Author

Zaikai He

Chinese Academy of Sciences

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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Bioinformatics· 2 Bioengineering· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Research Focus:protein design· 3 Assay:protein sequence· 2 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Approach:optimal transport· 1 Assay:protein structure· 1 Approach:statistical model· 1

Frequent Co-Authors

Chungong YuiD· 2 shared Dongbo BuiD· 2 shared Milong ReniD· 2 shared Bin He· 1 shared Bin Li· 1 shared Fan Liu· 1 shared Haicang ZhangiD· 1 shared Han Zhou· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersBioinformatics

Chungong YuORCID

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3 papers

Recent·Most cited

ComplexDesign: sequence-hallucination design of protein binders bridging multiple proteins

J Q Xu, Milong Ren, Ning Qi, Xinru Zhang, Zaikai He, Chungong Yu, Dongbo Bu

ComplexDesign is a method for designing multichain protein complexes by optimizing sequences to fold proteins and form inter-chain interactions, achieving high success rates in designing dimers, trimers, and tetramers.

bioRxiv · Jun 24, 2026 · PreprintBioinformatics

Objective curriculum-guided design of multi-property proteins

Longying Liu, Jianquan Zhao, Xiaomin Xie, Simeng Xu, Milong Ren, Xinru Zhang, Zaikai He, Fan Liu, Chungong Yu, Kun Wang, Xinglong Wang, Xinmiao Liang, Xianlong Ye, Dongbo Bu, Han Zhou

This paper introduces OCDesign, a curriculum-guided framework for multi-property protein design, showing that staged objective introduction improves success rates compared to one-shot optimization.

bioRxiv · May 29, 2026 · PreprintBioengineering

PocketX: Preference Alignment for Protein Pockets Design through Group Relative Policy Optimization

Yuliang Fan, Zaikai He, Bin Li, Bin He, Mingshu Zhang, Jian Zhang, Haicang Zhang

PocketX uses reinforcement learning to align protein pocket design with biophysical properties, outperforming existing methods on binding energy and evolutionary plausibility.

bioRxiv · Dec 28, 2025 · PreprintBioinformatics