Yuanhuan Mo — accepted AI-conference papers

2026

Drugging the Undruggable: Benchmarking and Modeling Fragment-Based Screening

Haichuan Tan, Bowen Gao, Jiaxin Li, Yinjun Jia, Wenyu Zhu, Wenxuan Xie +7

ICLR 2026poster

A significant portion of disease-relevant proteins remain undruggable due to shallow, flexible, or otherwise ill-defined binding pockets that hinder conventional molecule screening. Fragment-based drug discovery (FBDD) offers a promising alternative, as small, low-complexity fragments can flexibly e…

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2025

FIGRDock: Fast Interaction-Guided Regression for Flexible Docking

Shikun Feng, Bicheng Lin, Yuanhuan Mo, Yuyan Ni, Wenyu Zhu, Bowen Gao +3

NeurIPS 2025poster

Flexible docking, which predicts the binding conformations of both proteins and small molecules by modeling their structural flexibility, plays a vital role in structure-based drug design. Although recent generative approaches, particularly diffusion-based models, have shown promising results, they…

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