2024
DOI: 10.1021/acs.jcim.4c00104
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3DReact: Geometric Deep Learning for Chemical Reactions

Puck van Gerwen,
Ksenia R. Briling,
Charlotte Bunne
et al.

Abstract: Geometric deep learning models, which incorporate the relevant molecular symmetries within the neural network architecture, have considerably improved the accuracy and data efficiency of predictions of molecular properties. Building on this success, we introduce 3DREACT, a geometric deep learning model to predict reaction properties from three-dimensional structures of reactants and products. We demonstrate that the invariant version of the model is sufficient for existing reaction data sets. We illustrate its… Show more

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