微生物学报

Carbon fixation pathway	Key carbon fixation enzymes	Substrate	Thermodynamic efficiency	Theoretical maximum carboxylation rate	Catalytic features
CBB cycle	RuBisCO	CO₂	3 ATP+2 NADPH/CO₂	3-10 s^-1(plants), 10-30 s^-1(cyanobacteria/microbes)	Relies on RuBP enediolate intermediate; most extensively studied and widely distributed^[11]
rTCA cycle	OGOR, IDH	CO₂	2 ATP/CO₂	OGOR 1-5 s^-1	Ferredoxin-dependent reductive carboxylation, two key carboxylation steps^[12]
WL pathway	FDH, CODH/ACS	CO₂	1 ATP/CO₂	CODH/ACS 1-10 s^-1; FDH 10-100 s^-1	FDH catalyzes CO₂ reduction to formate, CODH/ACS coupled via hydrophobic channel, simultaneously forming C-C and C-S bonds^[13]
3-HP cycle	ACC, PCC	HCO₃^-	2.33 ATP/CO₂	PCC 5-15 s^-1	Uses HCO₃^- as substrate, independent of CO₂; ACC and PCC cooperate to complete the dual-cycle CO₂ fixation^[14]
3-HP/4-HB cycle	ACC, PCC	HCO₃^-	4.5 ATP/CO₂	Lower than 3-HP	Similar to 3-HP cycle, integrated with a 4-hydroxybutyrate module^[14]
Di/4-HB cycle	PFOR, PEPC	CO₂/HCO₃^-	5 ATP/CO₂	PEPC 50-200 s^-1; PFOR 0.5-5 s^-1	PFOR utilizes reduced ferredoxin; PEPC is biotin-independent with irreversible reaction^[15]
Carbon concentrating module	CA	CO₂	No ATP consumption	k_cat 10⁴-10⁶ s^-1	Efficiently and reversibly catalyzes CO₂/HCO₃^- conversion; used to construct carbon-concentrating modules^[16]
Methane metabolism pathway	MMO	Methane	-	sMMO 10-50 nmol/(min·mg)	Uses O₂ as electron acceptor oxidant to oxidize methane to methanol, forming the first intermediate of the methane metabolism pathway^[17]
Methanol metabolism pathway	MDH	Methanol	-	NAD-MDH 10-100 s^-1; PQQ-MDH 100-1 000 s^-1	Catalyzes oxidation of methanol to formaldehyde, playing a central role in C1 metabolism of methylotrophs^[18]
Serine pathway	SHMT	Formaldehyde	3 ATP/formaldehyde	-	Key step of C1 fixation in the serine pathway^[19-20]
Serine pathway	Tetrahydrofolate-dependent enzyme	C1 units	3 ATP/formaldehyde	-	Multi-enzyme cooperation responsible for transport of formyl, methylene, and other C1 units^[19-20]
RuMP pathway	HPS, PHI	Formaldehyde	No ATP consumption	-	Formaldehyde fixation^[21]

Carbon fixation pathway	Key carbon fixation enzymes	Substrate	Thermodynamic efficiency	Theoretical maximum carboxylation rate	Catalytic features
CBB cycle	RuBisCO	CO₂	3 ATP+2 NADPH/CO₂	3-10 s^-1(plants), 10-30 s^-1(cyanobacteria/microbes)	Relies on RuBP enediolate intermediate; most extensively studied and widely distributed^[11]
rTCA cycle	OGOR, IDH	CO₂	2 ATP/CO₂	OGOR 1-5 s^-1	Ferredoxin-dependent reductive carboxylation, two key carboxylation steps^[12]
WL pathway	FDH, CODH/ACS	CO₂	1 ATP/CO₂	CODH/ACS 1-10 s^-1; FDH 10-100 s^-1	FDH catalyzes CO₂ reduction to formate, CODH/ACS coupled via hydrophobic channel, simultaneously forming C-C and C-S bonds^[13]
3-HP cycle	ACC, PCC	HCO₃^-	2.33 ATP/CO₂	PCC 5-15 s^-1	Uses HCO₃^- as substrate, independent of CO₂; ACC and PCC cooperate to complete the dual-cycle CO₂ fixation^[14]
3-HP/4-HB cycle	ACC, PCC	HCO₃^-	4.5 ATP/CO₂	Lower than 3-HP	Similar to 3-HP cycle, integrated with a 4-hydroxybutyrate module^[14]
Di/4-HB cycle	PFOR, PEPC	CO₂/HCO₃^-	5 ATP/CO₂	PEPC 50-200 s^-1; PFOR 0.5-5 s^-1	PFOR utilizes reduced ferredoxin; PEPC is biotin-independent with irreversible reaction^[15]
Carbon concentrating module	CA	CO₂	No ATP consumption	k_cat 10⁴-10⁶ s^-1	Efficiently and reversibly catalyzes CO₂/HCO₃^- conversion; used to construct carbon-concentrating modules^[16]
Methane metabolism pathway	MMO	Methane	-	sMMO 10-50 nmol/(min·mg)	Uses O₂ as electron acceptor oxidant to oxidize methane to methanol, forming the first intermediate of the methane metabolism pathway^[17]
Methanol metabolism pathway	MDH	Methanol	-	NAD-MDH 10-100 s^-1; PQQ-MDH 100-1 000 s^-1	Catalyzes oxidation of methanol to formaldehyde, playing a central role in C1 metabolism of methylotrophs^[18]
Serine pathway	SHMT	Formaldehyde	3 ATP/formaldehyde	-	Key step of C1 fixation in the serine pathway^[19-20]
Serine pathway	Tetrahydrofolate-dependent enzyme	C1 units	3 ATP/formaldehyde	-	Multi-enzyme cooperation responsible for transport of formyl, methylene, and other C1 units^[19-20]
RuMP pathway	HPS, PHI	Formaldehyde	No ATP consumption	-	Formaldehyde fixation^[21]

