Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits

@article{Sacha2020MoleculeEG,
  title={Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits},
  author={Mikolaj Sacha and Mikolaj Blaz and Piotr Byrski and Pawel Wlodarczyk-Pruszynski and Stanislaw Jastrzebski},
  journal={Journal of chemical information and modeling},
  year={2020}
}
The central challenge in automated synthesis planning is to be able to generate and predict outcomes of a diverse set of chemical reactions. In particular, in many cases, the most likely synthesis pathway cannot be applied due to additional constraints, which requires proposing alternative chemical reactions. With this in mind, we present Molecule Edit Graph Attention Network (MEGAN), an end-to-end encoder-decoder neural model. MEGAN is inspired by models that express a chemical reaction as a… 

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