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 Video

Updated: May 16, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

PL-PatchSurfer3: improved structure-based virtual screening for structure variation using 3D Zernike descriptors.

Woong-Hee Shin1,2, Yuki Kagaya3, Wonkyeong Jang4

  • 1Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Republic of Korea. whshin@korea.ac.kr.

Journal of Cheminformatics
|May 15, 2026
PubMed
Summary

Related Concept Videos

Patch Clamp01:18

Patch Clamp

Many fundamental cell functions such as muscle contraction and nerve transmission rely on the electrical signals produced by the movement of positively and negatively charged ions across the cell membrane. One competent method to record current flowing across the whole cell or single ion channel is the patch-clamp technique.
In this method, a glass micropipette containing electrolyte solution is tightly sealed against a small portion of the cell membrane. As a result, a patch of the cell...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

DAQplugin: Deep Learning based Real-time Model Evaluation Plugin for ChimeraX.

bioRxiv : the preprint server for biology·2026
Same author

Direct Detection and Atomic Modeling of Ligands in Cryo-EM Maps Using Deep Learning.

bioRxiv : the preprint server for biology·2026
Same author

Broussochalcone A alleviates cognitive impairment in scopolamine-induced mice as a potent β-amyloid aggregation inhibitor and changes blood and brain metabolite profiles.

Journal of ethnopharmacology·2026
Same author

On the state of protein function prediction: a report on the fourth CAFA challenge.

bioRxiv : the preprint server for biology·2026
Same author

Functional impact of the ATP1A3-p.A813V variant: insights into a calcium-driven hyperexcitability cascade in rapid-onset dystonia-Parkinsonism.

Journal of translational medicine·2026
Same author

Multivalent recognition of ferritin by full-length NCOA4 enables robust ferritinophagy.

Protein science : a publication of the Protein Society·2026
Same journal

Unified heterogeneity-aware benchmark of drug synergy prediction: a cross-study analysis of traditional machine learning and graph deep learning models.

Journal of cheminformatics·2026
Same journal

Count your bits: fingerprint benchmarking to assess broad chemical space representation.

Journal of cheminformatics·2026
Same journal

Sampling out-of-distribution chemical spaces via Bayesian flow.

Journal of cheminformatics·2026
Same journal

Hold on tight: the kinetic profiling of opioid receptor ligands using the CORAL-MD.

Journal of cheminformatics·2026
Same journal

Transformer-accelerated discovery of inhibitors targeting the RpsA<sub>Δ438</sub> deletion in PZA-resistant tuberculosis.

Journal of cheminformatics·2026
Same journal

DICL: a manually curated database of ion channels and ligands as a useful platform for drug discovery targeting ion channels.

Journal of cheminformatics·2026
See all related articles
This summary is machine-generated.

Structure-based virtual screening (SBVS) methods struggle with protein flexibility. PL-PatchSurfer3 improves drug discovery by using a robust surface patch approach, enhancing accuracy across various protein structures.

Area of Science:

  • Computational chemistry
  • Drug discovery
  • Structural bioinformatics

Background:

  • Structure-based virtual screening (SBVS) is crucial for in silico drug discovery.
  • SBVS performance is highly dependent on the accuracy of the receptor's 3D structure.
  • Existing methods often fail when screening apo structures against holo targets due to conformational changes.

Purpose of the Study:

  • To introduce PL-PatchSurfer3, an enhanced SBVS method.
  • To improve robustness and accuracy in virtual screening.
  • To address the limitations of conventional docking methods concerning protein conformational flexibility.

Main Methods:

  • Utilized a surface patch-based representation of binding sites and ligands.
  • Employed 3D Zernike descriptors to capture shape and physicochemical properties of molecular surfaces.
Keywords:
3D Zernike descriptorsMolecular surfaceStructure flexibilityStructure-based virtual screening

More Related Videos

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
08:35

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Published on: May 29, 2021

Related Experiment Videos

Last Updated: May 16, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
08:35

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Published on: May 29, 2021

  • Incorporated refined hydrogen bond complementarity and visibility (curvature) for enhanced patch description.

    • Main Results:

    • PL-PatchSurfer3 demonstrated superior performance compared to its predecessor, PL-PatchSurfer.
    • The method showed robustness across diverse receptor structures, including apo, holo, modeled, and AlphaFold-predicted forms.
    • PL-PatchSurfer3 outperformed or matched conventional and recent deep learning-based SBVS methods.

    Conclusions:

    • PL-PatchSurfer3 offers a more stable and accurate SBVS approach.
    • The surface patch methodology effectively handles receptor conformational variations.
    • This advancement holds significant potential for improving the efficiency of in silico drug discovery pipelines.