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Related Concept Videos

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...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
Protein Folding Quality Check in the RER01:29

Protein Folding Quality Check in the RER

ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
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...

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Related Experiment Video

Updated: May 26, 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

Protein complex prediction with RNSC.

Andrew D King1, Nataša Pržulj, Igor Jurisica

  • 1Department of Industrial Engineering and Operations Research, Columbia University, New York, NY, USA.

Methods in Molecular Biology (Clifton, N.J.)
|December 7, 2011
PubMed
Summary
This summary is machine-generated.

This study presents a two-step method using graph theory to predict protein complexes from protein-protein interaction (PPI) networks. The approach identifies clusters and filters them by size, density, and functional homogeneity for accurate complex prediction.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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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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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
14:58

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:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Graph theory analysis of biological networks reveals relationships between network topology and cellular functions.
  • Protein-protein interaction (PPI) networks are crucial for understanding biological processes, with their increasing size necessitating efficient analysis.
  • Identifying dense sub-networks and motifs in PPIs aids in discovering protein complexes and their assembly.

Purpose of the Study:

  • To describe a computational method for predicting protein complexes from PPI networks.
  • To identify biologically meaningful protein complexes by analyzing network topology and functional properties.
  • To develop an efficient approach for analyzing large and growing PPI networks.

Main Methods:

  • Utilized graph theory to analyze protein-protein interaction (PPI) networks.
  • Employed the Restricted Neighbourhood Search Clustering algorithm to partition PPI networks into candidate protein complex clusters.
  • Filtered candidate complexes based on minimum cluster size, interaction density, and functional homogeneity.

Main Results:

  • The described method effectively predicts protein complexes from PPI network data.
  • The two-step approach, involving clustering and filtering, successfully identifies biologically relevant protein groups.
  • Previous studies have validated the effectiveness of this protein complex prediction methodology.

Conclusions:

  • The proposed method provides a robust framework for predicting protein complexes using PPI network topology.
  • The integration of clustering and filtering criteria enhances the accuracy and biological relevance of predicted complexes.
  • This computational approach is valuable for advancing the understanding of cellular functions and biological processes through network analysis.