Carbon fixation pathway	Key carbon fixation enzymes	Substrate	Thermodynamic efficiency	Theoretical maximum carboxylation rate	Catalytic features
CETCH cycle	ECR	HCO₃^-	5 ATP+6 NADPH	0.05-0.5 s^-1	Simultaneously achieves enoyl-CoA reduction and carboxylation, NADPH-dependent, engineered variant showed a 5.5-fold improvement in k_cat/K_m compared to the wild-type^[22]
ASAP pathway	FLS	Formaldehyde	No ATP consumption	0.8-4 s^-1	TPP-dependent, catalyzes the condensation of 2 formaldehyde molecules to form glycolaldehyde, saturation mutagenesis at the active site improved its catalytic activity by 7.6-fold^[23]
SACA pathway	GALS, PK	Formaldehyde	1 ATP/2 HCHO	GALS 0.01-0.1 s^-1; PK 1-10 s^-1	GALS was obtained through de novo computational design, PK was engineered via computational simulation and structural analysis to expand its substrate spectrum^[24]

Carbon fixation pathway	Key carbon fixation enzymes	Substrate	Thermodynamic efficiency	Theoretical maximum carboxylation rate	Catalytic features
CETCH cycle	ECR	HCO₃^-	5 ATP+6 NADPH	0.05-0.5 s^-1	Simultaneously achieves enoyl-CoA reduction and carboxylation, NADPH-dependent, engineered variant showed a 5.5-fold improvement in k_cat/K_m compared to the wild-type^[22]
ASAP pathway	FLS	Formaldehyde	No ATP consumption	0.8-4 s^-1	TPP-dependent, catalyzes the condensation of 2 formaldehyde molecules to form glycolaldehyde, saturation mutagenesis at the active site improved its catalytic activity by 7.6-fold^[23]
SACA pathway	GALS, PK	Formaldehyde	1 ATP/2 HCHO	GALS 0.01-0.1 s^-1; PK 1-10 s^-1	GALS was obtained through de novo computational design, PK was engineered via computational simulation and structural analysis to expand its substrate spectrum^[24]

Strategy	Representative example	Key structural features	Engineering implications
Directed transfer of substrates and intermediates	CODH/ACS	Single-particle cryo-EM revealed the fine arrangement of the Ni-Fe cluster active centers, and identified a hydrophobic gas channel connecting CODH and ACS for directed CO transport	Design artificial channel proteins to directionally transport intermediates in tandem enzyme reactions, improving catalytic cascade efficiency
Spatial organization of electron transfer systems	PFOR/OGOR	Multiple [Fe₄S₄] clusters are linearly distributed along specific pathways within each subunit, constituting an efficient electron transfer network	Rationally design oxidoreductase complexes in artificial carbon fixation pathways, optimize cofactor spatial arrangement, and enhance electron transfer rates
Conformational dynamics-driven catalytic regulation	ACC	The BC and CT domains are connected by a flexible linker peptide; the biotin arm carrying the carboxyl group undergoes large-scale “swinging” between the two domains to complete carboxyl transfer	Utilize allosteric sites to construct metabolite-responsive biosensors, or engineer allosteric effector specificity via directed evolution to achieve orthogonal metabolic regulatory circuits
PEPC	The cleft between subunits of the homotetramer stabilizes the active site conformation and forms allosteric regulatory sites that respond to signals such as acetyl-CoA (activation) and aspartate (inhibition)

Strategy	Representative example	Key structural features	Engineering implications
Directed transfer of substrates and intermediates	CODH/ACS	Single-particle cryo-EM revealed the fine arrangement of the Ni-Fe cluster active centers, and identified a hydrophobic gas channel connecting CODH and ACS for directed CO transport	Design artificial channel proteins to directionally transport intermediates in tandem enzyme reactions, improving catalytic cascade efficiency
Spatial organization of electron transfer systems	PFOR/OGOR	Multiple [Fe₄S₄] clusters are linearly distributed along specific pathways within each subunit, constituting an efficient electron transfer network	Rationally design oxidoreductase complexes in artificial carbon fixation pathways, optimize cofactor spatial arrangement, and enhance electron transfer rates
Conformational dynamics-driven catalytic regulation	ACC	The BC and CT domains are connected by a flexible linker peptide; the biotin arm carrying the carboxyl group undergoes large-scale “swinging” between the two domains to complete carboxyl transfer	Utilize allosteric sites to construct metabolite-responsive biosensors, or engineer allosteric effector specificity via directed evolution to achieve orthogonal metabolic regulatory circuits
PEPC	The cleft between subunits of the homotetramer stabilizes the active site conformation and forms allosteric regulatory sites that respond to signals such as acetyl-CoA (activation) and aspartate (inhibition)

