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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-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...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

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Related Experiment Video

Updated: Jun 6, 2026

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
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A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

In silico protein interaction analysis using the global proteome machine database.

Cheng-Cheng Zhang1, Jason C Rogalski, Daniel M Evans

  • 1The Biomedical Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.

Journal of Proteome Research
|November 12, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces an in silico tool using the Global Proteome Machine database to analyze protein-protein interactions. The method successfully identified known and candidate interactions across various protein complexes, demonstrating its utility in network analysis.

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Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics
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Area of Science:

  • Proteomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Protein-protein interactions are crucial for cellular functions.
  • Proteomic data repositories are valuable resources for studying these interactions.
  • Existing methods for identifying protein interactions can be resource-intensive.

Purpose of the Study:

  • To develop and validate an in silico tool for analyzing protein-protein interactions using a large proteomic database.
  • To demonstrate the tool's capability in identifying protein interaction partners and networks.

Main Methods:

  • Utilized the Global Proteome Machine database (GPMDB), a curated repository of tandem mass spectrometry data.
  • Developed an in silico analysis method for predicting protein-protein interactions.
  • Applied the method to human histone proteins, proteasome subunits, and integrin complexes.

Main Results:

  • Successfully identified interaction partners for human histone proteins, including those forming the histone octameric complex.
  • Identified all subunits of the human 20S proteasome core particle.
  • Discovered a 28-protein network for integrin αIIb and β3, involved in platelet activation, and validated interactions for integrin β1.

Conclusions:

  • In silico protein interaction analysis is a novel and effective tool for identifying known and candidate protein-protein interactions.
  • The method aids in uncovering proteins with shared functions within complex biological networks.
  • This approach offers a powerful computational strategy for advancing proteomic research.