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 scoring function for docking ligands to low-resolution protein structures.

Eckart Bindewald1, Jeffrey Skolnick

  • 1Center of Excellence in Bioinformatics, University at Buffalo, 901 Washington St., Buffalo, New York 14203, USA.

Journal of Computational Chemistry
|January 15, 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

Adversarial Sequence Mutations in AlphaFold and ESMFold Reveal Nonphysical Structural Invariance, Confidence Failures, and Concerns for Protein Design.

Computational and structural biotechnology journal·2026
Same author

Toward mechanistic virtual immune cells.

Nature biotechnology·2026
Same author

Understanding Substance Dependence: What Differentiates Addictive from Non-Addictive Drugs?

bioRxiv : the preprint server for biology·2026
Same author

A reliability-screened thalamocortical control-network phenotype tracks cocaine-use history in cocaine use disorder.

medRxiv : the preprint server for health sciences·2026
Same author

AlphaInterp: Mechanistic Interpretability of AlphaFold 3 Reveals How Evolutionary Information Shapes Protein Structure Prediction.

bioRxiv : the preprint server for biology·2026
Same author

PHENOCAUZ: Linking Human Symptoms, Drug Side Effects and Efficacy to Their Molecular Causes Using Mendelian Disease Biology.

bioRxiv : the preprint server for biology·2026
Same journal

PES2MP: A Python Application for Automating Collisional Dynamics of Linear Rigid-Rotors.

Journal of computational chemistry·2026
Same journal

The Anionic States of Ubiquinone Characterized by Second-Order Approximate Coupled-Cluster Theory.

Journal of computational chemistry·2026
Same journal

Hydrogen Bond Energy Estimation in Large Molecular Clusters via the Method of Synergistic Cyclic Cooperativity: A Software Update H-BEE 2.0.

Journal of computational chemistry·2026
Same journal

The Intricate Mechanism of Nitric Oxide Synthase.

Journal of computational chemistry·2026
Same journal

A Molecular "Thermometer" for Measuring Effective Non-Local Exchange.

Journal of computational chemistry·2026
Same journal

Insights to Orientation Dependence of Molecular Conduction Modeled by High-Level Quantum Embedding.

Journal of computational chemistry·2026
See all related articles

This study introduces a novel protein-ligand docking method optimized for low-resolution structures. The approach accurately predicts ligand-binding sites, significantly improving upon existing methods for both native and decoy structures.

Area of Science:

  • Structural Biology
  • Computational Chemistry
  • Drug Discovery

Background:

  • Accurate prediction of protein-ligand binding sites is crucial for drug discovery.
  • Existing docking methods often struggle with low-resolution protein structures.
  • Optimizing scoring functions for specific structural resolutions is essential.

Purpose of the Study:

  • To develop and validate a protein-ligand docking method tailored for low-resolution protein structures.
  • To assess the method's ability to accurately predict ligand-binding sites.
  • To compare the performance against existing docking algorithms.

Main Methods:

  • Development of a novel scoring function optimized for low-resolution protein structures.
  • Application of the docking method to predict ligand-binding sites in various protein-ligand complexes.

Related Experiment Videos

  • Validation using native and decoy protein structures with varying root-mean-square deviation (RMSD).
  • Comparative analysis with the Dolores method.

    • Main Results:

    • The developed scoring function parameters differ significantly between high- and low-resolution optimizations.
    • Successfully predicted ligand-binding sites in low-resolution structures with high accuracy.
    • For a set of 25 complexes, 76% correctly predicted >50% of ligand-contacting residues.
    • Achieved >50% correct residue prediction in 93.8% of cases for an 81-complex dataset.
    • Outperformed the Dolores method, achieving over four times more correct predictions for specific contacts.

    Conclusions:

    • The novel docking method demonstrates high efficacy in predicting ligand-binding sites, particularly for low-resolution protein structures.
    • The method offers a significant advancement over existing techniques, enhancing the reliability of structure-based drug design.
    • The findings underscore the importance of resolution-specific optimization in computational docking approaches.