Feature	Greenase	General databases (UniProt, PubMed, PDB)	Specialized databases (NFixDB, P450Rdb)
Scope	Focuses on carbon-fixing enzymes from natural and artificial carbon fixation pathways	Broad biological scope, but not specifically targeting carbon fixation	Focuses on specific enzyme systems (nitrogenases, P450)
Functional annotation	Contains K_m/k_cat data, EC number search, and descriptions related to catalytic conditions	Annotation is general or incomplete	Limited to annotations related to specific enzyme families
Pathway integration	Carbon fixation pathways	Not pathway-oriented, information is scattered	Limited to a single metabolic or catalytic pathway
Tools	Structure clustering and auxiliary enzyme recommendations	Provides raw structural data	Basic structure or reaction visualization
Design purpose	Enzyme discovery and biocatalytic applications in the field of carbon fixation	General biological reference	Specialized research for specific enzyme classes

Feature	Greenase	General databases (UniProt, PubMed, PDB)	Specialized databases (NFixDB, P450Rdb)
Scope	Focuses on carbon-fixing enzymes from natural and artificial carbon fixation pathways	Broad biological scope, but not specifically targeting carbon fixation	Focuses on specific enzyme systems (nitrogenases, P450)
Functional annotation	Contains K_m/k_cat data, EC number search, and descriptions related to catalytic conditions	Annotation is general or incomplete	Limited to annotations related to specific enzyme families
Pathway integration	Carbon fixation pathways	Not pathway-oriented, information is scattered	Limited to a single metabolic or catalytic pathway
Tools	Structure clustering and auxiliary enzyme recommendations	Provides raw structural data	Basic structure or reaction visualization
Design purpose	Enzyme discovery and biocatalytic applications in the field of carbon fixation	General biological reference	Specialized research for specific enzyme classes

微生物固碳酶的结构、功能与定向进化：从催化机制到工程化应用

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彭祉尧 ¹^,² , 肖开兴 ¹^,² , 方霞 ¹^,² , 宗继锴 ¹^,² , 袁云艳 ¹^,² , 余艳婷 ¹^,² , 梁山泉 ¹^,² , 王钦宏 ³^,⁴^,⁵^,^* , 王丹 ¹^,²^,^*

微生物学报 | 综述 2026,66(9): 4299-4319

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微生物学报 |综述 2026 , 66 (9) : 4299 -4319

微生物固碳酶的结构、功能与定向进化：从催化机制到工程化应用

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彭祉尧¹^,², 肖开兴¹^,², 方霞¹^,², 宗继锴¹^,², 袁云艳¹^,², 余艳婷¹^,², 梁山泉¹^,², 王钦宏³^,⁴^,⁵^,^*, 王丹¹^,²^,^*

作者信息

^1.低碳合成生物制造重庆市高校重点实验室，重庆

^2.重庆大学化学化工学院，重庆

^3.中国科学院天津工业生物技术研究所，低碳合成工程生物学全国重点实验室，天津

^4.中国科学院天津工业生物技术研究所，工业酶国家工程研究中心，天津

^5.国家合成生物技术创新中心，天津

通讯作者:

王钦宏, 王丹

作者简介:

作者贡献声明

彭祉尧：论文初稿撰写、文献调研与整理、可视化图表制作与数据整理；肖开兴：论文审阅与编辑、文献筛选与分类；方霞：文献检索与分类、关键数据提取与汇总、参考文献管理；宗继锴：文献调研、关键酶结构与功能信息收集、图表辅助设计与校对；袁云艳：文献调研、图表辅助设计与校对；余艳婷：文献检索、数据整理与核对；梁山泉：论文审阅与编辑；王钦宏：论文审阅与编辑、研究框架设计、整体构思与指导；王丹：论文审阅与编辑、研究主题确立与概念构思、项目总体统筹与监督、论文最终定稿与责任。

Structures, functions, and directed evolution of microbial carbon-fixing enzymes: from catalytic mechanisms to engineering applications

Zhiyao PENG¹^,², Kaixing XIAO¹^,², Xia FANG¹^,², Jikai ZONG¹^,², Yunyan YUAN¹^,², Yanting YU¹^,², Shanquan LIANG¹^,², Qinhong WANG³^,⁴^,⁵^,^*, Dan WANG¹^,²^,^*

Affiliations

^1.Chongqing Key Laboratory of Low-Carbon Synthetic Bio-Manufacturing, Chongqing, China

^2.School of Chemistry and Chemical Engineering, Chongqing University, Chongqing, China

^3.Key Laboratory of Engineering Biology for Low-Carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China

^4.National Engineering Research Center of Industrial Enzymes, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China

^5.National Center of Technology Innovation for Synthetic Biology, Tianjin, China

Corresponding Author:

