Chemically Induced Proximity for Targeted Protein O-GlcNAcylation

Abstract:
Protein O-linked β-N-acetylglucosamine modification (O-GlcNAcylation) plays a crucial role in regulating essential cellular processes. The disruption of O-GlcNAcylation homeostasis has been linked to various human diseases, including cancer, diabetes, and neurodegeneration. However, there are limited chemical tools for protein- and site-specific O-GlcNAc modification, rendering the precise study of O-GlcNAcylation challenging. To address this, we have developed bifunctional small molecules, named O-GlcNAcylation TArgeting Chimeras (OGTACs), which enable protein-specific O-GlcNAcylation in living cells. OGTACs promote O-GlcNAcylation of proteins such as p53, BRD4, CK2α, and EZH2 in cellulo by recruiting O-GlcNAc transferase (OGT), with temporal, magnitude, and reversible control. Overall, OGTACs represent a promising approach for inducing protein-specific O-GlcNAcylation, thus enabling functional dissection and offering new directions for O-GlcNAc-targeting therapeutic development.

Biographies:
Professor Billy Ng completed his postdoctoral training at Harvard Medical School and the University of Oxford, following his Ph.D. and B.Sc. (1st Hons) in Chemistry from The Chinese University of Hong Kong (CUHK). During his graduate studies, he was also a Fulbright Scholar at the Massachusetts Institute of Technology (MIT). He was recognized as a Young Global Leader by the World Economic Forum and received the Academic Young Investigator Award from the American Chemical Society (ACS) Division of Organic Chemistry.

Professor Ng’s research interests are chemical biology, drug discovery, and carbohydrate chemistry. He uses chemical and biological tools to develop novel small molecules for the treatment of various diseases, including cancers, infectious and neurodegenerative diseases. He has co-authored more than 30 papers in prestigious journals such as Science, Nature Chemical Biology, Molecular Cell, J. Am. Chem. Soc., Angew. Chem. Int. Ed., and ACS Central Science. His research has been funded by diverse sources, including the Bill & Melinda Gates Foundation, US National Academy of Medicine (NAM), the Innovation and Technology Fund (ITF), and Research Grants Council (RGC) of Hong Kong.

An Overview of AI-powered Drug Discovery

Abstract:
Artificial intelligence (AI) is revolutionizing drug discovery by enabling rapid exploration of vast chemical spaces and accurate modeling of complex molecular interactions that have long eluded conventional methods. State-of-the-art AI now powers de novo molecular design, ultra-large-scale virtual screening, and predictive assessment of druggability. Yet, real-world scientific datasets often suffer from sparsity, noise, severe label imbalance, and out-of-distribution shifts, limiting model reliability and generalization. In this talk, I will present our recent efforts to address these challenges by tightly integrating deep learning with physicochemical principles and multi-modal data. This hybrid paradigm yields significantly more robust and interpretable models for practical drug discovery. A highlight is our synthesis-aware generative framework, which seamlessly bridges computational design and experimental synthesis, reducing the full design-make-test-analyze cycle to under one month in a real-world test system. All presented in silico predictions are rigorously benchmarked and/or validated in the wet lab, demonstrating substantial gains in both model performance and real-world deployability.

Biographies:
Professor Chang-Yu (Kim) Hsieh is interested in computational science and interdisciplinary research, working at the interface of computational physics, quantum computing, artificial intelligence (AI), and drug discovery. He is currently the QiuShi Engineering Professor at the School of Pharmacy, Zhejiang University (since September 2022). His research centers on developing computational algorithms to simulate molecular interactions and accelerate the rational design of bioactive molecules, addressing the growing challenges of declining efficiency in pharmaceutical R&D. Several of his algorithms are currently being tested and applied by major pharmaceutical companies in China through collaboration with the startup CarbonSilicon AI.

Before joining Zhejiang University, Professor Hsieh led the Theory Division at Tencent Quantum Lab in Shenzhen, where he focused on integrating AI and quantum simulation for drug and material discovery. Previously, he conducted postdoctoral research in the Department of Chemistry at both MIT and the University of Toronto. Although his research focus has evolved from fundamental theory toward practical applications, his central interest remains to develop innovative computational algorithms for modeling the complex phenomena arised from atomic and molecular interactions.

Details

Professor Khuloud Al-Jamal, Lo Shiu Kwan Kan Po Ling Professor in Pharmacy & Global STEM Scholar, Department of Pharmacology and Pharmacy

8th December 2025 (Monday) at 10:00 am - 12:00 nn

Seminar Room 3,
G/F, Laboratory Block,
Faculty of Medicine Building,
21 Sassoon Road, Pokfulam
Hong Kong SAR, China

ALL ARE WELCOME