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

Structural characterization of proteins using residue environments.

Sean D Mooney1, Mike Hsin-Ping Liang, Rob DeConde

  • 1Department of Genetics, Stanford University, Stanford, California, USA. sdmooney@iupui.edu

Proteins
|October 26, 2005
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

GATSBI: improving context-aware protein embeddings through biologically motivated data splits.

Bioinformatics (Oxford, England)·2026
Same author

TikTok is a valuable data source for tracking the opioid crisis.

NPJ digital medicine·2026
Same author

Drug-Target Interaction Prediction with PIGLET.

bioRxiv : the preprint server for biology·2026
Same author

GATSBI: Improving context-aware protein embeddings through biologically motivated data splits.

bioRxiv : the preprint server for biology·2026
Same author

Biological data governance in an age of AI.

Science (New York, N.Y.)·2026
Same author

The Human Omnibus of Targetable Pockets.

Journal of cheminformatics·2025

Structural genomics faces challenges in automatically characterizing protein functions. A new method, S-BLEST (Structure-Based Local Environment Search Tool), identifies similar amino acid environments in protein structures, aiding functional annotation.

Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational biology

Background:

  • Automated functional characterization of protein structures is a key challenge in structural genomics.
  • Existing methods often rely on sequence similarity, limiting their application to novel or uncharacterized proteins.

Purpose of the Study:

  • To develop and validate a sequence-independent method for annotating protein structures based on local structural environments.
  • To create a searchable resource of protein structures for rapid identification of similar local environments.

Main Methods:

  • Developed S-BLEST (Structure-Based Local Environment Search Tool), a method that encodes local amino acid environments as vectors of structural properties.
  • Applied S-BLEST to a nonredundant database of protein structures to build a searchable resource.

Related Experiment Videos

  • Utilized a K-nearest neighbor search to identify similar amino acid environments for query amino acids.
  • Estimated the statistical significance of identified similar environments.

    • Main Results:

    • Validated S-BLEST using X-ray crystal structures from the ASTRAL 40 dataset.
    • Applied S-BLEST to 86 proteins with unknown function and no significant sequence neighbors in the Protein Data Bank (PDB).
    • Successfully associated 20 proteins with at least one local structural neighbor, identifying conserved amino acid environments.

    Conclusions:

    • S-BLEST provides an effective sequence-independent approach for functional annotation of protein structures.
    • The method facilitates the discovery of functional relationships by identifying similar local structural environments.
    • S-BLEST is a valuable tool for structural genomics, particularly for proteins with limited sequence information.