Chinese Journal of Organic Chemistry ›› 2020, Vol. 40 ›› Issue (11): 3812-3827.DOI: 10.6023/cjoc202006051 Previous Articles     Next Articles


刘伊迪, 杨骐, 李遥, 张龙, 罗三中   

  1. 清华大学化学系 基础分子科学中心 北京 100084
  • 收稿日期:2020-06-24 修回日期:2020-07-22 发布日期:2020-08-06
  • 通讯作者: 张龙, 罗三中;
  • 基金资助:

Application of Machine Learning in Organic Chemistry

Liu Yidi, Yang Qi, Li Yao, Zhang Long, Luo Sanzhong   

  1. Center for Basic Molecular Science, Department of Chemistry, Tsinghua University, Beijing 100084
  • Received:2020-06-24 Revised:2020-07-22 Published:2020-08-06
  • Supported by:
    Project supported by the National Science & Technology Fundamental Resource Investigation Program of China (No. 2018FY201200), the Tsinghua University Initiative Scientific Research Program (No. 2019Z07L01005) and the Natural Science Foundation of China (Nos. 22031006, 21672217, 21933008).

Driven by nowadays’ computing power, big data technology as well as learning algorithm, artificial intelligence (AI) has gained trenmendous attentions and become a transformative approach in many research areas. One of the most extensively explored AI approaches in chemistry is (deep) machine learning, which provides new twists in the fields of organic chemistry. The workflow of machine learning (ML) study in organic chemistry is briefly introduced. Meanwhile, the application of ML in the accurate prediction of chemical properties, molecular de novo design, chemical reaction prediction, retrosynthetic analysis and artificial intelligence synthetic machine are also summarized. In the end, the current challenges in this field are analyzed and discussed.

Key words: machine learning, molecular descriptor, algorithm, chemical property prediction, de novo design, chemical reaction prediction, retrosynthesis analysis