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Related Concept Videos

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Related Experiment Video

Updated: Jan 12, 2026

Modeling an Enzyme Active Site using Molecular Visualization Freeware
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Modeling protein-small molecule conformational ensembles with PLACER.

Ivan Anishchenko1,2, Yakov Kipnis1,2,3, Indrek Kalvet1,2,3

  • 1Department of Biochemistry, University of Washington, Seattle, WA 98105.

Proceedings of the National Academy of Sciences of the United States of America
|November 4, 2025
PubMed
Summary
This summary is machine-generated.

We developed PLACER, a graph neural network for protein-ligand atomistic conformational ensemble resolution. This tool rapidly generates diverse molecular structures, improving enzyme design and predicting protein-small molecule interactions.

Keywords:
enzyme designligand dockingmachine learning

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Artificial intelligence in drug discovery

Background:

  • Modeling conformational heterogeneity in protein-small molecule interactions is crucial but challenging.
  • Atomic-level descriptions offer potential advantages in speed and generality for probing interactions in folded states.

Purpose of the Study:

  • To develop a novel computational tool for modeling protein-small molecule interactions.
  • To generate accurate atomic-level conformational ensembles for small molecules and protein-ligand complexes.
  • To enhance enzyme design by assessing active site preorganization and accuracy.

Main Methods:

  • Developed PLACER (protein-ligand atomistic conformational ensemble resolver), a graph neural network model.
  • Trained PLACER on atomic positions from corrupted structures in the Cambridge Structural Database and Protein Data Bank.
  • Utilized PLACER for generating small molecule structures, protein side chains, and protein-small molecule docking ensembles.

Main Results:

  • PLACER accurately generates diverse organic small molecule structures based on composition and bonding.
  • The model effectively builds small molecule and protein side chain structures for docking.
  • Enzyme design using PLACER for active site assessment led to higher success rates and activities, including a retroaldolase with a kcat/KM of 11,000 M-1min-1.

Conclusions:

  • PLACER provides a rapid and stochastic method for generating conformational ensembles.
  • The tool is effective for both small molecule and protein-ligand systems.
  • PLACER shows significant promise for improving enzyme design and predicting molecular interactions.