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Antigens Involved in Adaptive Immunity

Antigens Involved in Adaptive Immunity

An antigen is any substance the immune system identifies as foreign and potentially harmful to the body, prompting an immune response. Antigens have two functional properties: immunogenicity and reactivity. Immunogenicity is the ability of an antigen to stimulate a specific immune response. At the same time, reactivity describes the antigen's ability to react with the cells and antibodies produced in response to it.
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Complete antigens possess both immunogenicity and reactivity.

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MHC molecules are key players in the immune response, enabling T cells to recognize and respond to specific antigens. They are present on the surface of all nucleated cells in the body and are instrumental in presenting antigens to T cells and activating them. T cells recognize the MHC-antigen complex and initiate an immune response. MHC class I and MHC class II are two main types of MHC molecules, each associated with a distinct antigen processing pathway.
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Conserved Binding Sites

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Updated: May 8, 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

Structure-based prediction of Major Histocompatibility Complex (MHC) epitopes.

Andrew J Bordner¹

¹Mayo Clinic, Scottsdale, AZ, USA.

Methods in Molecular Biology (Clifton, N.J.)

|August 22, 2013

Summary

Computational methods predict epitopes for MHC proteins to aid research. Structure-based approaches offer advantages over sequence-based methods for diverse MHC types, guiding experiments and biomedical applications.

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

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Stability and Structure of Bat Major Histocompatibility Complex Class I with Heterologous β2-Microglobulin

Stability and Structure of Bat Major Histocompatibility Complex Class I with Heterologous β₂-Microglobulin

Published on: March 10, 2021

Area of Science:

Immunoinformatics
Computational Biology
Molecular Immunology

Background:

Major Histocompatibility Complex (MHC) proteins exhibit vast diversity.
Peptide epitopes are crucial for immune recognition but experimentally challenging to identify.
Computational epitope prediction is essential to complement limited experimental data.

Purpose of the Study:

To describe structure-based computational methods for predicting epitopes.
To compare structure-based and sequence-based epitope prediction strategies.
To highlight the utility of these methods in guiding experimental research and biomedical applications.

Main Methods:

Detailed description of previously developed structure-based epitope prediction methods.
Application to both class I and class II MHC proteins.
Discussion of method advantages, disadvantages, and performance evaluation.

Main Results:

Structure-based methods can predict epitopes across diverse MHC types.
These methods offer an alternative to sequence-based approaches with distinct binding propensities.
The described methods provide a framework for enhancing epitope discovery.

Conclusions:

Structure-based epitope prediction is a valuable tool for immunoinformatics.
These computational approaches supplement experimental epitope mapping.
The methods discussed have significant potential for biomedical applications, including vaccine design and diagnostics.