Tango*: constrained synthesis planning using chemically informed value functions
Computer-aided synthesis planning (CASP) has made significant strides in generating retrosynthetic pathways for simple molecules in a non-constrained fashion. Recent work has introduced specialized bidirectional search algorithms to find synthesis pathways that incorporate pre-selected starting materials, tackling a specific formulation of the starting material-constrained problem. In this work, we introduce a simple guided search-Tango*-which allows solving the starting material-constrained synthesis planning problem using an existing unidirectional search algorithm, Retro*. We show that by optimising a single hyperparameter, Tango* outperforms existing methods in terms of efficiency and solve rate. We also highlight the effectiveness of our computed node cost function in steering synthesis pathways.
Authors
- Jeff Guo (ORCID: https://orcid.org/0000-0002-4633-3199)
- Philippe Schwaller (ORCID: https://orcid.org/0000-0003-3046-6576)
- D. M. Armstrong (ORCID: https://orcid.org/0009-0009-3813-6900)
- Zlatko Jončev
Institutions
- NCCR Chemical Biology - Visualisation and Control of Biological Processes Using Chemistry (CH)
- École Polytechnique Fédérale de Lausanne (CH)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00130g
- Primary Topic
- Chemistry and Chemical Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung