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 Experiment Videos

Shaping dots and lines: adding modularity into protein interaction networks using structural information.

Anne Campagna1, Luis Serrano, Christina Kiel

  • 1EMBL-CRG Systems Biology Unit, CRG-Centre de Regulacio Genomica, Dr. Aiguader 88, 08003 Barcelona, Spain.

FEBS Letters
|February 20, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Quantitative models of photoreceptor metabolisms: implications for rod outer segment length, retinal glycolysis and choroidal blood flow.

Physical biology·2026
Same author

Triple-hit diffuse large B-cell lymphoma with choroidal and cavernous sinus involvement mimicking inflammatory and neuro-ophthalmic disease: case report.

Frontiers in ophthalmology·2026
Same author

Exon inclusion signatures enable accurate estimation of splicing factor activity.

Nature communications·2026
Same author

Sources of essential lipids for Mycoplasma pneumoniae via P116 to target liver and atherosclerotic lesions.

Nature communications·2025
Same author

A Dual Valorization Strategy of Barley Straw for the Development of High-Performance Bio-Based Polyurethane Foams.

Polymers·2025
Same author

Using single-cell perturbation screens to decode the regulatory architecture of splicing factor programs.

Nucleic acids research·2025
Same journal

Extending the classical sequence-structure-function paradigm through protein dynamics and context-dependent behavior.

FEBS letters·2026
Same journal

α-Synuclein aggregation landscape from phase separation to neurotoxic intermediates.

FEBS letters·2026
Same journal

Modelling stem cell differentiation related processes-A practical overview for biologists.

FEBS letters·2026
Same journal

Overlapping gut microbiome signatures in aging and disease are characterized by enrichment of medication-associated oral microbes in the gut.

FEBS letters·2026
Same journal

Csk binding to integrin β3 is regulated by tyrosine and threonine phosphorylation of β3.

FEBS letters·2026
Same journal

Mixed-class J-domain protein scaffolds promote expanded aggregate handling and multivalent Hsp70 engagement during functional disaggregase assembly.

FEBS letters·2026
See all related articles

Structural information and computational tools can predict protein interactions and model network changes. This aids in understanding diseases and reorganizing biological networks into functional modules.

Area of Science:

  • Computational biology
  • Structural biology
  • Systems biology

Background:

  • Understanding protein interaction networks is vital for biological systems and disease research.
  • Predicting the impact of disease-related mutations requires dynamic network models.

Purpose of the Study:

  • To review the potential of integrating structural information with computational tools for protein interaction network analysis.
  • To explore methods for predicting new interactions, estimating binding affinities, and determining interaction compatibility.

Main Methods:

  • Utilizing structural data to computationally predict protein-protein interactions.
  • Employing computational models to estimate binding affinities and kinetic rate constants.
  • Analyzing interaction compatibility to identify exclusive and cooperative binding events.

Related Experiment Videos

Main Results:

  • Structural and computational approaches can accurately predict novel protein interactions.
  • These methods allow for the estimation of key kinetic and affinity parameters for protein complexes.
  • Determining interaction compatibility is key to modularizing large-scale networks.

Conclusions:

  • Integrating structural information and computational tools offers a powerful strategy for dissecting protein interaction networks.
  • This approach facilitates the prediction of disease-related mutant effects and the organization of networks into functional modules.