NYU Shanghai student team NYU Ultra won Third Prize at the 2025 Shanghai International Computational Biology Innovation Competition, standing out among 118 teams worldwide with an AI-driven model for drug discovery.
This year’s challenge centered on HCAR1, a newly identified tumor immunotherapy target originally discovered by scientists in Shanghai. HCAR1 can sense lactate signals and help drive tumor immune escape, and related findings were published in February 2025 in Nature Immunology.
Competition teams were tasked with using AI methods to identify potential drug molecules based on HCAR1’s protein sequence and structural information, then pairing computational screening with experimental validation to help speed up translational progress toward clinical applications.
Guided by Professor John Zhang, Director Emeritus of the NYU-ECNU Center for Computational Chemistry at NYU Shanghai, and co-advised by Professor Zhaoxi Sun of Shenzhen University of Advanced Technology, the team was formed by NYU Shanghai Chemistry PhD student Lei Zheng and undergraduate Yizhe Dai ’23. In just nine days, the team developed and applied an in-house AI model that successfully screened micromolar-level HCAR1 inhibitors, demonstrating the speed and promise of AI tools in early-stage small-molecule discovery.
“This competition was valuable because it pushed us to connect computational innovation with real translational goals. It’s a strong example of how AI, when paired with scientific judgment and experimental validation, can help accelerate early-stage drug discovery,” said Professor Zhang. “I’m proud of our team’s execution under an extremely tight timeline. In nine days, they worked with focus and discipline, iterated quickly, and delivered results that reflect both technical skill and strong teamwork.”
Building on this momentum, the team is receiving a grant from the Shanghai Municipal Science and Technology Commission through its 2025 Computational Biology Special Program. The new support will enable further research and development of small-molecule drug candidates targeting GPCR proteins, a major class of therapeutically relevant receptors.