I received my Ph.D. in 2023 from the University of Chinese Academy of Sciences. My research focuses on computational drug discovery and molecular design, combining computational chemistry, computational biology, and artificial intelligence to accelerate protein engineering and small-molecule drug discovery.
My current research interests include:
- generative AI for de novo protein design;
- virtual screening and molecular design based on CADD and AIDD;
- molecular mechanism studies of enzymes and GPCRs using molecular simulations.
More details are available on the lab website and my Google Scholar profile.
🔥 News
- 2025: Our work on generative-AI-designed haloalkane dehalogenase variants was published in Journal of the American Chemical Society.
- 2025: Sacrificing Knight for Pawn-Queen Promotion: Sonosensitive Nano-Xanthiums Orchestrate NO to Retain H2O2 for Antibiofilm Therapy was published in Advanced Materials.
- 2024: Our perspective article “Computational drug development for membrane protein targets” was published in Nature Biotechnology.
- 2024: Our work on machine-learning-based kinetic and thermodynamic prediction was published in Journal of Chemical Theory and Computation.
- 2024: Our perspective “Will the hype of automated drug discovery finally be realized?” was published in Expert Opinion on Drug Discovery.
📝 Publications
Natalia Gelfand, Vojtech Orel, Wenqiang Cui, Jiri Damborsky, Chenglong Li, Zbynek Prokop, Wen Jun Xie, Arieh Warshel
- A representative study on using generative AI to support enzyme and protein design with combined biochemical and computational validation.
Computational Drug Development for Membrane Protein Targets
Haijian Li, Xiaolin Sun, Wenqiang Cui, Marc Xu, Junlin Dong, Babatunde Edukpe Ekundayo, Dongchun Ni, Zhili Rao, Liwei Guo, Henning Stahlberg, Shuguang Yuan, Horst Vogel
- A broad perspective on computational strategies for membrane-protein-targeted drug development, integrating structure, simulation, and practical discovery workflows.
Junlin Dong, Shiyu Wang, Wenqiang Cui, Xiaolin Sun, Haojie Guo, Hailu Yan, Horst Vogel, Zhi Wang, Shuguang Yuan
- A machine-learning framework for accurate kinetic and thermodynamic prediction in molecular mechanism studies.
- Will the Hype of Automated Drug Discovery Finally Be Realized?, Wenqiang Cui, Shuguang Yuan, Expert Opinion on Drug Discovery, 2024
- Molecular Basis of Ligand Selectivity for Melatonin Receptors, Wenqiang Cui, Junlin Dong, Shiyu Wang, Horst Vogel, Rongfeng Zou, Shuguang Yuan, RSC Advances, 2023
Email: wenqiang.cui “AT” ufl.edu