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

A fast method to predict protein interaction sites from sequences.

X Gallet1, B Charloteaux, A Thomas

  • 1Centre de Biophysique Moléculaire Numérique, Faculté Agronomique, Gembloux, 5030, Belgium. brasseur.r@fsagx.ac.be

Journal of Molecular Biology
|September 20, 2000
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

Donepezil, rivastigmine, and vitamin E in Alzheimer disease: a combined P300 event-related potentials/neuropsychologic evaluation over 6 months.

Clinical neuropharmacology·2001
Same author

Analysis of glomerulosclerosis and atherosclerosis in lecithin cholesterol acyltransferase-deficient mice.

The Journal of biological chemistry·2001
Same author

Somatostatin, its receptors and analogs, in lung cancer.

Chemotherapy·2001
Same author

[A study on abnormal chondrocyte differentiation and abnormal expression of collagen types in articular cartilage from patients with Kaschin-Beck disease].

Zhonghua bing li xue za zhi = Chinese journal of pathology·2001
Same author

Improved flow cytometric detection of HLA alloantibodies using pronase: potential implications in renal transplantation.

Transplantation·2001
Same author

Rapid detection of resistance to rifampicin in Mycobacterium leprae.

Leprosy review·2001
Same journal

DynaPIN: A tool for characterizing dynamic protein interfaces.

Journal of molecular biology·2026
Same journal

BindRNAgen: Protein-binding RNA sequence generation using latent diffusion models.

Journal of molecular biology·2026
Same journal

Structural basis of HSP90C, a highly active chloroplastic HSP90 chaperone from Arabidopsis thaliana.

Journal of molecular biology·2026
Same journal

Clinical inflammasome biomarkers: Progress and prospects.

Journal of molecular biology·2026
Same journal

Biologically Relevant, Cationic Residues in Human Rhinovirus Stabilize Capsid-Bound RNA Duplexes, and Restrict Capsid Flexibility.

Journal of molecular biology·2026
Same journal

Cryo-EM structures of phage T4 infection intermediate.

Journal of molecular biology·2026
See all related articles

This study introduces a simple sequence-based method to predict protein interaction sites, identifying receptor-binding domains (RBDs) using hydrophobicity. The approach accurately detects various functional sites, aiding experimental research.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Identifying protein interaction sites is crucial for understanding biological functions.
  • Experimental methods for determining protein interaction sites can be time-consuming and resource-intensive.
  • Predictive methods based on sequence data can accelerate the discovery process.

Purpose of the Study:

  • To develop a simple, sequence-based method for predicting protein interaction sites.
  • To identify receptor-binding domains (RBDs) using hydrophobicity distribution analysis.
  • To validate the method's efficacy across diverse protein interaction datasets.

Main Methods:

  • Analysis of hydrophobicity distribution in protein sequences to identify linear stretches as RBDs.

Related Experiment Videos

  • Statistical analysis of amino acid frequencies in known and predicted interaction sites.
  • Prediction of RBDs from a large database (Swissprot) of protein sequences.

    • Main Results:

    • The method successfully detected 59-80% of known interaction sites as RBDs.
    • Arginine was identified as the most frequent residue in both known and predicted interaction sites.
    • Specific interaction sites, including DNA-binding (95%) and Ca-binding domains (83%), were accurately detected.

    Conclusions:

    • The proposed method offers a rapid and effective way to predict protein interaction sites directly from sequence data.
    • This sequence-based prediction approach can guide experimental strategies, such as site-specific mutagenesis and inhibitor design.
    • The method demonstrates utility in identifying functional domains in proteins like retroviral Gag and penicillin-binding proteins.