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UniZyme: A Unified Protein Cleavage Site Predictor Enhanced with Enzyme Active-Site Knowledge
Published in NeurIPS 2025, 2025
We introduce UniZyme, a unified protein cleavage site predictor that generalizes across diverse enzymes using a biochemically-informed model architecture with active-site knowledge of proteolytic enzymes.
Recommended citation: Chenao Li, Shuo Yan, Enyan Dai. (2025). "UniZyme: A Unified Protein Cleavage Site Predictor Enhanced with Enzyme Active-Site Knowledge." NeurIPS 2025.
Protap: General Protein Pretraining or Domain-Specific Designs? Benchmarking Protein Modeling on Realistic Applications
Published in arXiv, 2025
Protap is a comprehensive benchmark comparing backbone architectures, pretraining strategies, and domain-specific models across diverse realistic downstream protein applications.
Recommended citation: Shuo Yan, Yuliang Yan, Bin Ma, Chenao Li, Haochun Tang, Jiahua Lu, Minhua Lin, Yuyuan Feng, Enyan Dai. (2025). "Protap: Benchmarking Protein Modeling on Realistic Applications." arXiv:2506.02052.
FlexRibbon: Joint Sequence and Structure Pretraining for Protein Modeling
Published in ICLR 2026, 2025
FlexRibbon is a pretrained protein model that jointly learns from amino acid sequences and 3D structures, achieving SOTA on 12 different tasks.
Recommended citation: Jianwei Zhu, Yu Shi, ..., Chenao Li, ..., Tao Qin. (2025). "FlexRibbon: Joint Sequence and Structure Pretraining for Protein Modeling." ICLR 2026.
TCRAD: An End-to-End Framework for Antigen-Targeted T Cell Receptor Design
Published in bioRxiv(Under review in Briefings in Bioinformatics), 2026
TCRAD is an end-to-end deep learning framework for de novo design of antigen-specific TCR CDR3β sequences, with experimental validation showing 17.2% of designed TCRs elicited antigen-induced activation.
Recommended citation: Chenao Li, Yaochi Guo, Xin Guan, Hui Chen, Yong Zhang, Pengyuan Yang, Jizhong Lou. (2026). "TCRAD: An End-to-End Framework for Antigen-Targeted T Cell Receptor Design." bioRxiv.