^*E-mail: WANG Qinhong, wang_qh@tib.cas.cn

WANG Dan, dwang@cqu.edu.cn

出版时间: 2026-09-04 doi: 10.13343/j.cnki.wsxb.20260414

文章导航

摘要

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在全球碳减排与“碳中和”目标背景下，微生物固碳酶因其高效、低能耗、可产高值化学品的独特优势成为生物固碳技术的核心研究前沿。本文系统综述了天然与人工固碳酶的分类、结构特征、催化机制及调控网络，重点分析了核酮糖-1,5-二磷酸羧化酶/加氧酶(ribulose-1,5-bisphosphate carboxylase/oxygenase, RuBisCO)、碳酸酐酶(carbonic anhydrase, CA)、甲醛缩合酶(formolase, FLS)、一氧化碳脱氢酶/乙酰辅酶A合成酶复合体(carbon monoxide dehydrogenase/acetyl-CoA synthase, CODH/ACS)等固碳酶在固碳过程中的作用与动力学调控。从结构生物学视角出发，探讨了静态结构与动态构象变化对催化效率的决定性作用。在此基础上，综述了理性设计、定向进化、高通量筛选及人工智能(artificial intelligence, AI)辅助预测等蛋白质工程策略在固碳酶改造中的应用进展，并介绍了Greenase等专用数据库在酶挖掘与路径重构中的支撑作用。通过RuBisCO、CA、FLS及多酶级联系统等典型案例，展示了从单酶优化到体系集成的工程化路径。最后，展望了动态催化机制模拟、体内适配性工程、从头酶设计与电/光-酶耦合系统等未来发展方向，为构建高效、稳定、工业适配的新型生物固碳技术提供理论参考。

关键词

固碳酶 / 二氧化碳 / 固碳酶数据库 / AI辅助设计 / 定向进化

Abstract

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In the context of global carbon emission reduction and carbon neutrality strategies, microbial carbon-fixing enzymes have emerged as a research frontier in biological carbon fixation technologies due to their unique advantages, including high efficiency, low energy consumption, and the ability to produce value-added chemicals. This review systematically summarizes the classification, structural characteristics, catalytic mechanisms, and regulatory networks of both natural and engineered carbon-fixing enzymes. It focuses on the roles and kinetic regulation of key enzymes such as ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO), carbonic anhydrase (CA), formolase (FLS), and carbon monoxide dehydrogenase/acetyl-CoA synthase (CODH/ACS) in CO₂ fixation. From a structural biology perspective, the review discusses how static structures and dynamic conformational changes determine catalytic efficiency. Furthermore, this paper reviews the recent advances in protein engineering strategies including rational design, directed evolution, high-throughput screening, and artificial intelligence (AI)-assisted prediction for carbon-fixing enzymes, along with the enabling role of specialized databases such as Greenase in enzyme mining and pathway reconstruction. Representative case studies, including RuBisCO, CA, FLS, and multi-enzyme cascade systems, are adopted to illustrate engineering pathways from single-enzyme optimization to integrated systems. Finally, future directions are discussed, including dynamic catalytic mechanism simulation, in vivo fitness engineering, de novo enzyme design, and electro-/photo-enzyme coupling systems. This review provides a theoretical reference for the development of efficient, stable, and industrially adaptable novel biological carbon fixation technologies.

Key words

carbon-fixing enzyme / carbon dioxide / carbon-fixing enzyme database / AI-assisted design / directed evolution

引用本文

彭祉尧, 肖开兴, 方霞, 宗继锴, 袁云艳, 余艳婷, 梁山泉, 王钦宏, 王丹. 微生物固碳酶的结构、功能与定向进化：从催化机制到工程化应用. 微生物学报, 2026 , 66 (9) : 4299 -4319 . DOI: 10.13343/j.cnki.wsxb.20260414

Zhiyao PENG, Kaixing XIAO, Xia FANG, Jikai ZONG, Yunyan YUAN, Yanting YU, Shanquan LIANG, Qinhong WANG, Dan WANG. Structures, functions, and directed evolution of microbial carbon-fixing enzymes: from catalytic mechanisms to engineering applications[J]. Acta Microbiologica Sinica, 2026 , 66 (9) : 4299 -4319 . DOI: 10.13343/j.cnki.wsxb.20260414

正文

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在全球气候变化加剧的背景下，实现碳达峰碳中和已成为国际社会的广泛共识与核心目标^[1]。面对大气中CO₂浓度持续攀升的严峻挑战，发展高效、低成本的碳捕集、利用与封存(carbon capture, utilization and storage, CCUS)技术迫在眉睫。在诸多碳减排技术路径中，直接空气捕集和地质矿化虽取得了一定进展，但普遍面临能耗高、成本昂贵、产物附加值低等瓶颈^[2-3]。

与之相比，生物固碳，尤其是以微生物及其代谢酶为核心的生物催化策略展现出了无可比拟的优势。微生物固碳过程通常在常温常压下进行，不仅能量消耗低，且能够将CO₂转化为生物质、燃料、大宗化学品等高附加值产物，真正实现碳资源的可再生循环利用^[4]。自然界中，无论是进行光合作用的蓝藻、以无机物氧化获能的化能自养菌，还是经过代谢工程改造的异养菌，均演化出了多样且精巧的碳浓缩与固定策略。在这些复杂的代谢网络中，“关键固碳酶”扮演着决定性的核心角色——它们的催化效率、底物特异性以及抗逆稳定性，直接决定了整条固碳通路的代谢通量和最终固碳效率^[5-7]。这些天然的固碳机器各具特色，构成了微生物适应多样化生态位的分子基础。例如，卡尔文-本森-巴沙姆(Calvin-Benson-Bassham, CBB)循环中负责CO₂初始固定的核酮糖-1,5-二磷酸羧化酶/加氧酶(ribulose-1,5-bisphosphate carboxylase/oxygenase, RuBisCO)；还原性三羧酸循环(reductive tricarboxylic acid cycle, rTCA)和Wood-Ljungdahl (WL)途径中催化关键反应的丙酮酸:铁氧还蛋白氧化还原酶(pyruvate:ferredoxin oxidoreductase, PFOR)、一氧化碳脱氢酶/乙酰辅酶A合成酶复合体(carbon monoxide dehydrogenase/acetyl-CoA synthase, CODH/ACS)；以及在3-羟基丙酸循环(3-hydroxypropionate cycle, 3-HP)中发挥作用的乙酰辅酶A羧化酶(acetyl-CoA carboxylase, ACC)；调节CO₂与HCO₃^-平衡的关键辅助酶碳酸酐酶^[8-10]。然而，由于漫长的自然进化通常倾向于追求生存适应性而非绝对的催化速率，天然固碳酶普遍存在催化速率迟缓、副反应严重、氧敏感性高或难以在异源宿主中高效表达等固有缺陷。

