IEDB-AR

IEDB-AR provides computational tools to predict and analyze B-cell and T-cell immune epitopes for studying antigen recognition and immune responses.

Key Features:

• B-cell epitope prediction: Two dedicated B-cell epitope prediction tools, including a newly introduced B-cell epitope prediction tool.
• T-cell epitope prediction: Four dedicated T-cell epitope prediction tools for identifying T-cell epitopes.
• Peptide:MHC binding prediction: New-generation peptide:MHC binding predictive algorithms with improved performance validated by independent laboratory studies and demonstrated success in an international peptide:MHC-I binding prediction competition.
• Epitope analysis: Two analysis tools supporting comprehensive evaluation of predicted epitopes.
• Homology mapping: Updated homology mapping tool that supports mapping of discontinuous epitopes onto three-dimensional structures.

Scientific Applications:

• Epitope prediction: Prediction of B-cell and T-cell immune epitopes for immunological research.
• Peptide:MHC binding assessment: Assessment of peptide:MHC-I binding to inform epitope selection and characterization.
• Structural epitope mapping: Mapping discontinuous epitopes onto three-dimensional structures to analyze spatial configuration and potential interactions with immune receptors.
• Algorithm benchmarking: Validation and benchmarking of predictive algorithms using independent laboratory studies and international competition results.

Methodology:

Implementation of B-cell and T-cell epitope prediction algorithms, new-generation peptide:MHC binding predictive algorithms, and homology mapping for mapping discontinuous epitopes onto three-dimensional structures.