AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning
By Samuel Genheden, Amol Thakkar, Veronika Chadimová, Jean-Louis Reymond, Ola Engkvist, Esben Jannik Bjerrum. Journal of Cheminformatics, 2020
333 citations recorded by the source corpus.
We present the open-source AiZynthFinder software that can be readily used in retrosynthetic planning. The algorithm is based on a Monte Carlo tree search that recursively breaks down a molecule to purchasable precursors. The tree search is guided by an artificial neural network policy that suggests possible precursors by utilizing a library of known reaction templates. The software is fast and can typically find a solution in less than 10 s and perform a complete search in less than 1 min. Moreover, the development of the code was guided by a range of software engineering principles such as automatic testing, system design and continuous integration leading to robust software with high maintainability. Finally, the software is well documented to make it suitable for beginners. The software is available at http://www.github.com/MolecularAI/aizynthfinder .
Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/32cd4fe7634fcc79d36b8e08fd2b7f9677460e99
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Citations in the corpus
- Augmenting large language models with chemistry tools (2023, background): “Integrating such tools tends to occur within isolated environments, such as RXN for Chemistry 18,24,46–48 and AIZynthFinder 25,49,50 , facilitated by corporate directives that promote integrability.”