DirectMultiStep: Direct Route Generation for Multi-Step Retrosynthesis

• URL: http://arxiv.org/abs/2405.13983v2
• Date: Tue, 21 Jan 2025 17:37:07 GMT
• Title: DirectMultiStep: Direct Route Generation for Multi-Step Retrosynthesis
• Authors: Yu Shee, Haote Li, Anton Morgunov, Victor Batista,
• Abstract summary: We introduce a series of transformer-based models, utilizing mixture of experts approach, that directly generate multistep synthetic routes as a single string. Our models can accommodate specific conditions such as the desired number of steps and starting materials. Top-performing DMS-Flex (Duo) surpassing state-of-the-art methods on the PaRoutes dataset with a 2.5x improvement in Top-1 accuracy.
• Score: 0.0
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• Abstract: Traditional computer-aided synthesis planning (CASP) methods rely on iterative single-step predictions, leading to exponential search space growth that limits efficiency and scalability. We introduce a series of transformer-based models, utilizing mixture of experts approach, that directly generate multistep synthetic routes as a single string by conditionally predicting each molecule based on all preceding ones. Our models can accommodate specific conditions such as the desired number of steps and starting materials, with the top-performing DMS-Flex (Duo) surpassing state-of-the-art methods on the PaRoutes dataset with a 2.5x improvement in Top-1 accuracy on the n$_1$ test set and a 3.9x improvement on the n$_5$ test set. It also successfully predicts routes for FDA-approved drugs not included in the training data, showcasing its generalization capabilities. While the current suboptimal diversity of the training set may impact performance on less common reaction types, our multistep-first approach presents a promising direction towards fully automated retrosynthetic planning.

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