Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Protein Networks

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,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

The life history of recessive deleterious alleles as seen through the eyes of a honey bee (Apis mellifera).

Molecular biology and evolution·2026

Same author

Co-culturing hiPSC-cardiomyocytes and cardiac fibroblasts enhances engineered heart tissue structure and function.

Stem cells translational medicine·2026

Same author

Enzymatic Deacetylation as a Selective Strategy for <i>O</i>-GlcNAc Identification.

Analytical chemistry·2026

Same author

Liposomal lipid nanoparticles containing dihydrosphingomyelin exhibit improved stability and extended hepatic and extrahepatic transfection.

Journal of controlled release : official journal of the Controlled Release Society·2026

Same author

European foulbrood disease and protein supplementation in honey bee (<i>Apis mellifera</i> L.) colonies pollinating highbush blueberries in British Columbia.

PeerJ·2026

Same author

Ribosome biogenesis mediates the translational increase of nonoptimal codon transcripts during IFN-β stimulation.

Canadian journal of microbiology·2026

Same journal

Efficient evidence-based genome annotation with EviAnn.

Nature methods·2026

Same journal

ClairS: a deep-learning method for long-read tumor-normal pair somatic small variant calling.

Nature methods·2026

Same journal

RNAbpFlow: base pair-augmented SE(3) flow matching for conditional RNA 3D structure generation.

Nature methods·2026

Same journal

Spatio-DARLIN enables robust and efficient in situ lineage tracing in mice at single-cell resolution.

Nature methods·2026

Same journal

EasyGrid: a versatile platform for automated cryo-EM sample preparation and quality control.

Nature methods·2026

Same journal

Cloud-based microscope enables live neuroimaging for 24 h and beyond with worldwide access.

Nature methods·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 19, 2026

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Published on: November 17, 2019

A high-throughput approach for measuring temporal changes in the interactome.

Anders R Kristensen¹, Joerg Gsponer, Leonard J Foster

¹Department of Biochemistry & Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada.

|August 7, 2012

Summary

This summary is machine-generated.

Researchers mapped 291 protein complexes using quantitative proteomics and size-exclusion chromatography. This novel method accurately profiles interactomes without needing protein overexpression or tagging, revealing dynamic cellular interactions.

More Related Videos

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Published on: August 2, 2015

Related Experiment Videos

Last Updated: May 19, 2026

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Published on: November 17, 2019

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Published on: August 2, 2015

Area of Science:

Proteomics and Systems Biology
Molecular Interactions and Complex Mapping

Background:

Traditional methods like affinity purification-mass spectrometry (AP-MS) and yeast two-hybrid lack stoichiometric and temporal data.
Existing techniques often require protein overexpression or tagging, which can introduce artifacts.

Purpose of the Study:

To develop a method for mapping protein interactomes with stoichiometric and temporal information.
To provide an alternative to AP-MS and yeast two-hybrid that is less labor-intensive and avoids overexpression/tagging.

Main Methods:

Integration of quantitative proteomics with size-exclusion chromatography.
Utilizing triplex labeling for monitoring interactome dynamics.

Main Results:

Successfully mapped 291 coeluting protein complexes.
Achieved interactome mapping depth and accuracy comparable to AP-MS.
Demonstrated the ability to monitor interactome rearrangements.

Conclusions:

The combined quantitative proteomics and size-exclusion chromatography method offers a powerful tool for interactome analysis.
This approach provides a more efficient and less invasive way to study protein complex stoichiometry and dynamics.
Enables deeper insights into cellular organization and function through dynamic interactome mapping.