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Related Concept Videos

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 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 Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

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.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

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.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...

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Updated: May 11, 2026

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

Reconstituting protein interaction networks using parameter-dependent domain-domain interactions.

Vesna Memišević1, Anders Wallqvist, Jaques Reifman

  • 1Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA.

BMC Bioinformatics
|May 9, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces computational methods to improve the analysis of protein-protein interactions (PPIs) by better annotating protein domains and identifying key domain-domain interactions (DDIs). The new approach enhances the accuracy and scope of understanding cellular functions and diseases.

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Related Experiment Videos

Last Updated: May 11, 2026

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells
08:38

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Published on: March 3, 2015

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Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
07:57

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Protein-protein interactions (PPIs) are mediated by domain-domain interactions (DDIs).
  • Experimental DDI data is limited, posing challenges for understanding PPIs, cellular function, and disease.
  • Current methods struggle to identify specific DDIs responsible for PPIs without structural data.

Purpose of the Study:

  • To develop a computational strategy for merging domain annotation data from multiple databases.
  • To introduce a novel method (PADDS) for extracting a minimal set of DDIs from PPIs, minimizing false positives.
  • To improve the understanding of PPIs, cellular function, disease mechanisms, and evolution through enhanced DDI analysis.

Main Methods:

  • A novel computational strategy was developed to merge domain annotation data from six databases for yeast.
  • The parameter-dependent DDI selection (PADDS) method was introduced to identify key DDIs from PPIs.
  • PADDS was applied to PPIs from multiple organisms to extract experimentally detected DDIs.

Main Results:

  • Merging domain annotations increased the average number of domains per protein from 1.05 to 2.44.
  • PADDS extracted 27% more experimentally detected DDIs compared to existing computational approaches.
  • The study demonstrated that PADDS is not biased towards DDIs with extreme occurrence counts.

Conclusions:

  • A method for merging domain annotation data ensures comprehensive and consistent annotations.
  • PADDS effectively extracts a small, representative set of DDIs from PPIs, outperforming existing methods.
  • Annotation density influences DDI characteristics, but true biological false positives limit complete DDI assignment.