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October 3, 2025Open Access

Anticipating the Selectivity of Cyclization Reaction Pathways with Neural Network Potentials

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The proposed mechanism search strategy efficiently predicts reaction outcomes based on cyclization pathways.
Using neural network potential, AIMNet2-rxn, the method effectively estimates activation energies.
The approach successfully anticipates stereoselectivity crucial for the synthesis of natural products.
Combining graph-based methods with machine learning accelerates the search for complex reaction pathways.

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Mechanism search tools enhance cyclization understanding in natural products, suggesting improved reaction outcomes.

Casetti et al. (2025) studied this question.

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