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

SuperStar: improved knowledge-based interaction fields for protein binding sites.

M L Verdonk1, J C Cole, P Watson

  • 1Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge, CB2 1EZ, UK. m.verdonk@astex-technology.com

Journal of Molecular Biology
|March 29, 2001
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

Clinical benefit of faecal microbiota transplantation administered via a single retention enema as an adjunctive treatment in dogs with chronic enteropathy: a randomised controlled trial.

The Journal of small animal practice·2026
Same author

BSAVA Petsavers Article: Validation of an ELISA assay for measurement of the metabolite of serotonin, 5-hydroxyindole acetic acid (5-HIAA), in canine urine.

The Journal of small animal practice·2026
Same author

Development of an in-home screening tool for canine periodontitis.

Veterinary journal (London, England : 1997)·2025
Same author

Implementing creative dance activities for primary school children to improve health and wellbeing: a qualitative study in the North East England.

Perspectives in public health·2024
Same author

Real-world diagnostic potential of bacterial biomarkers of canine periodontitis.

Frontiers in veterinary science·2024
Same author

Stevens-Johnson syndrome induced by lacosamide: A rare adverse reaction.

Annales de dermatologie et de venereologie·2023
Same journal

Tesorai Search: cloud-based database search engine boosts identifications for mass spectrometry proteomics with a pretrained peptide-spectrum deep-learning model.

Journal of molecular biology·2026
Same journal

Characterization of diverse functions of NRF1 nuclear localization sequence.

Journal of molecular biology·2026
Same journal

UPF3A and UPF3B shape the transcriptome cooperatively yet oppose cell function.

Journal of molecular biology·2026
Same journal

Antibody-secreting cells integrate efficient NMD with non‑canonical UPR signaling to maintain proteostasis and support massive immunoglobulin synthesis.

Journal of molecular biology·2026
Same journal

Small molecule stabilization of diverse amyloidogenic immunoglobulin light chains revealed by hydrogen-deuterium exchange mass spectrometry.

Journal of molecular biology·2026
Same journal

UPF1 at Work: Structural and Mechanistic Insights Into a Master Regulator of Nonsense-Mediated mRNA Decay.

Journal of molecular biology·2026
See all related articles

SuperStar, an empirical method for protein interaction site identification, has been enhanced with new features for metal centers and improved probe selection. Validation shows high accuracy in predicting interaction hot spots, aiding drug discovery and protein engineering.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Drug Discovery

Background:

  • Identifying protein-ligand interaction sites is crucial for understanding biological processes and designing therapeutics.
  • Empirical methods like SuperStar leverage experimental data to predict these sites.

Purpose of the Study:

  • To describe recent modifications and additions to the SuperStar method for protein interaction site identification.
  • To validate the performance of enhanced SuperStar, particularly for metal-binding sites and new probes.

Main Methods:

  • Utilized the IsoStar database of non-bonded interactions from small-molecule crystal structures.
  • Generated propensity maps for protein binding sites using various chemical probes (e.g., nitrogen, oxygen, carbon atoms).
  • Introduced a peak-searching algorithm to identify interaction hot spots and validated on X-ray structures.

Related Experiment Videos

  • Developed and validated propensity map generation around metal centers (Ca(2+), Mg(2+), Zn(2+)).
  • Employed clustering techniques for non-redundant probe selection and performance testing.

    • Main Results:

    • SuperStar accurately predicted interaction hot spots, with ligand atoms within 1.0-1.5 Å of predicted peaks.
    • Propensity maps around metal centers were successfully generated, with correct coordination geometry identified in ~75% of cases.
    • Imposing correct metal coordination geometry improved prediction accuracy, with ligand atoms within 0.59 Å of peaks.
    • Newly introduced probes generally performed as well as the original four probes.

    Conclusions:

    • Recent enhancements significantly improve SuperStar's capability for identifying protein interaction sites, including metal-binding regions.
    • The method provides accurate predictions, valuable for structural bioinformatics and drug design.
    • SuperStar's performance around metal centers is comparable to other protein interaction sites.