Chengwei Ai — accepted AI-conference papers

2026

Bridging the Biophysical Gap: Holistic Environmental Awareness for 3D Linker Design

Mengwei Sun, Chengwei Ai, Xiaoyi Liu, Shiqiang Ma, Qiaozhen Meng, Fei Guo

IJCAI 2026

3D molecular linker design is a critical task in structure-based drug discovery, which requires the precise synthesis of chemical bridges to connect fragments within the constrained environment of a protein binding pocket. Existing methods often suffer from environmental blindness, treating the inte

Cited by 0 Scholar ↗

2026

PharmaQA: Prompt-Based Molecular Representation Learning via Pharmacophore-Oriented Question Answering

Chengwei Ai, Qiaozhen Meng, Mengwei Sun, Ruihan Dong, Hongpeng Yang, Shiqiang Ma +3

AAAI 2026technical

Molecular representation plays a central role in computational drug discovery. Pharmacophores, functional groups responsible for molecular bioactivity, have been widely studied in cheminformatics. However, their incorporation into molecular representation learning, particularly in a context reasonin

Cited by 0 Source ↗PDF ↗Scholar ↗