produce a provably optimal set of epitopes.