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Related Concept Videos

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-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 Organization01:24

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence.
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...

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Related Experiment Video

Updated: Jul 6, 2026

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling
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Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Published on: November 17, 2019

Fitting a geometric graph to a protein-protein interaction network.

Desmond J Higham1, Marija Rasajski, Natasa Przulj

  • 1Department of Mathematics, University of Strathclyde, Glasgow G1 1XH, UK.

Bioinformatics (Oxford, England)
|March 18, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a novel algorithm to embed protein-protein interaction (PPI) networks into Euclidean space, revealing a significant geometric structure. The findings support the hypothesis that PPI networks possess inherent geometric properties, aiding in understanding biological function and evolution.

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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

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Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling
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Published on: November 17, 2019

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

Area of Science:

  • Systems Biology and Bioinformatics
  • Network Science
  • Computational Biology

Background:

  • Protein-protein interaction (PPI) networks are crucial for understanding biological function and evolution.
  • Geometric random graphs have been proposed as a model for PPI networks, where connectivity relates to proximity in a metric space.
  • A key challenge is to computationally test and validate the geometric properties of PPI networks.

Purpose of the Study:

  • To develop and validate an algorithm for embedding protein-protein interaction networks into low-dimensional Euclidean space.
  • To test the hypothesis that PPI networks exhibit geometric structure, where connectivity reflects Euclidean proximity.
  • To assess the effectiveness of the embedding using Receiver Operator Characteristic (ROC) curve analysis.

Main Methods:

  • Developed a network embedding algorithm based on multi-dimensional scaling.
  • Utilized the square root of path length in the network as the Euclidean distance.
  • The algorithm exploits sparsity for computational efficiency, with O(N^2) complexity.

Main Results:

  • The algorithm successfully identified geometric structure in artificial networks, even with added noise.
  • Analysis of 19 PPI networks revealed the presence of geometric effects, with 2D Euclidean space often sufficient.
  • A high-confidence yeast PPI network showed strong geometric structure (ROC area of 0.89), similar to noisy geometric networks.

Conclusions:

  • The results provide strong support for the hypothesis that protein-protein interaction networks possess an underlying geometric structure.
  • The developed embedding algorithm is effective in detecting and quantifying this geometric property.
  • This geometric perspective offers new insights into the organization and evolution of biological networks.