12 papers
Cross-Chirality Generalization by Axial Vectors for Hetero-Chiral Protein-Peptide Interaction Design
Ziyi Yang, Zitong Tian, Yinjun Jia +7
D-peptide binders targeting L-proteins have promising therapeutic potential. Despite rapid advances in machine learning-based target-conditioned peptide design, generating D-peptid…
MolEvolve: LLM-Guided Evolutionary Search for Interpretable Molecular Optimization
Xiangsen Chen, Ruilong Wu, Yanyan Lan +2
Despite deep learning's success in chemistry, its impact is hindered by a lack of interpretability and an inability to resolve activity cliffs, where minor structural nuances trigg…
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…
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…
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…
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…