Journal of Cheminformatics (May 2024)

AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application

  • Lakshidaa Saigiridharan,
  • Alan Kai Hassen,
  • Helen Lai,
  • Paula Torren-Peraire,
  • Ola Engkvist,
  • Samuel Genheden

DOI
https://doi.org/10.1186/s13321-024-00860-x
Journal volume & issue
Vol. 16, no. 1
pp. 1 – 11

Abstract

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Abstract We present an updated overview of the AiZynthFinder package for retrosynthesis planning. Since the first version was released in 2020, we have added a substantial number of new features based on user feedback. Feature enhancements include policies for filter reactions, support for any one-step retrosynthesis model, a scoring framework and several additional search algorithms. To exemplify the typical use-cases of the software and highlight some learnings, we perform a large-scale analysis on several hundred thousand target molecules from diverse sources. This analysis looks at for instance route shape, stock usage and exploitation of reaction space, and points out strengths and weaknesses of our retrosynthesis approach. The software is released as open-source for educational purposes as well as to provide a reference implementation of the core algorithms for synthesis prediction. We hope that releasing the software as open-source will further facilitate innovation in developing novel methods for synthetic route prediction. AiZynthFinder is a fast, robust and extensible open-source software and can be downloaded from https://github.com/MolecularAI/aizynthfinder .

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