2024
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.
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.
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.
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.
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.
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.
2023
SE(3) equivariant message passing via two-stage decomposition
Jiahan Li, Chaoran Cheng
Technical Report 2023
Applying our equivariant message passing (Luo*, Li*, et al., CVPR'22) to chemistry and physics tasks.
2022
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.
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.
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.