most citedPharmAgents: Building a Virtual Pharma with Large Language Model Agents

2 citations · 2 across the 2 of their papers we have counts for

collaborators

6 papers

cs.LG2025

SDrug: Bridging Protein Sequence and 3D Structure in Contrastive Representation Learning for Virtual Screening

Bowei He, Bowen Gao, Yankai Chen +5

Virtual screening (VS) is an essential task in drug discovery, focusing on the identification of small-molecule ligands that bind to specific protein pockets. Existing deep learnin…

cs.LG2025

Coder as Editor: Code-driven Interpretable Molecular Optimization

Wenyu Zhu, Chengzhu Li, Xiaohe Tian +7

Molecular optimization is a central task in drug discovery that requires precise structural reasoning and domain knowledge. While large language models (LLMs) have shown promise in…

cs.LG2025

Learning Protein-Ligand Binding in Hyperbolic Space

Jianhui Wang, Wenyu Zhu, Bowen Gao +4

Protein-ligand binding prediction is central to virtual screening and affinity ranking, two fundamental tasks in drug discovery. While recent retrieval-based methods embed ligands…

cs.LG2025

AANet: Virtual Screening under Structural Uncertainty via Alignment and Aggregation

Wenyu Zhu, Jianhui Wang, Bowen Gao +5

Virtual screening (VS) is a critical component of modern drug discovery, yet most existing methods--whether physics-based or deep learning-based--are developed around holo protein…

q-bio.BM20252 cited

PharmAgents: Building a Virtual Pharma with Large Language Model Agents

Bowen Gao, Yanwen Huang, Yiqiao Liu +4

The discovery of novel small molecule drugs remains a critical scientific challenge with far-reaching implications for treating diseases and advancing human health. Traditional dru…

q-bio.BM2025

Pushing the boundaries of Structure-Based Drug Design through Collaboration with Large Language Models

Bowen Gao, Yanwen Huang, Yiqiao Liu +4

Structure-Based Drug Design (SBDD) has revolutionized drug discovery by enabling the rational design of molecules for specific protein targets. Despite significant advancements in…