ASKCOS: an open source software suite for synthesis planning

Zhengkai Tu, Sourabh J. Choure, Mun Hong Fong, Jihye Roh, Itai Levin +14 more
1/3/2025
cs.AI

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Abstract

The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. Here, we detail the newest version of ASKCOS, an open source software suite for synthesis planning that makes available several research advances in a freely available, practical tool. Four one-step retrosynthesis models form the basis of both interactive planning and automatic planning modes. Retrosynthetic planning is complemented by other modules for feasibility assessment and pathway evaluation, including reaction condition recommendation, reaction outcome prediction, and auxiliary capabilities such as solubility prediction and quantum mechanical descriptor prediction. ASKCOS has assisted hundreds of medicinal, synthetic, and process chemists in their day-to-day tasks, complementing expert decision making. It is our belief that CASP tools like ASKCOS are an important part of modern chemistry research, and that they offer ever-increasing utility and accessibility.

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@article{tu2025askcos,
  title  = {ASKCOS: an open source software suite for synthesis planning},
  author = {Zhengkai Tu and Sourabh J. Choure and Mun Hong Fong and Jihye Roh and Itai Levin and Kevin Yu and Joonyoung F. Joung and Nathan Morgan and Shih-Cheng Li and Xiaoqi Sun and Huiqian Lin and Mark Murnin and Jordan P. Liles and Thomas J. Struble and Michael E. Fortunato and Mengjie Liu and William H. Green and Klavs F. Jensen and Connor W. Coley},
  year   = {2025},
  eprint = {2501.01835},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2501.01835v1}
}

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