Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

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...
Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Pre-eclampsia: Re-visiting pathophysiology, role of immune cells, biomarker identification and recent advances in its management.

Journal of reproductive immunology·2024
Same author

A π-π Bonding-Assisted Molecular-Wiring of Folded-Cytochrome <i>c</i> and Naphthoquinone and Its Electron-Relay-Based Bioelectrocatalytic H<sub>2</sub>O<sub>2</sub> Reduction Reaction Visualized by Redox-Competitive Scanning Electrochemical Microscopy.

Langmuir : the ACS journal of surfaces and colloids·2023
Same author

Biotechnology, Bioinformatics and Bioinformation in an Autobiography.

Bioinformation·2023
Same author

Pointless pondering on predatory publications.

Bioinformation·2023
Same author

Challenges and other linked features in promoting open access to bioinformation literature over about 2 decades.

Bioinformation·2023
Same author

From Anna University to America and to Agriculture.

Bioinformation·2021

Related Experiment Video

Updated: Jun 26, 2026

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

Class II HLA-peptide binding prediction using structural principles.

Arumugam Mohanapriya1, Sajitha Lulu, Rajarathinam Kayathri

  • 1School of Biotechnology, Chemical and Biomedical Engineering, Vellore Institute of Technology University, Tamil Nadu, India.

Human Immunology
|February 4, 2009
PubMed
Summary

This study developed a new model to predict human leukocyte antigen (HLA) class II peptide binding for vaccine and diagnostic development. While simple and rapid, the model shows weak prediction accuracy but offers broad HLA allele coverage for proteome-wide scanning.

More Related Videos

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

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Related Experiment Videos

Last Updated: Jun 26, 2026

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

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

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Area of Science:

  • Immunology
  • Computational Biology
  • Bioinformatics

Background:

  • Accurate prediction of human leukocyte antigen (HLA) class II peptide binding is crucial for designing vaccines and diagnostics targeting CD4+ T-cell immunity.
  • Unlike class I, HLA class II binding peptides exhibit an extended conformation, increasing binding combinations and influencing immune responses to pathogens.

Purpose of the Study:

  • To develop a prediction model for HLA class II peptide binding using structural data.
  • To assess the model's performance in predicting binders and non-binders for potential applications in epitope design and disease diagnostics.

Main Methods:

  • A manually curated dataset of 15 HLA class II-peptide (HLA II-p) structural complexes from the Protein Data Bank (PDB) was used.
  • Virtual binding pockets were created to accommodate HLA-II-specific peptides, with binding estimated using a quantitative matrix (Q matrix).
  • Model performance was evaluated through internal cross-validation and external testing on a dataset from the MHCBN database.

Main Results:

  • Internal cross-validation yielded 53% accuracy and 53% sensitivity.
  • External evaluation showed 53% accuracy, 70.8% specificity, 27.6% sensitivity, 62% positive predictive value (PPV), and 58% negative predictive value (NPV).
  • The model demonstrates a 62% PPV, indicating a reasonable success rate for predicted binders.

Conclusions:

  • The developed HLA class II peptide binding prediction model is simple, rapid, and covers a wide range of HLA alleles.
  • Despite weak prediction accuracy, the model's broad allele coverage makes it applicable for proteome-wide scanning, particularly in parasitic genomes.
  • The model's utility lies in its potential for large-scale screening, aiding in epitope discovery for vaccines and diagnostics.