为突破这些自然进化的限制，研究者正致力于借助现代合成生物学、结构生物学与人工智能(artificial intelligence, AI)技术对现有酶进行深度工程化改造，从头设计全新的人工固碳酶。本文所讨论的“固碳酶”不局限于以CO₂为直接底物的羧化酶，还包括以一碳化合物(CO、甲烷、甲醇、甲醛等)为底物以及整个固碳途径中涉及的关键酶。首先系统概述核心天然与人工固碳酶家族的分类与功能特征(第2节)，随后从结构生物学视角剖析其“结构决定功能”的内在联系(第3节)，并深入探讨其催化化学本质与多层次的代谢调控机制(第4节)。在此基础上，本文将重点聚焦于蛋白质工程技术——详尽总结理性设计与定向进化策略(第5节)，以及固碳酶专用数据库的构建与人工智能在辅助酶和途径设计中的前沿应用(第6节)。最后，通过梳理典型的酶工程与体系级整合案例(第7节)，本文将对该领域的未来研究方向与工业化应用前景进行系统展望(第8节)，以期为开发新一代高效、稳定且具备工业应用潜力的生物固碳技术提供理论参考与实践指导。

1 核心固碳酶家族概述

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1.1 天然固碳酶概述

微生物在数十亿年的进化中发展出了多条不同的固碳途径，每条途径都包含其特有的关键固碳酶。根据代谢途径的类型，这些天然固碳酶可分布于卡尔文-本森-巴沙姆循环、还原性三羧酸循环、Wood-Ljungdahl途径、3-羟基丙酸循环、3-羟基丙酸/4-羟基丁酸循环(3-hydroxypropionate/4-hydroxybutylate cycle, 3-HP/4-HB)、二羧酸/4-羟基丁酸循环(dicarboxylic acid/4-hydroxybutyric acid cycle, Di/4-HB)等多条通路(表1)。

RuBisCO是研究最为深入、分布最为广泛的固碳酶，催化1,5-二磷酸核酮糖(ribulose-1,5-bisphosphate, RuBP)与CO₂的羧化反应生成2分子3-磷酸甘油酸，是卡尔文循环中的关键酶，其催化机制依赖于RuBP烯醇化形成的高度亲核烯二醇中间体对CO₂的攻击^[11]。

2-氧代戊二酸合酶(2-oxoglutarate synthase, OGOR)和异柠檬酸脱氢酶(isocitrate dehydrogenase, IDH)是rTCA循环中的关键固碳酶，属于铁氧还蛋白依赖的氧化还原酶家族，催化琥珀酰辅酶A与CO₂的还原性羧化反应生成2-氧代戊二酸，利用还原型铁氧还蛋白提供还原力；异柠檬酸脱氢酶则在循环中催化CO₂的固定生成异柠檬酸，是rTCA循环实现净碳固定的另一关键步骤^[12]。

甲酸脱氢酶(formate dehydrogenase, FDH)和一氧化碳脱氢酶/乙酰辅酶A合成酶复合体是WL途径中的核心固碳酶。FDH催化CO₂还原为甲酸的可逆反应，CODH/ACS复合体则是WL途径中最为关键的固碳机器，催化CO₂可逆还原为CO，随后CO与1个甲基基团以及辅酶A结合，同时催化C-C键和C-S键的形成，生成乙酰辅酶A^[13]。

乙酰辅酶A羧化酶和丙酰辅酶A羧化酶(propionyl-CoA carboxylase, PCC)是3-羟基丙酸双循环以及3-羟基丙酸/4-羟基丁酸循环中的关键固碳酶，ACC以HCO₃⁻为直接底物，催化乙酰辅酶A羧化生成丙二酰辅酶A。PCC则催化丙酰辅酶A的羧化生成甲基丙二酰辅酶A，与ACC共同完成这2个循环中的碳固定步骤^[14]。

丙酮酸合酶和磷酸烯醇丙酮酸羧化酶(phosphoenolpyruvate carboxylase, PEPC)是二羧酸/4-羟基丁酸循环中的关键固碳酶。丙酮酸合酶属于PFOR家族，利用还原型铁氧还蛋白提供的还原力催化乙酰辅酶A与CO₂的还原性羧化反应生成丙酮酸。PEPC则催化磷酸烯醇丙酮酸与HCO₃⁻的羧化反应生成草酰乙酸和无机磷酸，该反应不可逆，以HCO₃⁻为底物且不依赖生物素^[15]。

碳酸酐酶能够高效、可逆地催化CO₂与HCO₃⁻之间的相互转化，被广泛用于构建碳浓缩模块，通过将CA与下游羧化酶共定位或融合表达可以有效提高局部CO₂浓度，从而显著提升固碳效率^[16]。

