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...
Proteomics01:33

Proteomics

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.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...
Protein-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
Indirect methods involve isolating the bound drug from its free form in biological samples such as blood, serum, or plasma. These techniques aim to measure the percentage of drugs bound to proteins. Equilibrium dialysis is a commonly used method where the free drug concentration at equilibrium is measured by separating the bound...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Assembly of Signaling Complexes01:30

Assembly of Signaling Complexes

Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...

You might also read

Related Articles

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

Sort by
Same author

Localized and delocalized modes on random geometric graphs in one dimension.

Physical review. E·2026
Same author

Stochasticity Leads to Coexistence of Generalists and Specialists in Assembling Mutualistic Communities.

The American naturalist·2022
Same author

Master stability functions for metacommunities with two types of habitats.

Physical review. E·2022
Same author

A closed form for Jacobian reconstruction from time series and its application as an early warning signal in network dynamics.

Proceedings. Mathematical, physical, and engineering sciences·2022
Same author

Nested versus Independent Sampling: Solving the Mystery of Contradictory Species-Area Relationships.

The American naturalist·2021
Same author

The concerted emergence of well-known spatial and temporal ecological patterns in an evolutionary food web model in space.

Scientific reports·2021

Related Experiment Video

Updated: May 10, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Deducing Underlying Mechanisms from Protein Recruitment Data.

Laurin Lengert1, Barbara Drossel

  • 1Institute for Condensed Matter Physics, TU Darmstadt, Darmstadt, Germany.

Plos One
|July 5, 2013
PubMed
Summary

This study explores how protein interactions in living cells, particularly after DNA damage, can be understood using mechanistic models. Analyzing protein recruitment curves helps determine interaction types and assess model significance, even with incomplete reaction data.

More Related Videos

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
14:58

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

Published on: November 12, 2012

Related Experiment Videos

Last Updated: May 10, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
14:58

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

Published on: November 12, 2012

Area of Science:

  • Cellular dynamics and protein interactions
  • Mechanistic modeling in systems biology
  • Quantitative analysis of cellular responses

Background:

  • Fluorescent labeling allows in vivo measurement of protein distribution and dynamics in living cells.
  • Mechanistic models are crucial for studying cellular responses (e.g., to DNA damage) but are often underdetermined by experimental data.
  • Assessing the significance of model parameters and identifying essential proteins is challenging due to model complexity.

Purpose of the Study:

  • To systematically investigate the information reliably deducible from protein recruitment data.
  • To establish criteria for assessing the significance of mechanistic models when the complete set of reactions is unknown.
  • To analyze how protein interactions influence cellular responses and model interpretation.

Main Methods:

  • Detailed study of mechanistic models involving one or two interacting proteins recruited to a substrate.
  • Analysis of protein recruitment curves to infer interaction types and model parameters.
  • Investigation of conditions under which different mechanistic models can be discriminated based on experimental data.

Main Results:

  • The shape of protein recruitment curves can often reveal the type of interaction between proteins.
  • Criteria are discussed for determining when different mechanistic models are distinguishable or indistinguishable from the data.
  • Protein concentration variations in experiments can aid in discriminating between alternative models that equally fit existing data.

Conclusions:

  • Reliable deduction of protein interaction mechanisms is possible from recruitment data, even with incomplete knowledge of cellular reactions.
  • Understanding model identifiability is key to interpreting complex biological systems.
  • Strategic experimental design, such as varying protein concentrations, can enhance the power of mechanistic models in systems biology.