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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.
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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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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.
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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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Conservation of Protein Domains Over Different Proteins02:26

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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling
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PCprophet: a framework for protein complex prediction and differential analysis using proteomic data.

Andrea Fossati1,2,3,4, Chen Li5,6, Federico Uliana1

  • 1Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.

Nature Methods
|April 16, 2021
PubMed
Summary
This summary is machine-generated.

PCprophet is a new toolkit for analyzing protein complexes using size exclusion chromatography-sequential window acquisition of all theoretical mass spectrometry (SEC-SWATH-MS) data. It accurately predicts protein complexes and their dynamic changes across conditions.

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Area of Science:

  • Proteomics
  • Systems Biology
  • Biochemistry

Background:

  • Analyzing protein complexes and their dynamics across conditions is challenging.
  • Existing methods often rely on protein-protein interaction inference for cofractionation data interpretation.
  • Systematic analysis of protein complex rearrangements requires advanced computational tools.

Purpose of the Study:

  • To introduce PCprophet, a novel toolkit for predicting protein complexes and their alterations.
  • To leverage size exclusion chromatography-sequential window acquisition of all theoretical mass spectrometry (SEC-SWATH-MS) data for complex analysis.
  • To provide a robust method for characterizing dynamic changes in protein complexes.

Main Methods:

  • Utilizing SEC-SWATH-MS data to predict protein complex composition.
  • Developing a Bayesian approach to analyze altered protein-protein interactions.
  • Implementing PCprophet with command-line and graphical interfaces for broad applicability.

Main Results:

  • PCprophet demonstrates superior performance compared to current state-of-the-art methods.
  • The toolkit accurately predicts protein complexes and tracks their changes across experimental conditions.
  • The Bayesian approach effectively analyzes condition-specific protein-protein interactions.

Conclusions:

  • PCprophet offers a powerful and versatile solution for analyzing protein complex dynamics.
  • The toolkit facilitates the detection and quantitative tracking of protein complexes and their physiological variations.
  • PCprophet is applicable to various cofractionation MS datasets, enhancing proteomic research.