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

1 citations · 1 across the 10 of their papers we have counts for

collaborators

11 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.IR2026

SLSREC: Self-Supervised Contrastive Learning for Adaptive Fusion of Long- and Short-Term User Interests

Wei Zhou, Yue Shen, Junkai Ji +5

User interests typically encompass both long-term preferences and short-term intentions, reflecting the dynamic nature of user behaviors across different timeframes. The uneven tem…

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

RIGA-Fold: A General Framework for Protein Inverse Folding via Recurrent Interaction and Geometric Awareness

Sisi Yuan, Jiehuang Chen, Junchuang Cai +4

Protein inverse folding, the task of predicting amino acid sequences for desired structures, is pivotal for de novo protein design. However, existing GNN-based methods typically su…

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…