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This is a Experimental Study study.

October 11, 2025Journal of Chemical Theory and Computation

Anticipating the Selectivity of Cyclization Reaction Pathways with Neural Network Potentials

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Authors

NCNicholas CasettiMassachusetts Institute of Technology DADylan M. AnstineNorthwest Missouri State University OIOlexandr IsayevCarnegie Mellon University

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Implication

Mechanism search shows improved stereoselectivity and activation energy estimates in cyclization reactions, suggesting advancements in natural product synthesis.

Key Points

The neural network potential effectively estimates activation energies for cyclization reactions, enhancing accuracy in predictions.
Mechanism search strategies utilizing graph-based enumeration and machine learning streamline the exploration of complex reaction pathways.
Stereoselectivity was anticipated correctly through the application of neural network potentials, indicating potential applications in synthesis.
This approach aids in identifying relevant reaction steps, addressing challenges posed by several concerted bond changes.

Cite This Study

Casetti et al. (2025) studied this question.

synapsesocial.com/papers/68e9b1d0ba7d64b6fc132a11 https://doi.org/10.1021/acs.jctc.5c01161

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Implication

Mechanism search shows improved stereoselectivity and activation energy estimates in cyclization reactions, suggesting advancements in natural product synthesis.

Anticipating the Selectivity of Cyclization Reaction Pathways with Neural Network Potentials

Discussion

Member takes

Implication

Key Points

Cite This Study

Anticipating the Selectivity of Cyclization Reaction Pathways with Neural Network Potentials

Discussion

Member takes

Implication

Key Points

Cite This Study

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