Author

Shizhang Wan

Tsinghua University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Molecular Biology· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Approach:contrastive learning· 1 Research Focus:drug response / drug discovery· 1 Approach:graph neural network· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Assay:protein structure· 1

Frequent Co-Authors

Jiqing ZhengiD· 2 shared Bin LiiD· 1 shared Chaoran ChengiD· 1 shared Chunhao Zhu· 1 shared Cui Yunxia· 1 shared Guiyu Guan· 1 shared Hao Zhang· 1 shared Haoxiang LiiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersMolecular Biology

Jiqing ZhengORCID

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2 papers

Recent·Most cited

Accurate de novo design of peptides from programming biophysical landscape

Mingyu Li, Yini Liu, Jie Zhong, Xinchao Shi, Jiqing Zheng, Kai Wang, Cui Yunxia, Chaoran Cheng, Shijin Li, Xiangzhe Kong, S W Li, Miaojie Xv, Chunhao Zhu, Xiaobing Lan, He Yang, , Jian Zhang

NeoPep designs functional peptides de novo using a deep-learning framework that models biophysical principles, achieving high hit rates and structural accuracy across diverse targets.

bioRxiv · Jun 9, 2026 · PreprintMolecular Biology

MFPLI: A Computational Framework for Assessing Biological Authenticity of Protein-Ligand Interactions Using Molecular Fingerprints and Structural Features

Hao Zhang, Jiqing Zheng, Haoxiang Li, Shizhang Wan, Guiyu Guan, Bin Li, Lei Liu, Wei He

MFPLI evaluates protein-ligand binding authenticity using deep learning with physicochemical and structural features, achieving high accuracy in distinguishing native conformations from docking poses.

bioRxiv · Jun 19, 2025 · PreprintMolecular Biology