activity
20232026
most citedFull-Atom Peptide Design with Geometric Latent Diffusion

4 citations · 13 across the 8 of their papers we have counts for

collaborators

10 papers

cs.LG2026

Scalable Peptide Design via Memory-Efficient Equivariant Transformer

Rui Jiao, Xiangzhe Kong, Yinjun Jia +4

Target-specific peptide design requires sequence and structure co-design under full atom geometric constraints. Latent generative frameworks offer an effective route for this probl…

q-bio.BM2026

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…

cs.LG2025

Coder as Editor: Code-driven Interpretable Molecular Editing

Wenyu Zhu, Chengzhu Li, Xiaohe Tian +8

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

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…

cs.LG2025

Manipulating 3D Molecules in a Fixed-Dimensional E(3)-Equivariant Latent Space

Zitao Chen, Yinjun Jia, Zitong Tian +2

Medicinal chemists often optimize drugs considering their 3D structures and designing structurally distinct molecules that retain key features, such as shapes, pharmacophores, or c…

physics.chem-ph2024

MoleculeCLA: Rethinking Molecular Benchmark via Computational Ligand-Target Binding Analysis

Shikun Feng, Jiaxin Zheng, Yinjun Jia +4

Molecular representation learning is pivotal for various molecular property prediction tasks related to drug discovery. Robust and accurate benchmarks are essential for refining an…

q-bio.BM2024★ 2 cited

SIU: A Million-Scale Structural Small Molecule-Protein Interaction Dataset for Unbiased Bioactivity Prediction

Yanwen Huang, Bowen Gao, Yinjun Jia +4

Small molecules play a pivotal role in modern medicine, and scrutinizing their interactions with protein targets is essential for the discovery and development of novel, life-savin…

cs.LG2024★ 3 cited

Multi-level Interaction Modeling for Protein Mutational Effect Prediction

Yuanle Mo, Xin Hong, Bowen Gao +2

Protein-protein interactions are central mediators in many biological processes. Accurately predicting the effects of mutations on interactions is crucial for guiding the modulatio…

q-bio.BM2024★ 4 cited

Full-Atom Peptide Design with Geometric Latent Diffusion

Xiangzhe Kong, Yinjun Jia, Wenbing Huang +1

Peptide design plays a pivotal role in therapeutics, allowing brand new possibility to leverage target binding sites that are previously undruggable. Most existing methods are eith…

q-bio.BM2023★ 4 cited

Protein-ligand binding representation learning from fine-grained interactions

Shikun Feng, Minghao Li, Yinjun Jia +2

The binding between proteins and ligands plays a crucial role in the realm of drug discovery. Previous deep learning approaches have shown promising results over traditional comput…