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

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...

Protein-Protein Interfaces

Protein-Protein Interfaces

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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...

Conserved Binding Sites

Conserved Binding Sites

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...

You might also read

Related Articles

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

Sort by

Same author

PDA-MutPred: Reliable prediction of binding affinity change upon mutation in protein-DNA complexes.

International journal of biological macromolecules·2026

Same author

Classification of driver and passenger mutations in different cancer types using deep neural networks.

Bioinformatics advances·2026

Same author

Investigating protein aggregation in protein-carbohydrate interfaces using sequence and structural features.

Biochimica et biophysica acta. Proteins and proteomics·2026

Same author

Integrating Sequence, Structure, and Graph-based Features for Elucidating the Stability of Thermophilic Proteins.

Journal of molecular biology·2025

Same author

Herpes Simplex Virus Glycoprotein D Associated with Aβ<sub>1-42</sub> Tetramers Mediates Neurotoxicity by Perturbing Neuronal Membrane Integrity: A Molecular Dynamics Simulation.

ACS chemical neuroscience·2025

Same author

Computational design of protein complexes: influence of binding affinity.

Chemical communications (Cambridge, England)·2025

Search research articles

Related Experiment Video

Updated: Apr 25, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

Protein-protein binding affinity prediction from amino acid sequence.

K Yugandhar¹, M Michael Gromiha¹

¹Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai-600036, Tamil Nadu, India.

Bioinformatics (Oxford, England)

|August 31, 2014

Summary

Predicting protein-protein binding affinity is crucial. This study classifies complexes by function and binding site residues, developing accurate sequence-based regression models for improved predictions.

More Related Videos

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

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Related Experiment Videos

Last Updated: Apr 25, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

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

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

Biochemistry
Computational Biology
Bioinformatics

Background:

Protein-protein interactions (PPIs) are fundamental to biological processes.
Predicting binding affinity aids in understanding molecular recognition and PPI networks.

Purpose of the Study:

To develop a novel methodology for predicting protein-protein complex binding affinity using sequence-based features.
To investigate the relationship between binding affinity and sequence-derived properties.

Main Methods:

Collected experimental binding affinity data for 135 protein-protein complexes.
Analyzed correlations between binding affinity and 642 sequence-based properties.
Classified complexes based on function and predicted binding site residue percentages.
Developed regression models for classified complex groups using selected properties.

Main Results:

Overall correlation between binding affinity and sequence properties was initially poor.
Affinity determinants varied based on complex type, function, molecular weight, and binding site residues.
Classified regression models achieved high prediction accuracy, with correlations ranging from 0.739 to 0.992 (jack-knife test).

Conclusions:

A novel, biologically significant approach to protein-protein binding affinity prediction was developed.
Classifying complexes by function and binding site characteristics improves prediction accuracy.
Sequence-based features, when applied within specific complex classes, are effective for affinity prediction.