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

Conserved Binding Sites01:49

Conserved Binding Sites

5.0K
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...
5.0K
Ligand Binding Sites02:40

Ligand Binding Sites

14.8K
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...
14.8K
Ligand Binding Sites02:40

Ligand Binding Sites

8.5K
8.5K
Protein-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

579
Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
Indirect methods involve isolating the bound drug from its free form in biological samples such as blood, serum, or plasma. These techniques aim to measure the percentage of drugs bound to proteins. Equilibrium dialysis is a commonly used method where the free drug concentration at equilibrium is measured by separating the bound...
579
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

14.8K
The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
14.8K
Protein-protein Interfaces02:04

Protein-protein Interfaces

14.4K
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...
14.4K

You might also read

Related Articles

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

Sort by
Same author

High-Affinity Probes for Androgen Receptor Imaging: From Cells and <i>In Silico</i> Modeling to Whole-Body Fluorescent Applications.

Journal of medicinal chemistry·2025
Same author

RAPID-Net: Accurate Pocket Identification for Binding-Site-Agnostic Docking.

ArXiv·2025
Same author

Enhancing Open-World Bacterial Raman Spectra Identification by Feature Regularization for Improved Resilience against Unknown Classes.

Chemical & biomedical imaging·2024
Same author

Four-color fluorescence cross-correlation spectroscopy with one laser and one camera.

Biomedical optics express·2023
Same author

Raman Spectroscopy in Open-World Learning Settings Using the Objectosphere Approach.

Analytical chemistry·2022
Same author

Cholera Toxin as a Probe for Membrane Biology.

Toxins·2021

Related Experiment Video

Updated: Jan 6, 2026

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors
10:33

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors

Published on: October 26, 2015

11.7K

RAPID-Net: Accurate Pocket Identification for Binding-Site-Agnostic Docking.

Yaroslav Balytskyi1, Inna Hubenko2, Alina Balytska2

  • 1Department of Physics and Astronomy, Wayne State University, Detroit, Michigan 48201, United States.

Journal of Chemical Information and Modeling
|November 13, 2025
PubMed
Summary
This summary is machine-generated.

RAPID-Net, a deep learning algorithm, accurately predicts drug binding pockets for structure-based drug design. It enhances docking accuracy and identifies novel allosteric sites, accelerating therapeutic development.

More Related Videos

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

1.1K
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.4K

Related Experiment Videos

Last Updated: Jan 6, 2026

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors
10:33

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors

Published on: October 26, 2015

11.7K
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

1.1K
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.4K

Area of Science:

  • Computational chemistry
  • Structural biology
  • Drug discovery

Background:

  • Accurate identification of druggable pockets is crucial for structure-based drug design and docking.
  • Existing methods may not fully capture pocket features or integrate seamlessly with docking pipelines.

Purpose of the Study:

  • To present RAPID-Net, a deep learning algorithm for precise prediction of binding pockets.
  • To evaluate RAPID-Net's performance in structure-based drug design and virtual screening.
  • To demonstrate RAPID-Net's capability in identifying novel binding sites for therapeutic development.

Main Methods:

  • Development of RAPID-Net, a deep learning-based algorithm for pocket prediction.
  • Integration of RAPID-Net with AutoDock Vina for docking simulations.
  • Performance evaluation on the PoseBusters benchmark and diverse datasets.
  • Comparison with existing pocket prediction tools (DiffBindFR, PUResNet, Kalasanty) and AlphaFold 3.

Main Results:

  • RAPID-Net-guided AutoDock Vina achieved 54.9% Top-1 poses with RMSD < 2 Å on PoseBusters.
  • On challenging data, RAPID-Net-guided Vina achieved 53.1% Top-1 poses (vs. 59.5% for AlphaFold 3).
  • RAPID-Net identified at least one pose with RMSD < 2 Å in 92.2% of cases, highlighting pose ranking as a bottleneck.
  • RAPID-Net outperformed other tools in docking accuracy and pocket-ligand intersection rates.
  • Accurate identification of distal functional sites and broader pocket identification for SARS-CoV-2 RdRp.

Conclusions:

  • RAPID-Net offers accurate binding pocket prediction, enhancing docking pipeline integration.
  • Its lightweight inference, scalability, and competitive accuracy make it suitable for large-scale virtual screening.
  • RAPID-Net facilitates the discovery of novel therapeutic targets, including allosteric sites.
  • The algorithm shows potential for accelerating novel therapeutic development by uncovering diverse binding pockets.