除了上述直接固定CO₂或HCO₃⁻的酶类，微生物中还存在着以其他C1化合物为底物的固碳相关酶。甲烷单加氧化酶(methane monooxygenase, MMO)以氧气作为电子受体氧化剂，将甲烷氧化为甲醇，从而形成甲烷代谢途径的第一个中间体^[17]。甲醇脱氢酶(methanol dehydrogenase, MDH)催化甲醇氧化为甲醛，在甲基营养菌的C1代谢中起核心作用^[18]。丝氨酸羟甲基转移酶(serine hydroxymethyltransferase, SHMT)催化甲醛与四氢叶酸缩合生成亚甲基四氢叶酸，是丝氨酸途径中C1固定的关键步骤。四氢叶酸依赖的酶系包括甲酰四氢叶酸合成酶、次甲基四氢叶酸环化水解酶、亚甲基四氢叶酸脱氢酶等，负责C1单元的活化和转移^[19-20]。在核酮糖单磷酸途径中，己酮糖-6-磷酸合酶(hexulose-6-phosphate synthase, HPS)和6-磷酸-3-己酮糖异构酶(6-phospho-3-hexuloisomerase, PHI)协同作用催化甲醛与核酮糖-5-磷酸缩合形成己酮糖-6-磷酸，实现甲醛的固定^[21]。这些以C1为底物的酶虽然不直接固定CO₂，但在微生物的碳代谢网络中与固碳过程密切相关，构成了完整的C1生物转化链条。

1.2 人工固碳酶概述

面对天然固碳酶，尤其是RuBisCO，普遍存在的催化速率慢、氧敏感性高、底物选择性差等瓶颈，研究者开始探索和设计非天然的固碳酶，或对现有酶进行工程化改造(表2)，以期突破自然进化的限制，实现更高效、更稳定的CO₂生物转化。

巴豆酰辅酶A羧化酶/还原酶(enoyl-CoA carboxylases/reductases, ECR)是巴豆酰辅酶A/乙基丙二酰辅酶A/羟基丁酰辅酶A循环(crotonyl-CoA/ethylmalonyl-CoA/hydroxybutyryl-CoA cycle, CETCH)中的核心固碳酶，ECR催化的反应极具特色，利用NADPH提供的还原力，同时实现烯酰辅酶A的还原和羧化，一步生成相应的烷基羧酸。然而，天然ECR的底物谱较窄，限制了其在CETCH循环中的固碳效率，经过人工改造后突变体V350G的催化效率k_cat/K_m显著提升，相比野生型提高了5.5倍^[22]。

甲醛缩合酶是人工淀粉合成代谢途径(artificial starch anabolic pathway, ASAP)中的关键酶之一，以苯甲酰甲酸脱羧酶为模板，通过人工计算蛋白质设计获得。为解决天然FLS酶催化活性低、产物选择性差等问题，Cheng等^[23]对FLS活性中心进行饱和突变扫描，确定其活性中心改造后，成功地将其催化活性提升了7.6倍。

乙醇醛合酶(glycolaldehyde synthase, GALS)和磷酸酮醇酶(phosphoketolase, PK)是人工乙酰辅酶A合成(synthetic acetyl-CoA pathway, SACA)途径中的核心固碳酶，其中，乙醇醛合酶是研究人员为解决“甲醛到乙醇醛”这一关键反应而从头设计的，用于催化甲醛缩合生成乙醇醛；磷酸酮醇酶则通过计算模拟和结构分析，改造其底物结合口袋，使其能够识别并催化乙醇醛，同时保留其天然催化磷酸酮糖裂解的功能。两者协同作用，完成SACA途径中的C-C键形成与断裂。尽管这2种酶在天然微生物中存在同源物，但在SACA途径中它们被重新组织与工程化改造，以适应非天然的代谢通量^[24]。

除此之外，在其他人工固碳系统中还涉及多种工程化改造的固碳酶。例如，甲酸脱氢酶的工程化突变体被用于构建甲酸驱动的固碳系统，通过定点突变188位Asp为Arg，并结合固定化技术，可使催化效率提高约25倍^[25]。此外，通过对RuBisCO定向进化获得的具有更高CO₂亲和力的突变体RbcL-F140I，整合到人工固碳途径中以改善天然RuBisCO的性能瓶颈^[26]。

