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Related Concept Videos

Antigens Involved in Adaptive Immunity01:26

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.
Complete Antigens
Complete antigens possess both immunogenicity and reactivity.
Antigen Processing Pathways01:31

Antigen Processing Pathways

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.
MHC Class I: Presenting Endogenous...
T Cell Activation and Clonal Selection01:22

T Cell Activation and Clonal Selection

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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Related Experiment Video

Updated: Jun 13, 2026

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
07:59

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

Published on: March 25, 2014

MHC class II epitope predictive algorithms.

Morten Nielsen1, Ole Lund, Søren Buus

  • 1Department of Systems Biology, Technical University of Denmark, Centre for Biological Sequence Analysis, Lyngby, Denmark. mniel@cbs.dtu.dk

Immunology
|April 23, 2010
PubMed
Summary
This summary is machine-generated.

Predicting peptide binding to major histocompatibility complex class II (MHC-II) molecules is crucial for understanding immune responses. Recent pan-specific methods improve prediction accuracy for diverse MHC-II alleles, aiding in immune system analysis.

More Related Videos

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis
09:32

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis

Published on: October 15, 2021

Related Experiment Videos

Last Updated: Jun 13, 2026

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
07:59

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

Published on: March 25, 2014

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis
09:32

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis

Published on: October 15, 2021

Area of Science:

  • Immunology
  • Computational Biology
  • Bioinformatics

Background:

  • Major histocompatibility complex class II (MHC-II) molecules present extracellular peptides to the immune system, crucial for detecting foreign pathogens.
  • Predicting peptide-MHC binding is vital for understanding immune responses, but MHC-II prediction accuracy lags behind MHC-I due to open-ended binding grooves.
  • Existing methods for MHC-II peptide binding prediction are limited, with few advancements beyond the TEPITOPE/ProPred approach.

Purpose of the Study:

  • To review and highlight recent advancements in developing predictive methods for peptide-MHC class II (MHC-II) binding.
  • To address the challenges in MHC-II peptide binding prediction, including the variable binding core and the vast diversity of MHC-II alleles.
  • To explore the utility of pan-specific methods and data-driven approaches in improving prediction accuracy and understanding MHC-II specificities.

Main Methods:

  • Review of existing and novel computational methods for predicting peptide binding to MHC-II molecules.
  • Inclusion of flanking residues in prediction algorithms to better define the binding motif.
  • Development and application of pan-specific prediction methods capable of generalizing to unseen MHC-II alleles.
  • Utilizing data-driven approaches over ab initio structure-based predictions for improved performance.

Main Results:

  • Pan-specific methods demonstrate improved accuracy in predicting peptide-MHC-II binding, even for alleles not present in training datasets.
  • Including flanking residues in predictions enhances the accuracy of MHC-II binding motif identification.
  • Data-driven methods significantly outperform structure-based ab initio predictions for MHC-II binding.
  • These methods enable the definition of MHC-II allele supertypes and the creation of visual tools like MHCMotifviewer for comparing allele specificities.

Conclusions:

  • Recent advancements, particularly pan-specific and data-driven methods, have significantly improved the prediction of peptide-MHC class II (MHC-II) binding.
  • These improved predictive capabilities are essential for understanding immune responses to pathogens and for vaccine design.
  • Tools like MHCMotifviewer facilitate the comparison of MHC-II allele specificities, advancing immunological research.