Recent advances in artificial intelligence for retrosynthesis
- URL: http://arxiv.org/abs/2301.05864v1
- Date: Sat, 14 Jan 2023 09:29:39 GMT
- Title: Recent advances in artificial intelligence for retrosynthesis
- Authors: Zipeng Zhong, Jie Song, Zunlei Feng, Tiantao Liu, Lingxiang Jia,
Shaolun Yao, Tingjun Hou, Mingli Song
- Abstract summary: Retrosynthesis is the cornerstone of organic chemistry, providing chemists in material and drug manufacturing access to poorly available and brand-new molecules.
Recent breakthroughs driven by artificial intelligence have revolutionized retrosynthesis.
- Score: 29.32667622776065
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Retrosynthesis is the cornerstone of organic chemistry, providing chemists in
material and drug manufacturing access to poorly available and brand-new
molecules. Conventional rule-based or expert-based computer-aided synthesis has
obvious limitations, such as high labor costs and limited search space. In
recent years, dramatic breakthroughs driven by artificial intelligence have
revolutionized retrosynthesis. Here we aim to present a comprehensive review of
recent advances in AI-based retrosynthesis. For single-step and multi-step
retrosynthesis both, we first list their goal and provide a thorough taxonomy
of existing methods. Afterwards, we analyze these methods in terms of their
mechanism and performance, and introduce popular evaluation metrics for them,
in which we also provide a detailed comparison among representative methods on
several public datasets. In the next part we introduce popular databases and
established platforms for retrosynthesis. Finally, this review concludes with a
discussion about promising research directions in this field.
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