2 结构生物学视角：结构决定功能

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2.1 已知高分辨结构回顾

高分辨率三维结构的解析为理解固碳酶的催化机理、底物选择性和稳定性提供了重要基础。尽管不同固碳途径中的关键酶来源广泛、催化反应各异，但现有结构研究表明其功能实现普遍依赖于3类核心结构策略：底物与中间体的定向传递、电子传递体系的空间组织以及构象动态驱动的催化调控(表3)。许多固碳酶通过构建特化的底物通道实现反应中间体的高效传递与隔离，典型代表是CODH/ACS复合体，单颗粒冷冻电镜(cryo-electron microscopy, Cryo-EM)揭示了其Ni-Fe簇活性中心的精细排布以及CO从CODH到ACS的1条疏水气体通道^[27]。其次，对于涉及氧化还原反应的固碳酶，电子传递元件的精确空间排列是实现高效催化的重要基础，PFOR/OGOR家族结构显示，各亚基内部多个[Fe₄S₄]簇沿特定路径线性分布，形成贯穿蛋白质内部的电子传递网络^[28]。构象动态变化是许多固碳酶实现催化循环的重要机制，ACC和PEPC代表了固碳酶的另一种结构范式——“双结构域摆动”。ACC的BC和CT 2个结构域在空间上相对独立，由一段柔性连接肽相连，携带羧基的生物素臂在两大结构域之间大幅“摆动”^[29]。相比之下，PEPC则借助同源四聚体亚基间裂缝稳定活性中心构象，并创造出别构调控位点以响应乙酰辅酶A (激活剂)和天冬氨酸(抑制剂)等多种代谢信号^[30]。这一系列结构发现深刻揭示了固碳酶在漫长进化中形成的结构多样性与功能适应性。无论是依靠长距离疏水通道实现底物精准传递、利用线性铁硫簇构筑高效电子高速公路，还是借助柔性结构域摆动或复杂亚基间的别构效应，自然界针对不同的催化难题和代谢环境，演化出了截然不同但又各具特色的结构解决方案。

2.2 动力学与结构关联

结构信息与动力学研究紧密关联，固碳酶的构象变化动力学直接影响底物通道的开闭以及对底物的选择性。底物通道的开闭动力学直接影响催化选择性，RuBisCO的“开放-闭合”构象变化是其催化循环的核心，底物RuBP的结合诱导活性中心从开放构象转变为闭合构象，将CO₂或O₂捕获其中。闭合构象的稳定性决定催化中间体不被过早水解，而开放构象的频率则影响产物释放和抑制剂结合^[31]。同时，结构域摆动的频率与幅度决定多结构域酶的催化通量，ACC的生物素臂摆动速率是催化效率的限制因素之一，BC和CT结构域之间的距离决定摆动幅度，柔性连接肽的长度影响摆动频率，进化已优化出最适的连接肽长度——过短导致摆动幅度不足，过长则降低摆动频率，两者都会损害催化活性^[29]。多亚基的协同动力学赋予别构调控非线性响应特征，PEPC的活性受别构调控的动力学特性显著，乙酰辅酶A和天冬氨酸、苹果酸分别结合于不同的别构位点，通过诱导构象变化影响活性中心的几何结构，四聚体亚基之间的协同效应使得PEPC对效应物浓度的响应呈现S形曲线^[30]。无论是通道的微观开闭、结构域的宏观摆动，还是多亚基的别构协同，这些精细的动态构象变化从根本上决定了催化周期的运转效率，这也深刻揭示了仅依赖单一静态结构的理性设计存在固有局限。

2.3 结构解析方法及新工具

X射线晶体学长期以来是获取固碳酶原子分辨率结构的主力工具，贡献了绝大多数高精度结构，揭示了RuBisCO的高分辨率晶体结构(α/β)₈桶状活性中心的精细排布。对于大型、柔性或难以结晶的多酶复合体，Cryo-EM技术的革命性突破提供了前所未有的可能，研究者利用Cryo-EM成功解析了CODH/ACS复合体的三维结构，揭示了CO从CODH到ACS的完整疏水气体通道走向，使得解析其近原子分辨率的结构和动态构象变化成为现实。近年来，以AlphaFold为代表的人工智能蛋白质结构预测模型为固碳酶研究带来了新的机遇与挑战，其优势在于，对于尚无实验结构的固碳酶突变体，尤其是来自极端环境或未培养微生物的同源物能够快速提供高置信度的结构模型，研究者利用AlphaFold对CA的MutaT7随机突变引入的突变体进行结构预测，发现P105S突变破坏了活性中心氢键网络，这对于指导定向进化中的突变位点选择极具价值^[32]。然而，其局限性也显而易见，AI预测通常基于进化耦合分析，难以准确预测配体或金属离子诱导的构象变化，以及溶液中存在的动态构象系综。因此，当前最有效的策略是将AI预测模型与经典的生物化学、生物物理实验验证相结合(图1)，并进一步引入分子动力学模拟，例如对AI预测的结构模型进行显式溶剂分子动力学模拟，通过模拟酶在溶液中的动态行为及其与配体、金属离子的相互作用重点分析关键残基的构象柔性、底物结合路径以及金属离子配位状态的稳定性，弥补AI预测在构象动态描述上的不足，从而更全面地理解固碳酶的结构与功能关系。

3 功能机制与调控

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3.1 固碳酶的催化本质与反应路径

固碳酶催化的化学本质在于对惰性CO₂分子的活化以及C-C键的形成。CO₂作为弱亲电分子，其碳原子虽然带有部分正电荷，但反应活性较低，微生物固碳酶演化出了不同的活化策略。ECR主要通过Mg²⁺离子辅助，稳定底物烯醇化或去质子化后形成的亲核碳负离子，该中间体具有较强的亲核性，从而进攻CO₂^[33]。CA则是通过Zn²⁺活化水分子，产生高亲核性的Zn-OH⁻来攻击CO₂^[34]。对于氧化还原耦合型固碳酶PFOR/OGOR/CODH，电子供体还原型铁氧还蛋白提供的电子通过蛋白质内的电子传递通道精确地传递至多金属簇活性中心[Fe₄S₄]簇、Ni-Fe簇，这些金属中心既是电子库又是底物活化位点，实现了电子传递与碳骨架构建的协同演化。固碳酶在分子水平上实现了对惰性CO₂分子的精准操控，这种对活化化学本质的深刻认知，为打破天然途径在热力学或动力学上的局限，从而构建具有更高原子经济性或还原力利用效率的人工固碳反应提供了核心的理论依据。

