Tango*: Constrained synthesis planning using chemically informed value functions
Armstrong, Daniel, Joncev, Zlatko, Guo, Jeff, Schwaller, Philippe
–arXiv.org Artificial Intelligence
Computer-aided synthesis planning (CASP) has made significant strides in generating retrosynthetic pathways for simple molecules in a non-constrained fashion. Recent work introduces a specialised bidirectional search algorithm with forward and retro expansion to address the starting material-constrained synthesis problem, allowing CASP systems to provide synthesis pathways from specified starting materials, such as waste products or renewable feed-stocks. In this work, we introduce a simple guided search which allows solving the starting material-constrained synthesis planning problem using an existing, uni-directional search algorithm, Retro*. We show that by optimising a single hyperparameter, Tango* outperforms existing methods in terms of efficiency and solve rate. We find the Tango* cost function catalyses strong improvements for the bidirectional DESP methods. Our method also achieves lower wall clock times while proposing synthetic routes of similar length, a common metric for route quality.
arXiv.org Artificial Intelligence
Dec-4-2024
- Country:
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- North America > United States
- California > Orange County > Anaheim (0.04)
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- Research Report > New Finding (0.46)
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- Health & Medicine > Pharmaceuticals & Biotechnology (0.68)
- Materials > Chemicals (0.46)
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