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- W3101473090 abstract "<div>Retrosynthesis is the process of recursively decomposing target molecules into available building blocks. It plays an important role in solving problems in organic synthesis planning. To automate the retrosynthesis analysis, many retrosynthesis prediction methods have been proposed.</div><div>However, most of them are cumbersome and lack interpretability about their predictions.</div><div>In this paper, we devise a novel template-free algorithm, RetroXpert, for automatic retrosynthetic expansion by automating the procedure that chemists used to do.</div><div>Our method disassembles retrosynthesis into two steps: i) we identify the potential reaction center within the target molecule through a graph neural network and generate intermediate synthons; and ii) we predict the associated reactants based on the obtained synthons via a reactant generation model. </div><div>While outperforming the state-of-the-art baselines by a significant margin, our model also provides chemically reasonable interpretation.</div>" @default.
- W3101473090 created "2020-11-23" @default.
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- W3101473090 date "2020-11-05" @default.
- W3101473090 modified "2023-10-18" @default.
- W3101473090 title "RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist" @default.
- W3101473090 doi "https://doi.org/10.26434/chemrxiv.11869692.v5" @default.
- W3101473090 hasPublicationYear "2020" @default.
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