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Related Concept Videos

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...
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...
Protein Networks02:26

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 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 Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...

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Related Experiment Video

Updated: Jun 28, 2026

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

A simple and efficient method for predicting protein-protein interaction sites.

R H Higa1, C L Tozzi

  • 1Faculdade de Engenharia Elétrica e de Computação, Universidade Estadual de Campinas, Campinas, SP, Brasil. roberto@cnptia.embrapa.br

Genetics and Molecular Research : GMR
|October 25, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a simple yet effective method for predicting protein-protein interaction sites. The new approach leverages amino acid composition to identify key residues, achieving a high success rate of 82.1%.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Identifying Protein-protein Interaction Sites Using Peptide Arrays
07:44

Identifying Protein-protein Interaction Sites Using Peptide Arrays

Published on: November 18, 2014

Related Experiment Videos

Last Updated: Jun 28, 2026

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

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Identifying Protein-protein Interaction Sites Using Peptide Arrays
07:44

Identifying Protein-protein Interaction Sites Using Peptide Arrays

Published on: November 18, 2014

Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein science

Background:

  • Predicting protein-protein interaction (PPI) sites computationally typically yields 70-80% accuracy.
  • Experimental data suggests only a subset of residues at the core of interaction sites are crucial for binding.
  • Amino acid composition analysis reveals distinct patterns for residues at interaction sites versus other surface residues.

Purpose of the Study:

  • To develop and evaluate a straightforward computational method for predicting protein-protein interaction sites.
  • To leverage the differential amino acid composition of interaction site residues for improved prediction accuracy.

Main Methods:

  • Implementation of a prediction method based on the distinct amino acid composition of interaction site residues.
  • Evaluation of the method's performance using established datasets and performance metrics.
  • Comparison with existing computational methods for predicting PPI sites.

Main Results:

  • The developed method achieved a success rate of 82.1% in predicting interaction site residues.
  • This performance is competitive with, and slightly exceeds, other state-of-the-art methods on the same dataset.
  • The findings validate the utility of focusing on amino acid composition at the core of interaction sites.

Conclusions:

  • A simple method exploiting amino acid composition effectively predicts protein-protein interaction sites.
  • This approach offers a competitive alternative to more complex computational prediction strategies.
  • The study highlights the importance of residue composition in understanding and predicting protein binding interfaces.