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

Docking without docking: ISEARCH--prediction of interactions using known interfaces.

Stefan Günther1, Patrick May, Andreas Hoppe

  • 1Institute of Molecular Biology and Bioinformatics - Charité, 14195 Berlin, Germany. stefan.guenther@charite.de

Proteins
|September 7, 2007
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

Selective vulnerability of dopaminergic neurons in Parkinson's disease connects PRKN and differential expression of CHCHD2 and GPNMB.

Cell death & disease·2026
Same author

Genetic variation in antidiabetic drug targets: associations with Parkinson's disease risk and age at onset.

NPJ Parkinson's disease·2026
Same author

PathoFact 2.0: an integrative pipeline for the prediction of antimicrobial resistance genes, virulence factors, toxins and toxin-associated proteins, and biosynthetic gene clusters in metagenomes.

GigaScience·2026
Same author

Is obstructive sleep apnea a driver of cancer and chronic disease risk? A real-world analysis of over 3 million patients.

BMC pulmonary medicine·2026
Same author

Flexible Data Integration for Genomics-Driven Decision Support in Rare Genetic Epilepsy.

Studies in health technology and informatics·2026
Same author

High-resolution multi-omics enhances prediction and detection of smORF-encoded proteins in the human gut microbiome.

Nature communications·2026
Same journal

Engineered HSP90-MP65 Bivalent Fusion Antigen: A Novel Vaccine Candidate Against Invasive Candidiasis.

Proteins·2026
Same journal

Physics-Based Energy Functions for Computational Protein Design.

Proteins·2026
Same journal

Impact of Stabilizing Osmolytes on the Conformational Dynamics of Human and Rat Islet Amyloid Polypeptides.

Proteins·2026
Same journal

Stabilization of Bone Morphogenetic Protein-2 at Physiological pH: Contrasting Roles of CHAPS and Arginine in Aggregation Inhibition.

Proteins·2026
Same journal

Structural Insights Into the Function of Leishmania major Adenylosuccinate Lyase.

Proteins·2026
Same journal

Generalizing the Gaussian Network Model: Spanning-Tree Thermodynamics Shows Entropy-Driven KRAS Activation.

Proteins·2026
See all related articles

This study introduces a computational method to identify protein interaction sites by comparing surface patches. The NeedleHaystack algorithm efficiently finds similar regions, aiding in predicting protein complexes.

Area of Science:

  • Computational biology
  • Structural biology
  • Bioinformatics

Background:

  • The growing number of solved protein structures offers a rich resource for studying protein-protein interactions.
  • Identifying these interaction interfaces is crucial for understanding biological processes and for drug discovery.

Purpose of the Study:

  • To develop and evaluate a computational approach for identifying protein-protein interaction sites.
  • To enable the prediction of protein complexes by leveraging known interface structures.

Main Methods:

  • Utilizing an interface library of known protein-protein interactions.
  • Employing the NeedleHaystack algorithm for rapid screening of protein surface patches.
  • Superposing unbound protein structures onto known interfaces based on structural and residue composition similarity.

Related Experiment Videos

Main Results:

  • The NeedleHaystack algorithm successfully identifies structurally similar surface patches within minutes.
  • The method recognizes related sites even with partial template similarity and low overall similarity.
  • The approach demonstrates effectiveness on standard benchmark datasets, complementing existing prediction methods.

Conclusions:

  • This interface library approach provides a valuable tool for predicting protein complexes.
  • The method is efficient and can identify interaction sites even with low similarity, broadening its applicability.
  • It serves as a complementary strategy to *ab initio* prediction methods in structural biology.