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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,...
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...
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: Jul 4, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Using indirect protein-protein interactions for protein complex prediction.

Hon Nian Chua1, Kang Ning, Wing-Kin Sung

  • 1Graduate School of Integrated Sciences, National University of Singapore, Singapore. g0306417@nus.edu.sg

Journal of Bioinformatics and Computational Biology
|June 25, 2008
PubMed
Summary
This summary is machine-generated.

Predicting protein complexes is crucial for cell biology. This study enhances protein-protein interaction (PPI) networks using indirect interactions and topological weights, improving complex prediction accuracy, especially for novel protein complexes.

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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
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Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

Published on: November 12, 2012

Area of Science:

  • Computational Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Protein complexes are essential for cellular organization and function.
  • Accurate protein complex prediction from protein-protein interaction (PPI) networks aids biological discovery.
  • Existing PPI networks are often incomplete and noisy, challenging complex prediction.

Purpose of the Study:

  • To investigate the utility of level-2 interactions (indirect interactions) for protein complex prediction.
  • To develop a method for weighting and incorporating indirect interactions into PPI networks.
  • To propose a novel algorithm for identifying protein complexes in modified PPI networks.

Main Methods:

  • Utilized indirect interactions between level-2 neighbors to augment PPI networks.
  • Developed a topological weight (FS-Weight) to estimate functional association strength.
  • Introduced a novel partial clique merging algorithm for cluster formation.

Main Results:

  • Incorporating indirect interactions and topological weights improved the precision of existing clustering algorithms.
  • The proposed complex-finding algorithm demonstrated high performance on the modified networks.
  • The method effectively predicted novel protein complexes using only PPI network data.

Conclusions:

  • Indirect interactions and topological weighting are valuable for enhancing PPI networks.
  • The novel complex-finding algorithm offers an effective approach for protein complex prediction.
  • This method holds significant potential for discovering novel protein complexes without additional data.