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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

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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.
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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.
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Protein Organization

Protein Organization

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Intrinsically Disordered Proteins

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Related Experiment Video

Updated: Mar 11, 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

BindML/BindML+: Detecting Protein-Protein Interaction Interface Propensity from Amino Acid Substitution Patterns.

Qing Wei¹, David La², Daisuke Kihara^3,4

¹Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA.

Methods in Molecular Biology (Clifton, N.J.)

|December 4, 2016

Summary

This summary is machine-generated.

Predicting protein-protein interaction sites is crucial for understanding protein function. New methods, BindML and BindML+, identify these sites using mutation patterns and can distinguish between permanent and transient interactions.

Keywords:

Bioinformatics Interface residues Protein binding site prediction Protein docking Protein interaction design Protein interaction propensity Protein-protein interaction

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Identifying Protein-protein Interaction Sites Using Peptide Arrays

Identifying Protein-protein Interaction Sites Using Peptide Arrays

Published on: November 18, 2014

Area of Science:

Structural biology
Bioinformatics
Computational biology

Background:

Protein-protein interactions (PPIs) are fundamental to cellular processes.
Accurate prediction of PPI sites aids in understanding protein function and complex formation.
Existing prediction methods often lack the ability to differentiate interaction types.

Purpose of the Study:

To introduce BindML and BindML+, novel computational methods for predicting protein-protein interaction sites.
To develop an interactive web server for visualizing PPI site predictions.
To enhance the prediction of PPI sites by distinguishing between permanent and transient interactions.

Main Methods:

BindML utilizes phylogenetic substitution models to identify mutation patterns in known protein-protein complexes.
BindML+ extends BindML to differentiate between permanent and transient PPI sites.
An interactive web server was developed for structural visualization of predicted PPI sites.

Main Results:

BindML effectively predicts protein-protein interaction sites based on evolutionary mutation patterns.
BindML+ successfully distinguishes between permanent and transient PPI sites.
The web server provides a user-friendly platform for analyzing PPI site predictions.

Conclusions:

BindML and BindML+ offer powerful tools for predicting and characterizing protein-protein interaction sites.
These methods can guide protein complex modeling and design.
The developed web server facilitates the application and visualization of these prediction tools.