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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: May 9, 2026

Peptide-based Identification of Functional Motifs and their Binding Partners
14:28

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

Counting motifs in the human interactome.

Ngoc Hieu Tran1, Kwok Pui Choi, Louxin Zhang

  • 1Department of Statistics and Applied Probability, National University of Singapore NUS, Singapore 117546, Singapore.

Nature Communications
|August 7, 2013
PubMed
Summary

We developed a method to accurately count biological network motifs, even with incomplete data. This reveals significant differences in motif abundance across species and cell types.

Area of Science:

  • Systems Biology
  • Network Science
  • Bioinformatics

Background:

  • Biological networks, such as protein-protein interaction networks and gene regulatory networks, are crucial for understanding cellular functions.
  • Over-represented small motifs within these networks often represent fundamental functional units.
  • Quantifying motif occurrences is essential for understanding network organization and biological processes, but is challenging with noisy biological data.

Purpose of the Study:

  • To develop and validate an accurate computational method for estimating motif occurrences in biological networks, particularly from incomplete and noisy datasets.
  • To apply this method to compare motif frequencies across different biological systems, including eukaryotic interactomes and transcription factor regulatory networks.
  • To investigate the relationships between the occurrences of different types of motifs within specific biological networks.

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

Published on: March 3, 2015

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Related Experiment Videos

Last Updated: May 9, 2026

Peptide-based Identification of Functional Motifs and their Binding Partners
14:28

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

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

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Main Methods:

  • Development of a novel statistical method for robust motif counting in large-scale biological networks.
  • Application of the developed method to analyze eukaryotic interactomes (e.g., human and yeast) and cell-specific transcription factor regulatory networks.
  • Comparative analysis of motif abundance and correlation between different motif types (e.g., triads and quadriad motifs).

Main Results:

  • The human interactome contains approximately 194 times more triangles than the Saccharomyces cerevisiae interactome.
  • A significant positive linear correlation was observed between the occurrences of triad and quadriad motifs in human cell-specific transcription factor regulatory networks.
  • The developed method demonstrated high accuracy and generalizability across different network types and data qualities.

Conclusions:

  • The proposed method provides a powerful and accurate approach for quantifying motif occurrences in biological networks, overcoming limitations of noisy and incomplete data.
  • Comparative analyses reveal substantial differences in motif composition between species and network types, offering insights into evolutionary and functional divergence.
  • The findings highlight the utility of motif analysis in understanding the structure and function of complex biological systems.