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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...

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Related Experiment Video

Updated: May 28, 2026

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

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Published on: October 15, 2021

NetMHCcons: a consensus method for the major histocompatibility complex class I predictions.

Edita Karosiene1, Claus Lundegaard, Ole Lund

  • 1Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Building 208, Kemitorvet, Lyngby, 2800, Denmark. edita@cbs.dtu.dk

Immunogenetics
|October 20, 2011
PubMed
Summary
This summary is machine-generated.

Predicting peptide binding to major histocompatibility complex (MHC) molecules is crucial for cell-mediated immunity. This study analyzes combinations of prediction methods, finding NetMHCpan best for uncharacterized alleles and specific combinations for well-characterized ones.

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Area of Science:

  • Immunology
  • Computational Biology
  • Bioinformatics

Background:

  • Major histocompatibility complex (MHC) molecules present peptides for T-cell recognition, a critical process in cell-mediated immunity.
  • Numerous in silico methods exist for predicting peptide binding to MHC class I molecules, but their accuracy varies.
  • Consensus methods, combining multiple prediction tools, generally offer improved accuracy over individual methods.

Purpose of the Study:

  • To analyze combinations of state-of-the-art MHC-peptide binding prediction methods.
  • To guide non-expert users in selecting the most suitable prediction method for specific MHC molecules.
  • To develop an improved consensus method for accurate MHC-peptide binding predictions.

Main Methods:

  • In-depth analysis of three leading MHC-peptide binding prediction methods: NetMHC, NetMHCpan, and PickPocket.
  • Evaluation of different combinations of these methods.
  • Assessment of prediction performance based on the availability and characteristics of training data for specific MHC alleles.

Main Results:

  • A simple combination of NetMHC and NetMHCpan performs best for well-characterized MHC alleles (≥50 data points, ≥10 binders).
  • NetMHCpan is the optimal predictor for alleles not included in the training set or with limited data.
  • For alleles with distant neighbors in the training set, a combination of NetMHCpan and PickPocket shows superior performance.
  • The developed consensus method, NetMHCcons, provides accurate predictions for any MHC molecule and is publicly available.

Conclusions:

  • The optimal MHC-peptide binding prediction strategy depends on the specific MHC allele and available training data.
  • Consensus methods, particularly NetMHCcons, offer a robust and user-friendly solution for accurate MHC-peptide binding predictions.
  • This work simplifies the selection of prediction tools, enhancing research in immunology and vaccine development.