Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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-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...

You might also read

Related Articles

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

Sort by
Same author

Pro-regenerative fingerprints identified in a sub-population of adult mouse cardiomyocytes by integrative single-cell proteomics.

Genome biology·2026
Same author

A ginsenoside metabolite and its derivative target PRELID3B against lung cancer cells.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Peptide-to-Protein Data Aggregation Using Fisher's Method Improves Target Identification in Chemical Proteomics.

Analytical chemistry·2026
Same author

Above-Filter Digestion Proteomics Reveals Drug Targets and Localizes Ligand Binding Site.

Journal of proteome research·2026
Same author

Anti-Tumoral Treatment with Thioredoxin Reductase 1 Inhibitor Auranofin Fosters Regulatory T Cell and B16F10 Expansion in Mice.

Antioxidants (Basel, Switzerland)·2025
Same author

The Novel Achievements in Oncological Metabolic Radio-Therapy: Isotope Technologies, Targeted Theranostics, Translational Oncology Research.

Medical sciences (Basel, Switzerland)·2025
Same journal

Identification of Age-Associated Circulating Proteins and Lipids in 3800 Comorbidity-Enriched Older Adults from Japan-Based Cohorts Using Olink Assays and MRM Mass Spectrometry.

Journal of proteome research·2026
Same journal

Molecular Solution to the Paradox of Ancient Brain Preservation.

Journal of proteome research·2026
Same journal

From Method-Defined Signals to Reference Measurement Procedures: Two Decades of Mass Spectrometry-Based ProGRP Quantification.

Journal of proteome research·2026
Same journal

Proteomic Profiling of Extracellular Vesicle-Enriched Plasma Using Mag-Net for Biomarker Discovery in Pancreatic Ductal Adenocarcinoma.

Journal of proteome research·2026
Same journal

Computationally Efficient Bayesian Estimation of Graphical Networks for Omics Data.

Journal of proteome research·2026
Same journal

Hierarchy of MS-Based Evidence.

Journal of proteome research·2026
See all related articles

Related Experiment Video

Updated: Jun 3, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Drug target identification from protein dynamics using quantitative pathway analysis.

David M Good1, Roman A Zubarev

  • 1Chemistry I, Department of Molecular Biochemistry and Biophysics, Karolinska Institutet, Scheeles väg 2, 171 77 Stockholm, Sweden.

Journal of Proteome Research
|March 26, 2011
PubMed
Summary
This summary is machine-generated.

Quantitative pathway analysis (qPA) offers a powerful systems biology approach for drug target discovery. This method efficiently identifies potential drug targets from proteomics data, overcoming limitations of traditional dynamic proteomics techniques.

More Related Videos

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification
09:04

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Published on: August 17, 2015

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

Related Experiment Videos

Last Updated: Jun 3, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification
09:04

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Published on: August 17, 2015

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

Area of Science:

  • Proteomics
  • Systems Biology
  • Pharmacology

Background:

  • Dynamic proteomics enables identification of drug target proteins by monitoring protein responses over time.
  • Previous studies, like Cohen et al. (2008), demonstrated potential but faced limitations in equipment, labor, and data analysis.
  • Accurate drug target identification requires knowledge of target time-course evolution and direct monitoring.

Purpose of the Study:

  • To develop a quantitative pathway analysis (qPA) technique to overcome limitations in dynamic proteomics for drug target discovery.
  • To elucidate putative drug targets and other molecules of interest using well-annotated signaling pathways.
  • To demonstrate the efficacy of qPA in identifying known drug targets even without their explicit inclusion in the input data.

Main Methods:

  • Developed a quantitative pathway analysis (qPA) technique.
  • Employed well-annotated signaling pathways for analysis.
  • Utilized general assumptions and a limited number of time points (3 out of 144) from proteomics data.

Main Results:

  • qPA successfully identified the known camptothecin target, TOPI, among a small set of putative targets.
  • Identification of TOPI was achieved without TOPI being explicitly included in the input data.
  • The method demonstrated efficiency using fewer data points compared to traditional dynamic proteomics.

Conclusions:

  • Quantitative pathway analysis (qPA) is a promising technique for drug target discovery.
  • qPA effectively analyzes proteomics data by leveraging systems biology principles.
  • This approach addresses key limitations of conventional dynamic proteomics, enhancing efficiency and accuracy.