collaborators

7 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

BioLM-Score: Language-Prior Conditioned Probabilistic Geometric Potentials for Protein-Ligand Scoring

Zhangfan Yang, Baoyun Chen, Dong Xu +4

Protein-ligand scoring is a central component of structure-based drug design, underpinning molecular docking, virtual screening, and pose optimization. Conventional physics-based e…

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…

cs.LG2025

IBEX: Information-Bottleneck-EXplored Coarse-to-Fine Molecular Generation under Limited Data

Dong Xu, Zhangfan Yang, Jenna Xinyi Yao +3

Three-dimensional generative models increasingly drive structure-based drug discovery, yet it remains constrained by the scarce publicly available protein-ligand complexes. Under s…

q-bio.BM2025

MODA: A Unified 3D Diffusion Framework for Multi-Task Target-Aware Molecular Generation

Dong Xu, Zhangfan Yang, Sisi Yuan +3

Three-dimensional molecular generators based on diffusion models can now reach near-crystallographic accuracy, yet they remain fragmented across tasks. SMILES-only inputs, two-stag…