MHCPred

MHCPred predicts peptide binding affinities to MHC class I and II molecules and TAP and designs heteroclitic peptides to support T-cell epitope identification and vaccine and immunotherapy research.

Key Features:

• Expanded Allele Coverage: Includes models for human and mouse MHC molecules and supports 11 human HLA class I alleles, three human HLA class II alleles, and three mouse class I models.
• Incorporation of TAP Binding Model: Integrates a binding model for human TAP to enable prediction of peptide transport efficiency alongside MHC binding affinity.
• Heteroclitic Peptide Design: Designs modified heteroclitic peptides derived from natural epitopes to enhance immune responses for vaccine and immunotherapy research.
• Confidence Percentage Calculation: Calculates a confidence percentage for each predicted peptide binding affinity to assess prediction reliability.

Scientific Applications:

• T-cell Epitope Identification and Design: Identifies and designs T-cell epitopes for immunological research using predicted MHC and TAP interactions.
• Vaccine Development and Antigen Processing Studies: Supports vaccine development by predicting immune responses and modeling peptide transport via TAP to study antigen processing pathways.

Methodology:

Uses quantitative models to predict peptide binding affinities to MHC class I and II molecules and TAP, and removes previous computational constraints to provide flexible and comprehensive analysis.