MAPDP

MAPDP performs high-throughput immunopeptidomic and proteogenomic analyses to identify peptides presented by major histocompatibility complex (MHC) molecules and predict peptide–MHC binding for antigen discovery.

Key Features:

• Proteogenomic analysis: Performs proteogenomic analyses of immunopeptidomes compatible with modern mass spectrometers, enabling detection of thousands of peptides from samples with fewer than 100 million cells.
• Data management: Manages large-scale mass spectrometry and proteogenomic datasets for downstream analysis.
• Database access: Provides indexed access to stored immunopeptidomes for comparative analyses.
• Filtering tools: Applies advanced, criteria-based filtering to refine peptide and protein datasets.
• Visualizations: Generates visualizations to support interpretation of complex immunopeptidomic data.
• Annotations: Integrates peptide and variant annotations from IEDB, dbSNP, and gnomAD.
• Peptide-binding affinity prediction: Predicts peptide–MHC binding affinities using mhcflurry and NetMHC algorithms.
• HLA genotyping: Performs HLA genotyping to determine individual HLA alleles for allele-specific analyses.
• Personalized proteome databases: Constructs customized proteome databases for proteogenomic searches.
• Variant-associated peptide discovery: Identifies MHC-presented peptides associated with genetic variants in cancer datasets, including ovarian carcinoma examples.

Scientific Applications:

• Antigen discovery for immunotherapy: Identification of actionable antigenic targets for therapeutic cancer vaccines, adoptive T-cell therapy, and T-cell receptor–based biologics.
• Cancer immunology and personalized medicine: Discovery of neoantigens and variant-associated MHC peptides from tumor datasets to inform personalized immunotherapies.
• Comparative immunopeptidomics: Comparative analysis of immunopeptidomes across samples or conditions to study antigen presentation differences.
• HLA allele-specific studies: Analysis of allele-specific peptide presentation to investigate individual variation in immune responses.

Methodology:

Performs proteogenomic analyses and mass spectrometry data handling, integrates annotations from IEDB, dbSNP, and gnomAD, constructs personalized proteome databases, conducts HLA genotyping, applies filtering and visualization, and predicts peptide–MHC binding using mhcflurry and NetMHC.