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
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

12.9K
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:
12.9K
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
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.8K
Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
4.8K
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

2.3K
2.3K

You might also read

Related Articles

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

Sort by
Same author

Artificial intelligence methods for protein structure and interaction prediction: Recent advances and challenges.

Current opinion in structural biology·2026
Same author

Assessing the potential of deep learning for protein-ligand docking.

Nature machine intelligence·2026
Same author

FlowDock: Geometric flow matching for generative protein-ligand docking and affinity prediction.

Bioinformatics (Oxford, England)·2025
Same author

Protein-Ligand Structure and Affinity Prediction in CASP16 Using a Geometric Deep Learning Ensemble and Flow Matching.

Proteins·2025
Same author

FlowDock: Geometric Flow Matching for Generative Protein-Ligand Docking and Affinity Prediction.

ArXiv·2025
Same author

Geometry-complete diffusion for 3D molecule generation and optimization.

Communications chemistry·2024

Related Experiment Video

Updated: Jun 24, 2025

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

Assessing the potential of deep learning for protein-ligand docking.

Alex Morehead1, Nabin Giri2, Jian Liu2

  • 1NERSC, Lawrence Berkeley National Laboratory, Berkeley, California, USA.

Arxiv
|June 3, 2024
PubMed
Summary

PoseBench is a new benchmark for protein-ligand docking that evaluates deep learning (DL) methods. It reveals DL methods struggle with novel proteins and multi-ligand binding, impacting drug discovery.

Keywords:
BenchmarksDeep learningMolecular dockingProtein-ligand interactions

More Related Videos

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

11.3K
Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

1.2K

Related Experiment Videos

Last Updated: Jun 24, 2025

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
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

11.3K
Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

1.2K

Area of Science:

  • Computational Biology
  • Structural Biology
  • Biotechnology

Background:

  • Ligand binding influences protein structure and function, crucial for drug discovery and biotechnology.
  • Existing deep learning (DL) docking methods lack systematic evaluation for broad applicability, including using predicted protein structures, multi-ligand binding, and unknown pockets.

Purpose of the Study:

  • Introduce PoseBench, the first comprehensive benchmark for broadly applicable protein-ligand docking.
  • Enable rigorous evaluation of DL methods for apo-to-holo docking and protein-ligand structure prediction.
  • Facilitate systematic assessment using primary and novel multi-ligand datasets.

Main Methods:

  • Developed PoseBench, a benchmark for evaluating protein-ligand docking and structure prediction.
  • Included datasets for single and multiple ligand binding scenarios.
  • Assessed DL co-folding methods against conventional and DL docking baselines.

Main Results:

  • DL co-folding methods generally outperform baseline docking methods.
  • Popular DL methods like AlphaFold 3 face challenges with novel protein sequences.
  • DL methods exhibit sensitivity to multiple sequence alignments and struggle with balancing accuracy and specificity in multi-ligand predictions.

Conclusions:

  • PoseBench provides a robust framework for evaluating protein-ligand docking methods.
  • Current DL methods require further development for real-world applications, especially for novel targets and multi-ligand systems.
  • The benchmark facilitates advancements in drug discovery and protein design through improved computational tools.