7 papers
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…
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…
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…
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…
Rethinking Drug-Drug Interaction Modeling as Generalizable Relation Learning
Dong Xu, Jiantao Wu, Qihua Pan +3
Drug-drug interaction (DDI) prediction is central to drug discovery and clinical development, particularly in the context of increasingly prevalent polypharmacy. Although existing…
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…