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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,...
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...

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Related Experiment Video

Updated: Jul 8, 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

Computational methods for predicting protein-protein interactions.

Sylvain Pitre1, Md Alamgir, James R Green

  • 1School of Computer Science, Carleton University, 5304 Herzberg Building, 1125 Colonel By Drive, K1S 5B6, Ottawa, Ontario, Canada.

Advances in Biochemical Engineering/Biotechnology
|January 19, 2008
PubMed
Summary

Computational methods predict protein-protein interactions (PPIs) efficiently, overcoming experimental limitations. This review covers various computational PPI prediction techniques, including PIPE, and discusses their limitations.

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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

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Last Updated: Jul 8, 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

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells
08:38

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells

Published on: March 3, 2015

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

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Protein-protein interactions (PPIs) are fundamental to cellular processes.
  • Experimental PPI discovery methods are costly and yield inconsistent results.
  • Computational approaches offer a scalable alternative for PPI data analysis.

Purpose of the Study:

  • To review computational techniques for predicting protein-protein interactions (PPIs).
  • To introduce the PIPE computational method for PPI prediction.
  • To compare computational methods with conventional large-scale PPI prediction approaches.

Main Methods:

  • Focus on computational prediction of PPIs.
  • Review of various computational techniques, including the PIPE method.
  • Brief discussion of conventional large-scale PPI prediction strategies.

Main Results:

  • Computational techniques are valuable for collecting, indexing, validating, and analyzing PPI data.
  • The PIPE method is presented as a novel computational tool for PPI prediction.
  • Comparison highlights the advantages and disadvantages of different PPI prediction strategies.

Conclusions:

  • Computational PPI prediction methods offer efficiency and scalability.
  • Both experimental and computational approaches have limitations in determining PPIs.
  • Further development is needed to refine computational and experimental PPI determination.