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
Protein Networks02:26

Protein Networks

4.0K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.0K

You might also read

Related Articles

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

Sort by
Same author

Blockiness reduces the packing of styrene/methyl methacrylate copolymers.

Soft matter·2026
Same author

Molecular crowding and amyloidogenic self-assembly: Emergent perspectives from modern computations.

Current opinion in structural biology·2026
Same author

Overlapping gut microbiome signatures in aging and disease are characterized by enrichment of medication-associated oral microbes in the gut.

FEBS letters·2026
Same author

Theoretical investigation of catalytic oxidation of benzyl alcohol by Au, Cu and Au-Cu nanoclusters.

Physical chemistry chemical physics : PCCP·2026
Same author

Thermal resilience of the archaeal heat shock Protein-14 (sHSP14) dimer: Insights into Nature's molecular design.

Biochemical and biophysical research communications·2026
Same author

Mechanistic principles of antimicrobial peptides uncovered by charge density-based machine learning.

Chemical communications (Cambridge, England)·2026

Related Experiment Video

Updated: Jul 4, 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

PLAS-20k: Extended Dataset of Protein-Ligand Affinities from MD Simulations for Machine Learning Applications.

Divya B Korlepara1,2, Vasavi C S1,3, Rakesh Srivastava4

  • 1IHub-Data, International Institute of Information Technology, Hyderabad, 500032, India.

Scientific Data
|February 9, 2024
PubMed
Summary

A new large-scale dataset, PLAS-20k, captures dynamic protein-ligand interactions for improved binding affinity prediction in drug discovery. This dataset enhances machine learning models, outperforming traditional docking scores.

More Related Videos

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

1.8K
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.1K

Related Experiment Videos

Last Updated: Jul 4, 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
Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

1.8K
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.1K

Area of Science:

  • Computational chemistry
  • Structural biology
  • Machine learning in drug discovery

Background:

  • Accurate prediction of protein-ligand binding affinities is crucial for efficient drug discovery.
  • Current machine learning models struggle due to a lack of dynamic interaction data in existing datasets.

Purpose of the Study:

  • To develop the PLAS-20k dataset, incorporating dynamic features of protein-ligand interactions.
  • To provide a benchmark for developing advanced machine learning models for binding affinity prediction.

Main Methods:

  • Generated PLAS-20k dataset with 97,500 simulations for 19,500 protein-ligand complexes.
  • Retrained the OnionNet model using the PLAS-20k dataset.
  • Evaluated model performance against experimental values and docking scores.

Main Results:

  • PLAS-20k dataset shows good correlation with experimental binding affinities.
  • The dataset improves predictions for ligands following Lipinski's rule and diverse complex structures.
  • The dataset aids in classifying strong and weak binders more effectively than docking.

Conclusions:

  • The PLAS-20k dataset is a valuable resource for developing next-generation machine learning models in drug discovery.
  • Large-scale molecular dynamics (MD)-based datasets can accelerate the drug discovery pipeline.
  • Incorporating dynamic features significantly enhances binding affinity prediction accuracy.