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 Concept Videos

Ligand Binding Sites02:40

Ligand Binding Sites

12.8K
Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
12.8K
Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
4.2K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.5K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.5K

You might also read

Related Articles

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

Sort by
Same author

Target Class Repurposing Across Membrane Transporter Families Provides Privileged Ligands to Address Specific and Undruggable Pharmacological Targets.

ACS pharmacology & translational science·2026
Same author

Discovery of an allosteric binding site for anthraquinones at the human P2X4 receptor.

Nature communications·2025
Same author

Synthesis, Characterization, Interactions, and Immunomodulatory Function of Ectonucleotidase CD39/CD73 Inhibitor 8-Butylthioadenosine 5'-Monophosphate.

ACS pharmacology & translational science·2025
Same author

Selective, Non-nucleotidic Radiotracer for P2Y<sub>12</sub> Receptors: Design, Synthesis, Characterization, and Imaging of Brain Slices.

Journal of medicinal chemistry·2025
Same author

Subnanomolar MAS-related G protein-coupled receptor-X2/B2 antagonists with efficacy in human mast cells and disease models.

Signal transduction and targeted therapy·2025
Same author

Discovery of Anthranilic Acid Derivatives as Antagonists of the Pro-Inflammatory Orphan G Protein-Coupled Receptor GPR17.

Journal of medicinal chemistry·2024

Related Experiment Video

Updated: Jun 25, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
10:29

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

953

Computer-aided pattern scoring - A multitarget dataset-driven workflow to predict ligands of orphan targets.

Katja Stefan1,2, Vigneshwaran Namasivayam3,4, Sven Marcel Stefan5,6,7

  • 1University of Oslo and Oslo University Hospital, Department of Pathology, Rikshospitalet, Sognsvannsveien 20, 0372, Oslo, Norway.

Scientific Data
|May 23, 2024
PubMed
Summary

Researchers developed a novel computational method, computer-aided pattern scoring (C@PS), to identify potential drug ligands for challenging

More Related Videos

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.7K
Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

2.5K

Related Experiment Videos

Last Updated: Jun 25, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
10:29

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

953
A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.7K
Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

2.5K

Area of Science:

  • Drug discovery and development
  • Computational chemistry
  • Pharmacology

Background:

  • Identifying drug leads and novel targets are key challenges in life sciences.
  • Many disease-associated proteins are 'orphan targets' with unknown functions and ligands.
  • Undruggability hinders drug development, necessitating innovative approaches for ligand identification.

Purpose of the Study:

  • To present a novel cheminformatic workflow for identifying ligands for orphan targets.
  • To demonstrate the utility of a unique dataset for the ABCA1 orphan target.
  • To address the challenge of undruggable targets in drug discovery.

Main Methods:

  • Development of the computer-aided pattern scoring (C@PS) workflow.
  • Utilizing a unique dataset for the ABCA1 orphan target.
  • Applying cheminformatic approaches for ligand identification.

Main Results:

  • The C@PS workflow achieved a 95.5% hit rate in identifying novel ligands.
  • Identified molecules exhibited high potency and significant structural diversity.
  • The developed dataset serves as a template for deorphanization studies.

Conclusions:

  • The C@PS workflow is effective for identifying novel ligands for orphan targets.
  • This approach can accelerate drug discovery for previously undruggable targets.
  • The presented dataset and method offer a generalizable strategy for target deorphanization.