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Updated: Jun 11, 2025
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Modeling an Enzyme Active Site using Molecular Visualization Freeware
Published on: December 25, 2021
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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, USA.
Biorxiv : the Preprint Server for Biology
|October 10, 2024
Summary
ChemNet, a novel graph neural network, accurately models protein-small molecule interactions at the atomic level. This method enhances enzyme design by predicting conformational ensembles, leading to higher activity and success rates.
Area of Science:
- Computational chemistry
- Structural biology
- Machine learning
Background:
- Modeling conformational heterogeneity in protein-small molecule systems is complex.
- Atomic-level descriptions offer advantages in speed and generality for folded-state interactions.
Purpose of the Study:
- To develop a novel graph neural network (ChemNet) for atomic-level modeling of protein-small molecule systems.
- To leverage ChemNet for predicting conformational ensembles and improving enzyme design.
Main Methods:
- Developed ChemNet, a graph neural network, trained on atomic positions from the Cambridge Structural Database and Protein Data Bank.
- Utilized ChemNet to generate atomic structures of small molecules and protein side chains for docking.
- Generated conformational ensembles using ChemNet's rapid and stochastic predictions.
Main Results:
- ChemNet accurately reconstructs atomic positions from corrupted inputs.
- The model successfully generates structures for diverse organic small molecules and protein-small molecule complexes.
- Enzyme design using ChemNet for active site assessment yielded higher success rates and activities, including a retroaldolase with a kcat/KM of 11000 M-1min-1.
Conclusions:
- ChemNet provides a rapid and general method for modeling conformational heterogeneity in small molecule and protein systems.
- The approach significantly improves enzyme design by enabling the creation of pre-organized active sites.
- ChemNet is anticipated to be a valuable tool for computational chemistry and structural biology research.
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