collaborators

6 papers

q-bio.BM2026

DegradeQuery: Counterfactual Tuple Pretraining for Context-Aware PROTAC Degradation Prediction

Dong Xu, Zhangfan Yang, Jiantao Wu +3

Proteolysis-targeting chimeras (PROTACs) induce protein degradation by recruiting a target protein to an E3 ubiquitin ligase, making degradation a joint outcome of the degrader mol…

cs.AI2026

Toward Closed-loop Molecular Discovery via Language Model, Property Alignment and Strategic Search

Junkai Ji, Zhangfan Yang, Dong Xu +4

Drug discovery is a time-consuming and expensive process, with traditional high-throughput and docking-based virtual screening hampered by low success rates and limited scalability…

q-bio.BM2026

FROGENT: An End-to-End Full-process Drug Design Multi-Agent System

Qihua Pan, Dong Xu, Qianwei Yang +5

Drug discovery is a complex, multi-step pipeline that remains heavily dependent on manual, experience-driven operations; meanwhile, existing customized artificial intelligence tool…

cs.LG2026

Unveiling Scaling Behaviors in Molecular Language Models: Effects of Model Size, Data, and Representation

Dong Xu, Qihua Pan, Sisi Yuan +3

Molecular generative models, often employing GPT-style language modeling on molecular string representations, have shown promising capabilities when scaled to large datasets and mo…

cs.LG2026

From Tokens to Blocks: A Block-Diffusion Perspective on Molecular Generation

Qianwei Yang, Dong Xu, Zhangfan Yang +4

Drug discovery can be viewed as a combinatorial search over an immense chemical space, motivating the development of deep generative models for de novo molecular design. Among thes…

q-bio.BM2025

READ: A Retrieval-Alignment Diffusion Framework for Structure-based Drug Design

Dong Xu, Zhangfan Yang, Junchuang Cai +6

Structure-based drug design (SBDD) models are central to modern pharmaceutical research, enabling the rational exploration of protein-ligand interactions at atomic resolution. Howe…