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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:

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

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Published on: March 25, 2014

Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method.

Morten Nielsen1, Claus Lundegaard, Ole Lund

  • 1Center for Biological Sequence Analysis, BioCentrum-DTU, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk

BMC Bioinformatics
|July 5, 2007
PubMed
Summary

A new method, SMM-align, accurately predicts peptide:MHC class II binding affinities, outperforming existing tools for rational vaccine design and epitope discovery. This advancement aids in identifying foreign peptides for T helper cell activation.

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Area of Science:

  • Immunology
  • Bioinformatics
  • Computational Biology

Background:

  • Antigen-presenting cells (APCs) present extracellular peptides via MHC class II molecules to T helper cells.
  • Accurate prediction of peptide:MHC class II interactions is crucial for rational vaccine design and epitope discovery.
  • The open-ended binding groove of MHC class II necessitates precise peptide alignment for motif identification.

Purpose of the Study:

  • To introduce SMM-align, a novel stabilization matrix alignment method for predicting peptide:MHC class II binding affinities.
  • To validate the predictive performance of SMM-align on a large MHC class II benchmark dataset.
  • To compare SMM-align with existing prediction methods.

Main Methods:

  • Development and application of the SMM-align method for direct prediction of peptide:MHC binding affinities.
  • Validation using a benchmark dataset covering 14 HLA-DR and 3 mouse H2-IA alleles.
  • Analysis of peptide flanking residues (PFR) and binding register optimization.

Main Results:

  • SMM-align demonstrated superior predictive performance compared to Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred.
  • Incorporating peptide length directly may lead to over-fitting; favoring a minimum PFR length of two amino acids improves prediction.
  • Discrepancies in binding motifs were observed between SMM-align and TEPITOPE, with SMM-align identifying preferences for hydrophobic/neutral amino acids at anchors for DRB1*1302.

Conclusions:

  • SMM-align outperforms current state-of-the-art MHC class II prediction methods.
  • The method's ability to predict quantitative binding affinities makes it suitable for rational epitope discovery.
  • The method and dataset are publicly available, supporting further research in MHC class II binding prediction.