Rankpep

Rankpep predicts and ranks peptide–MHC class I interactions to identify T-cell epitopes and support antigen-processing analysis.

Key Features:

• Position Specific Scoring Matrices (PSSMs): PSSMs are constructed from aligned peptides known to bind a particular MHC molecule to capture sequence similarity among binders.
• Ranking Algorithm: A search algorithm ranks all possible peptides derived from an input protein based on their PSSM coefficients.
• Predictive Power and Validation: Validated on proteins containing MHC class I K(b)- and D(b)-restricted T-cell epitopes, identifying over 80% of these epitopes within the top 2% of scoring peptides.
• Versatility: Provides a variety of MHCI-specific PSSMs and supports user-defined profiles for tailored predictions.

Scientific Applications:

• Immunology and vaccine development: Identification of candidate T-cell epitopes for vaccine antigen selection and immunological studies.
• T-cell epitope discovery: Prioritization and ranking of peptide candidates derived from protein sequences for experimental testing.
• Antigen processing analysis: Prediction of proteasomal cleavage sites at the C-terminal end of MHCI ligands to inform antigen processing studies.

Methodology:

PSSMs are built from aligned MHC-binding peptides, and a search algorithm ranks peptides derived from input proteins using PSSM coefficients.