Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Ligand Binding Sites

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 Interfaces

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...

Conserved Binding Sites

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...

You might also read

Related Articles

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

Sort by

Same author

Human NKT10 cells are enriched in cord-derived invariant natural killer T cells and mediate immune-regulation in a xenogeneic graft-versus-host disease model.

Frontiers in immunology·2026

Same author

Mapping the TCR landscape: computational tools empowering translational immunology and therapy design.

Journal for immunotherapy of cancer·2026

Same author

FOXM1-Specific TCR-Engineered T Cells Target Non-Small Cell Lung Cancer.

Cancer immunology research·2026

Same author

STEGG: Structural TCR-pMHC ensemble generator and gallery.

Journal of molecular biology·2026

Same author

STAG-LLM: Predicting TCR-pHLA binding with protein language models and computationally generated 3D structures.

Computational and structural biotechnology journal·2026

Same author

3DSeqCheck: A Web-based Tool for Verifying Sequence Consistency Between a 3D Structure File and the Corresponding UniProt Entry.

Journal of molecular biology·2026

Same journal

Turbulent flow in a vortex separator with a directed pipe inlet.

Scientific reports·2026

Same journal

Systematic characteristic evaluation of clay-based cementitious material derived from calcium carbide residue and waste tile powder.

Scientific reports·2026

Same journal

Retraction Note: Improvement of a rapid diagnostic application of monoclonal antibodies against avian influenza H7 subtype virus using Europium nanoparticles.

Scientific reports·2026

Same journal

Applying large language models to spam detection in the Kazakh low-resource language setting.

Scientific reports·2026

Same journal

An open-source 3D printing system enabling in-situ freeze-thaw processing of hydrogels.

Scientific reports·2026

Same journal

An enhanced EfficientNet framework for automated waste classification using cosine annealing and label smoothing.

Scientific reports·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 29, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

3pHLA-score improves structure-based peptide-HLA binding affinity prediction.

Anja Conev¹, Didier Devaurs², Mauricio Menegatti Rigo¹

¹Department of Computer Science, Rice University, Houston, 77005, USA.

Scientific Reports

|June 24, 2022

Summary

This summary is machine-generated.

This study introduces a new machine learning method, 3pHLA-score, for predicting peptide-Human Leukocyte Antigen (HLA) binding affinity using structural data. This approach significantly improves accuracy for identifying potential vaccine targets.

More Related Videos

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

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

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: Apr 29, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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

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

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
Structural Biology

Background:

Peptide-Human Leukocyte Antigen (HLA) binding is essential for immune responses and crucial for vaccine development.
Current computational methods for predicting peptide-HLA binding affinity often rely solely on sequence data, limiting their effectiveness.
Structure-based data offers a promising avenue to overcome the limitations of sequence-based approaches.

Purpose of the Study:

To develop a novel machine learning (ML) protocol for predicting peptide-HLA binding affinity using structure-based data.
To engineer input features by decoupling energy contributions at different peptide residue positions, creating a per-peptide-position protocol.
To introduce and evaluate a new scoring function, 3pHLA-score, based on this novel protocol.

Main Methods:

Developed a novel structure-based machine learning protocol for peptide-HLA binding affinity prediction.
Engineered input features by decoupling energy contributions at individual peptide residue positions.
Utilized Rosetta's ref2015 scoring function as a baseline to develop the 3pHLA-score model.

Main Results:

The novel per-peptide-position protocol significantly improved the area under the precision-recall curve from 0.82 to 0.99 compared to standard training protocols.
The developed 3pHLA-score outperformed established scoring functions, including AutoDock4, Vina, Dope, Vinardo, FoldX, and GradDock, in structural virtual screening.
Demonstrated the efficacy of structure-based data in enhancing the accuracy of peptide-HLA binding affinity predictions.

Conclusions:

The proposed structure-based ML protocol and 3pHLA-score represent a significant advancement in predicting peptide-HLA binding affinity.
This work moves structure-based methods closer to practical application in epitope discovery pipelines.
The findings could accelerate the development of novel cancer and viral vaccines by improving target identification.