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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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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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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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Updated: Feb 21, 2026

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling
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Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

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Identifying direct contacts between protein complex subunits from their conditional dependence in proteomics

Kevin Drew1, Christian L Müller2, Richard Bonneau2,3

  • 1Center for Systems and Synthetic Biology, Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, United States of America.

Plos Computational Biology
|October 13, 2017
PubMed
Summary

We developed a new computational method to predict direct protein-protein contacts within complexes using co-fractionation mass spectrometry (CF-MS) data. This approach improves structural modeling and understanding of protein complex function.

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Area of Science:

  • Proteomics
  • Structural Biology
  • Computational Biology

Background:

  • Determining protein complex 3D structure is crucial for understanding function and genetic variation.
  • Co-fractionation mass spectrometry (CF-MS) identifies protein complexes but struggles with direct subunit contact identification.
  • Existing correlation analysis of CF-MS data is limited in inferring direct physical contacts within complexes.

Purpose of the Study:

  • To develop a novel computational method for identifying direct protein-protein contacts within human protein complexes.
  • To improve the accuracy of predicting protein complex structures and subunit arrangements.
  • To provide a more complete 3D model of protein complexes, including recently discovered components.

Main Methods:

  • Learning a sparse conditional dependency graph from approximately 3,000 CF-MS experiments on human cell lines.
  • Applying the method to predict direct interactions and compare performance against correlation analysis.
  • Utilizing benchmark datasets of protein complexes with solved 3D structures.

Main Results:

  • Substantial performance gains in estimating direct protein-protein interactions compared to traditional correlation analysis.
  • Successful prediction of 3D arrangements for complexes lacking known structures, such as the exocyst and tRNA multi-synthetase complex.
  • Established evidence for the structural position of GON7/C14ORF142 within the human EKC/KEOPS complex, refining its 3D model.

Conclusions:

  • Direct contact prediction from CF-MS data offers significant advantages over correlation analysis for structural insights.
  • The method provides valuable, easily calculable structural information for large-scale protein complex mapping.
  • This approach is broadly applicable across organisms as CF-MS datasets expand, enhancing protein complex studies.