全细胞人工金属酶的工程化策略及应用研究

张英娇; 刘晓宇; 王云鹏; 相林; 李春; 王润铭

doi:10.12211/2096-8280.2026-058

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全细胞人工金属酶的工程化策略及应用研究

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- 全细胞人工金属酶的工程化策略及应用研究
- Advances in Engineering Strategies and Applications of Whole-Cell Artificial Metalloenzymes
- 合成生物学 2026年页码：1-19
- 作者机构：
  
  1.清华大学深圳国际研究生院生物医药与健康工程研究院，广东深圳 518055
  2.清华大学化工系，北京 100084
  3.北京理工大学化学与化工学院，北京 100101
  4.工业生物催化教育部重点实验室，北京 100084
  5.活性蛋白多肽绿色生物制造广东普通高校重点实验室，广东深圳 518055
- 作者简介：
  
  张英娇（1998—），女，博士研究生，研究方向为金属蛋白肽的合成生物制造与人工金属酶全细胞催化体系的开发等。
  李春（1970—），男，教授，博士，博士生导师。研究方向为细胞工厂数字化设计与工程应用，微生物合成植物天然产物（甘草）。
  王润铭（1989—），男，副教授，博士，博士生导师。研究方向为金属蛋白（肽）与金属药物的智能挖掘设计与精准生物制造。
- 基金信息：
  
  国家自然青年科学基金项目(22307063);广东省“珠江人才计划”引进创新创业团队项目(2023ZT10C040)
- DOI：10.12211/2096-8280.2026-058
  中图分类号： Q55
- 收稿：2026-06-24，
  
  修回：2026-08-21，
  
  网络首发：2026-08-31，
- 稿件说明：
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张英娇，刘晓宇，王云鹏，相林，李春，王润铭. 全细胞人工金属酶的工程化策略及应用研究［J］. 合成生物学， 2026， 7. DOI： 10.12211/2096-8280.2026-058

ZHANG Yingjiao， LIU Xiaoyu， WANG Yunpeng， XIANG Lin， LI Chun， WANG Runming. Advances in Engineering Strategies and Applications of Whole-Cell Artificial Metalloenzymes［J］. Synthetic Biology Journal， 2026， 7. DOI： 10.12211/2096-8280.2026-058
张英娇，刘晓宇，王云鹏，相林，李春，王润铭. 全细胞人工金属酶的工程化策略及应用研究［J］. 合成生物学， 2026， 7. DOI： 10.12211/2096-8280.2026-058 DOI：

ZHANG Yingjiao， LIU Xiaoyu， WANG Yunpeng， XIANG Lin， LI Chun， WANG Runming. Advances in Engineering Strategies and Applications of Whole-Cell Artificial Metalloenzymes［J］. Synthetic Biology Journal， 2026， 7. DOI： 10.12211/2096-8280.2026-058 DOI：

摘要

人工金属酶（Artificial metalloenzymes， ArMs）将非天然金属催化中心整合至蛋白质支架中，兼具金属催化剂的反应多样性和生物大分子的选择性识别能力，为拓展天然酶催化反应边界提供了重要工具。体外重构 ArMs 已在不对称转移氢化、不对称环丙烷化及 C-H 键不对称官能化等反应中展现出独特优势，但其进一步的应用仍受限于蛋白纯化成本高、催化体系稳定性不足等问题。将ArMs构建于活细胞或细胞衍生体系中，依托细胞代谢网络与保护机制，以及区室化结构等特点，提升了催化剂稳定性及生产效率；同时支持多步级联反应及高通量筛选，展现出工业化应用潜力。本文系统梳理了全细胞体系下ArMs的最新进展，核心内容涵盖三大模块：一是细胞组装与定位策略，重点分析细胞质、周质空间、细胞表面三类空间定位方式的技术原理、研究突破与适用场景；二是分子改造与高通量筛选技术体系，总结了从随机突变到计算驱动的多层次突变文库构建方法，以及无细胞提取物筛选、全细胞-光谱联用筛选等技术革新；三是场景化应用进展，详细阐述了其在肿瘤靶向治疗与高值化学品生物合成两大领域的代表性研究。最后，分析了该领域在金属辅因子稳定性、蛋白表达调控及催化性能优化等方面面临的挑战，并对人工智能与合成生物学深度融合驱动的未来发展方向进行了展望。

Abstract

Artificial metalloenzymes (ArMs) are biohybrid catalysts that integrate non-natural metal catalytic centers into protein scaffolds. By combining the broad reaction diversity of metal catalysts with the precise recognition capability of biological macromolecules

ArMs provide a critical tool for expanding the catalytic boundaries of natural enzymes. In vitro reconstituted ArMs have demonstrated unique advantages in a range of asymmetric transformations

including transfer hydrogenation

cyclopropanation

Michael addition

and C–H bond functionalization. However

their practical application remains constrained by multiple limitations

including high protein purification costs

insufficient stability

challenges in cofactor regeneration

and limited compatibility with complex reaction environments. Constructing ArMs within living cells or cell-derived systems enhances catalyst stability and production efficiency by leveraging the host cells′ intrinsic metabolic networks

protective mechanisms

and compartmentalized structures. Furthermore

whole-cell systems support autonomous cofactor regeneration

multi-step cascade reactions

and high-throughput directed evolution screening

demonstrating remarkable potential for industrial applications. In recent years

whole-cell ArM systems have achieved non-natural catalytic reactions including olefin metathesis and C–H bond activation

thereby expanding the inherent reaction scope of natural enzymes. Nevertheless

their development still faces core challenges in catalytic efficiency optimization

metal cofactor delivery

and large-scale preparation. This review systematically summarizes engineering strategies and application progress for ArMs in whole-cell systems

and is organized into three core modules. First

intracellular assembly and localization strategies are discussed

covering the fundamental principles and breakthroughs in cytoplasmic assembly

periplasmic localization

and cell-surface display. Second

the technological framework of protein engineering and high-throughput screening is reviewed

including multi-level mutant library construction and various innovative screening approaches. Third

scenario-based applications are examined

with emphasis on tumor-targeted therapy and high-value chemical biosynthesis. Finally

future directions are discussed

highlighting the deep integration of artificial intelligence and synthetic biology as a key driver of future technological advancement. The insights presented in this review are expected to provide theoretical support and decision-making references for the development of efficient and stable bio–non-biological hybrid catalytic systems.

关键词

Keywords

references

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