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Updated: Jul 19, 2026

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

Published on: March 25, 2014

Methods and protocols for prediction of immunogenic epitopes.

Joo Chuan Tong¹, Tin Wee Tan, Shoba Ranganathan

¹Institute of Infocomm Research, Singapore.

Briefings in Bioinformatics

|November 2, 2006

Summary

Bioinformatics tools aid in identifying T-cell epitopes for cellular immunity. This review covers computational strategies and guidelines for predicting antigenic peptides, crucial for understanding peptide/MHC interactions.

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A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

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Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

Published on: March 24, 2017

Area of Science:

Immunology and Bioinformatics
Computational Biology
Molecular Interactions

Background:

Cellular immunity relies on T-cell recognition of peptide/major histocompatibility complex (MHC) complexes.
Identifying T-cell epitopes is critical for understanding immune responses.
Bioinformatics tools are increasingly used to study these interactions.

Purpose of the Study:

To review existing computational strategies for studying peptide/MHC interactions.
To identify key bioinformatics tools and methods relevant to peptide/MHC research.
To provide guidelines for predicting antigenic peptides using experimental data.

Main Methods:

Literature review of computational strategies.
Analysis of bioinformatics tools for peptide/MHC interaction studies.
Synthesis of guidelines for antigenic peptide prediction.

Main Results:

A comprehensive overview of current computational approaches for peptide/MHC analysis.
Identification and discussion of significant bioinformatics tools in the field.
Framework for predicting antigenic peptides informed by experimental data.

Conclusions:

Computational methods are essential for advancing the study of T-cell epitopes and peptide/MHC interactions.
The reviewed tools and guidelines can facilitate research in cellular immunity.
Integrating bioinformatics with experimental data enhances the prediction of antigenic peptides.