Designing Cyclic Peptides via Harmonic SDE with Atom-Bond Modeling

Xiangxin Zhou, Yi Xiao, Mingyu Li, Jiahan Li, Dongyu Xue, Zaixiang Zheng, Jianzhu Ma, Quanquan Gu

International Conference on Machine Learning (ICML) 2025

Designing any type of cyclic peptide vias full-atom diffusion modeling.

Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension

Jiahan Li*, Tong Chen*, Shitong Luo, Chaoran Cheng, Jiaqi Guan, Ruihan Guo, Sheng Wang, Ge Liu, Jian Peng, Jianzhu Ma (* equal contribution)

International Conference on Learning Representations（ICLR) 2025

The first multi-stage method combining energy-based models with autoregressive dihedral prediction for peptide binder design.

[paper]

Group Ligands Docking to Protein Pockets

Jiaqi Guan*, Jiahan Li*, Xiangxin Zhou, Xingang Peng, Sheng Wang, Yunan Luo, Jian Peng, Jianzhu Ma (* equal contribution)

International Conference on Learning Representations（ICLR) 2025

Enhance blind docking with the use of other ligands in the target group.

Geometric Point Attention Transformer for 3D Shape Reassembly

Jiahan Li*, Chaoran Cheng*, Jianzhu Ma, Ge Liu (* equal contribution)

Under Review.

Solving 3D part assembly with the use of Invariant Geometric Point Attention and Pose Recycling.

[Paper]

Enhancing Protein Mutation Effect Prediction through a Retrieval-Augmented Framework

Ruihan Guo*, Rui Wang*, Ruidong Wu*, Zhizhou Ren, Jiahan Li, Shitong Luo, Zuofan Wu, Qiang Liu, Jian Peng, Jianzhu Ma (* equal contribution)

Conference and Workshop on Neural Information Processing Systems (NeurIPS) 2024

A retrieval-augmented model to improve protein mutation predictions by using local structure motif emebddings.

[Proceedings]

Categorical Flow Matching on Statistical Manifolds

Chaoran Cheng*, Jiahan Li*, Jian Peng, Ge Liu (* equal contribution)

Conference and Workshop on Neural Information Processing Systems (NeurIPS) 2024

A novel flow matching framework on the manifold of parameterized probability measures for discrete generation.

[paper] [Code] [Proceedings]

Full-Atom Peptide Design based on Multi-modal Flow Matching

Jiahan Li*, Chaoran Cheng*, Zuofan Wu, Ruihan Guo, Shitong Luo, Zhizhou Ren, Jian Peng, Jianzhu Ma (* equal contribution)

International Conference on Machine Learning (ICML) 2024

The first multi-modal multi-task flow matching method for target-specific full-atom peptide design and analysis.

[paper] [Code] [Proceedings]

FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames

Ruidong Wu*, Ruihan Guo*, Rui Wang*, Shitong Luo, Yue Xu, Jiahan Li, Jianzhu Ma, Qiang Liu, Yunan Luo, Jian Peng (* equal contribution)

International Conference on Machine Learning (ICML) 2024 Spotlight

Replacing AF2's FAPE loss with SE(3) group-aware geodesic loss.

[paper] [Proceedings] [Code]

Proximal Exploration for Model-guided Protein Sequence Design

Zhizhou Ren*, Jiahan Li*, Fan Ding, Yuan Zhou, Jianzhu Ma, Jian Peng (* equal contribution)

International Conference on Machine Learning (ICML) 2022 Spotlight

Addressing model-guided sequence design using evolutionary search to find high-fitness mutants with low mutation counts.

[Paper] [Code] [Proceedings]

Orientation-Aware Graph Neural Networks for Protein Structure Representation Learning

Jiahan Li*, Shitong Luo*, Congyue Deng*, Chaoran Cheng*, Jiaqi Guan, Leonidas Guibas, Jian Peng, Jianzhu Ma (* equal contribution)

International Conference on Research in Computational Molecular Biology (RECOMB) 2025

A new type of vector-based neural network combines directional 3D weights with equivariant message passing.

[Paper]

Equivariant Point Cloud Analysis via Learning Orientations for Message Passing

Shitong Luo*, Jiahan Li*, Jiaqi Guan*, Yufeng Su, Chaoran Cheng, Jian Peng, Jianzhu Ma (* equal contribution)

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022 Oral

Learning virtual orientations for each point. Projecting neighbor points to local orientations before aggregating information from them.

[Paper] [Code] [Proceedings]