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Related Concept Videos

Protein Networks02:26

Protein Networks

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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,...
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Proteomics01:33

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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.
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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...
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Functional Analysis of MS-Based Proteomics Data: From Protein Groups to Networks.

Marie Locard-Paulet1, Nadezhda T Doncheva2, John H Morris3

  • 1Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark; Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, Université Toulouse III-Paul Sabatier (UT3), Toulouse, France; Infrastructure nationale de protéomique, ProFI, FR 2048, Toulouse, France.

Molecular & Cellular Proteomics : MCP
|November 1, 2024
PubMed
Summary

Mass spectrometry-based proteomics can group similar proteins, impacting network analysis. Proteo Visualizer aids visualization and analysis of these protein groups in proteomics data.

Keywords:
BioinformaticsBiological databasesCytoscapeFunctional enrichmentMass spectrometryNetworksProtein groupsProteomicsSTRING

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Systems Biology

Background:

  • Mass spectrometry-based proteomics quantifies proteins, variants, and modifications.
  • Distinguishing proteins with similar sequences is challenging due to non-specific peptides, leading to protein grouping.
  • Protein groups can represent multiple genes, complicating downstream analysis.

Purpose of the Study:

  • To investigate the impact of multi-gene protein groups on Gene Ontology (GO) term enrichment and network analysis.
  • To introduce a tool for visualizing and analyzing bottom-up mass spectrometry-based proteomics data using protein groups.

Main Methods:

  • Analysis of GO-term enrichment with and without single-gene selection from protein groups.
  • Development and application of the Cytoscape app Proteo Visualizer.
  • Retrieval of protein interaction networks from STRING using protein groups as input.

Main Results:

  • Multi-gene protein groups have minimal impact on GO-term enrichment.
  • Selecting only one gene per group significantly affects network analysis outcomes.
  • Proteo Visualizer successfully visualizes and analyzes protein interaction networks from proteomics data.

Conclusions:

  • Careful consideration of protein grouping is necessary for accurate network analysis in proteomics.
  • Proteo Visualizer provides a valuable solution for analyzing complex proteomics datasets by integrating protein groups with interaction networks.
  • The tool facilitates robust network analysis of bottom-up mass spectrometry-based proteomics data.