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T Cell Activation and Clonal Selection

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T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...

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Updated: Mar 6, 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

T-Cell Epitope Prediction.

George N Konstantinou^1,2

¹Department of Allergy and Clinical Immunology, 424 General Military Training Hospital, 11 Eleftheriou Venizelou Street, Kalamaria, 55 133, Thessaloniki, Greece. gnkonstantinou@gmail.com.

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

|March 19, 2017

Summary

Computational methods can predict T-cell epitopes, identifying individuals genetically prone to allergies. These immunoinformatics tools analyze major histocompatibility complex (MHC) binding and T-cell receptor recognition for allergen prediction.

Keywords:

Allergen Allergy Antigen Bioinformatics In silico Peptide Prediction Processing T-Cell epitope

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Peptide:MHC Tetramer-based Enrichment of Epitope-specific T cells

Peptide:MHC Tetramer-based Enrichment of Epitope-specific T cells

Published on: October 22, 2012

Area of Science:

Immunology
Bioinformatics
Computational Biology

Background:

An epitope is a specific region of an antigen recognized by the immune system.
T-cell epitopes are peptide fragments presented by MHC molecules on antigen-presenting cells, recognized by T-cell receptors.
Genetic predisposition to allergies involves specific MHC molecules binding to allergens and T-cell recognition.

Purpose of the Study:

To explore the in silico prediction of T-cell epitopes for allergens.
To identify individuals genetically susceptible to allergic reactions.
To leverage computational techniques for understanding T-cell epitope interactions.

Main Methods:

Utilizing modern computational techniques based on mathematics and statistics.
Employing immunoinformatics databases to store and analyze experimental data.
Developing and applying software programs for T-cell epitope prediction.

Main Results:

Computational methods can predict potential allergen T-cell epitopes.
Variations in predictions are expected due to differing computational technique design principles.
Freeware software enables online access to T-cell epitope prediction methods.

Conclusions:

In silico analysis of MHC-peptide complexes can identify genetic predispositions to allergies.
Immunoinformatics tools are crucial for predicting allergen T-cell epitopes.
Accessible freeware facilitates the study and prediction of T-cell epitopes.