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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...
Protein-Drug Binding: Mechanism and Kinetics01:16

Protein-Drug Binding: Mechanism and Kinetics

Protein-drug binding refers to the interaction between drugs and proteins within the body. This binding process can occur intracellularly, involving drug interactions with enzymes or receptors within cells, or extracellularly, involving plasma proteins in the blood.
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Related Experiment Video

Updated: May 17, 2026

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
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Published on: August 21, 2019

Deciphering complex protein interaction kinetics using Interaction Map.

Danièle Altschuh1, Hanna Björkelund, John Strandgård

  • 1Biotechnologie et signalisation cellulaire, Université de Strasbourg, CNRS, Irebs-ESBS, Boulevard Sébastien Brant, 67412 Illkirch, France. daniele.altschuh@unistra.fr

Biochemical and Biophysical Research Communications
|October 16, 2012
PubMed
Summary

The novel Interaction Map (IM) method accurately analyzes complex cellular receptor binding data. This approach decomposes binding curves, revealing multiple ligand-receptor interactions for better understanding of biological systems.

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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Biophysics

Background:

  • Cellular receptor systems exhibit complex ligand interactions beyond simple one-to-one models.
  • Traditional regression analysis struggles with heterogeneous binding data.
  • The Interaction Map (IM) method was previously developed to address these limitations.

Purpose of the Study:

  • To validate the Interaction Map (IM) approach for analyzing complex binding data.
  • To demonstrate IM's capability in decomposing heterogeneous binding curves.
  • To assess IM's utility for data from LigandTracer and Surface Plasmon Resonance (SPR) devices.

Main Methods:

  • Artificially generated heterogeneous binding data from two known interactions.
  • Applied the Interaction Map (IM) method to analyze the generated data.
  • Utilized data from LigandTracer and Surface Plasmon Resonance (SPR) platforms.

Main Results:

  • The Interaction Map (IM) method successfully decomposed artificially generated heterogeneous binding curves.
  • IM accurately identified and separated the contributions of individual ligand-receptor interactions.
  • The study confirmed IM's ability to handle complex datasets from SPR and LigandTracer.

Conclusions:

  • The Interaction Map (IM) approach is a robust method for analyzing complex binding data.
  • IM can resolve previously uninterpretable heterogeneous binding patterns.
  • This method shows significant potential for analyzing cell-based assay data.