Research

段宏亮 Duan Hongliang

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 Biography

Dr. Hongliang Duan, received his PhD in Medicinal Chemistry from Shanghai Institute of Materia Medica, Chinese Academy of Sciences in 2012, and a master's degree in artificial intelligence from Oklahoma City University, USA. From 2018 to 2023, he served as a professor and director at the Artificial Intelligence Aided  Drug Discovery Institute in Zhejiang University of Technology.

Since 2023, he has been an associate professor at Macao Polytechnic University. His academic research mainly combines pharmaceutical big data with artificial intelligence technology, and is committed to using AI technology to assist in traditional drug discovery and synthesis. He has published more than twenty high-level academic papers as the first or corresponding author, and has led multiple projects including National Natural Science Foundation and Zhejiang Natural Science Foundation. He is the editor-in-chief of the book "Computational Pharmacy" on AI pharmaceuticals, and the translator of "Artificial Intelligence in Drug Design".

In the aspect of integrating industry, academia and research, several innovative drug projects have achieved good industrial transformation. Among them, the antidiabetic drug developed as a core member was sold to the French pharmaceutical company Servier, and three new first-class drugs developed as main members are currently in the clinical research stage.

 Education and Experiences

Education:
2016-2017:  Master of Artificial Intelligence, Oklahoma City University      
2009-2012:  Doctor of Medicinal Chemistry, Shanghai Institute of Materia Medica
2006-2009:  Master of Medicinal Chemistry, Shanghai Institute of Materia Medica
2002-2006:  Bachelor in Pharmacy, Jinan University

Professional experiences:
2023-Present:  Associate Professor, Macao Polytechnic University
2018-2023:    Professor, Zhejiang University of Technology
2013-2016:    Post-doctoral, Oklahoma Medical Research Foundation    
2012-2013:    Senior Scientist, Wuxi AppTec Co., Ltd.

 Research Interests

• Artificial Intelligence Aided Drug Discovery
• Intelligent Drug Synthesis

 Selected Recent Publications (First or corresponding author)

1. S. Zhai; Y. Tan; C Zhang; C. Hipolito; L. Song; C. Zhu; Y. Zhang; H. Duan*; Y. Yin*. PepScaf: Harnessing Machine Learning with In Vitro Selection toward De Novo Macrocyclic Peptides against IL-17C/IL-17RE Interaction. J.Med.Chem. 2023, 66, 16, 11187-11200.
2. Z. Wu; X. Cai; C. Zhang; H. Qiao; Y. Wu; Y. Zhang; X. Wang; H. Xie; F. Luo; H. Duan*. Self-Supervised Molecular Pretraining Strategy for Low-Resource Reaction Prediction Scenarios. J. Chem. Inf. Model. 2022, 62, 4579-4590.
3. A. Su; X. Wang; L. Wang; C. Zhang; Y. Wu; X. Wu; Q. Zhao; H. Duan*. Reproducing the invention of a named reaction: zero-shot prediction of unseen chemical reactions. Phys. Chem. Chem. Phys. 2022, 17, 10280-10291.
4. X. Wang; C. Yao; Y. Zhang; J. Yu; H. Qiao; C. Zhang; Y. Wu; R. Bai; H. Duan*. From theory to experiment: transformer-based generation enables rapid discovery of novel reactions. J. Cheminformatics. 2022, 14, 60-71.
5. J. Xu; Y. Zhang; J. Han; A. Su; H. Qiao; C. Zhang; J. Tang; X. Shen; B. Sun; W. Yu;  S. Zhai; X. Wang; Y. Wu; W. Su; Hongliang Duan*. Providing direction for mechanistic inferences in radical cascade cyclization using a Transformer model, Org. Chem. Front. 2022, 9, 2498-2508.
6. X. Wu; Y. Zhang; J. Yu; C. Zhang; H. Qiao; Y. Wu; X. Wang; Z. Wu; H. Duan*. Virtual data augmentation method for reaction prediction. Sci. Rep. 2022, 12, 17098-17109.
7. Y. Wu; C. Zhang, L. Wang; H. Duan*. A graph-convolutional neural network for addressing small-scale reaction prediction. Chem. Commun. 2021, 57, 4114–4117.
8. Y. Zhang; L. Wang; X. Wang; A. Su; H. Duan*. Data augmentation and transfer learning strategies for reaction prediction in low chemical data regimes. Org. Chem. Front. 2021, 8, 1415–1423.