3.2 关键固碳酶的催化机制解析

不同固碳酶的催化循环展示了酶学反应的“分子编舞”——每一步化学转化都需要精确的空间和时间控制，对关键固碳酶催化机制的深入解析揭示了其独特之处，尽管各酶的底物与反应类型不同，但其催化机制在亲核攻击、中间体稳定，以及CO₂活化方式等方面呈现出可归纳的共性规律。如图2所示，甲酸脱氢酶催化CO₂还原为甲酸的可逆反应，在较温和条件下即可高效催化这一反应，将电子传递给氧化型辅酶，或者反向将CO₂还原为甲酸，将电子传递给还原型辅酶^[35]。CA中与活性中心的Zn²⁺相连的H₂O去质子形成中间产物EZnOH⁻，随后CO₂被EZnOH⁻中的OH⁻水合形成EZnHCO₃⁻，然后EZnHCO₃⁻中的HCO₃⁻被H₂O置换形成EZnH₂O和HCO₃⁻^[34]。这2个酶的催化共性是依赖辅酶或者金属离子，生成高活性亲核试剂，而PEPC和丙酮酸羧化酶(pyruvate decarboxylase, PDC)则是生成高能碳负离子或活化中间体，实现对CO₂或HCO₃⁻的亲核加成，PEPC先利用高能磷酸烯醇式丙酮酸活化HCO₃⁻，形成不稳定中间体，经分子内重排后生成草酰乙酸^[30]。PDC则依赖辅因子硫胺素焦磷酸(thiamine pyrophosphate, TPP)：其C2去质子化后形成α-碳负离子/卡宾(a1/a2)，该活性中间体与乙醛非共价结合生成2-羟乙基-TPP (a3)，随后其羟基碳原子亲核攻击CO₂，生成2-乳酰-TPP (a4)，最终转化为丙酮酸^[36]。

3.3 影响固碳效率的关键调控层级

固碳效率不仅取决于酶自身的催化性能，更受制于多层次调控网络的协同作用。不同固碳酶面临的调控挑战各异——有些受限于底物供给，有些受制于产物抑制，还有些需要在竞争性反应中做出“选择”。若下游酶不能及时转化其羧化产物，积累的产物会反馈抑制酶活性，这种“代谢堵车”现象在多酶级联反应中普遍存在^[37-38]。某些底物如甲醇、甲醛具有显著的细胞毒性，通常由上游酶原位产生，其生成速率与消耗速率的匹配程度决定了系统中底物的稳态浓度，浓度过低则酶活性不足，过高则产生毒性^[39]。有些固碳酶的调控涉及辅因子选择，实际人工固碳系统的设计中固碳酶选择类型又取决于下游代谢对辅因子的需求^[40]。将上述固碳酶面临的辅因子制约、产物反馈抑制以及有毒底物压力等调控特征放在一起比较，可以归纳出一个共同的主题：在人工固碳系统的设计中，酶本身的动力学参数仅是构建高效途径的基石，而如何调控底物、产物以及辅因子在时间和空间上的适配与平衡是实现从“酶活性”向“固碳通量”转化的关键，这提示下一代固碳酶工程必须超越单酶的理性设计，迈向系统级的代谢网络适配工程。

4 蛋白质工程策略

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4.1 理性设计

理性设计的核心假设是研究者足够深入地理解酶的结构-功能关系就可以精准预测有益突变。这一策略依赖于高分辨率结构X射线晶体学、冷冻电镜或AlphaFold模型和对催化机理的深刻认知。对RuBisCO的理性设计尝试最多，也最能体现这一策略的潜力与局限。经典靶点包括：改造活性中心残基(Lys201、Asp203、Glu60)以优化底物结合和过渡态稳定；改造底物口袋以调节CO₂/O₂选择性，扩大CO₂进入通道或缩小O₂结合空间；引入盐桥或二硫键提高热稳定性^[41-43]。FDH的改造可优化辅因子NAD⁺/NADH结合域和释放动力学，结合固定化技术可使热稳定性提高约18倍^[25]。针对PFOR/OGOR等氧敏感酶，理性设计的主要目标是提高氧耐受性——通过识别氧气通道入口的关键残基进行突变，降低O₂进入速率^[44]。然而，理性设计的根本局限在于研究者对酶的认识是不完整的，无论是过渡态结构还是远端突变的构象影响，研究者均难以依托静态结构精准预测，这解释了为什么理性设计成功的案例相对较少，也说明了定向进化仍为不可替代的技术路径。

4.2 定向进化

与理性设计互补，定向进化技术不依赖于酶的结构信息，而是通过模拟自然进化过程，在实验室中建立大规模的突变文库，并施加特定的选择压力，以筛选出性能提升的突变体。文库构建的常用方法包括易错PCR、重组同源基因片段以及定点饱和突变^[45]。对于MDH等难以直接通过产物颜色或荧光进行高通量筛选的酶，需要设计巧妙的筛选策略。一种常见方法是构建代谢耦合筛选系统，将MDH基因与宿主菌株的生长必需基因偶联，使得只有在MDH活性足够支持甲醇固定为生物质时菌株才能在无外源有机碳的培养基中生长^[46]。另一种是使用荧光检测系统，将固碳产物的下游代谢与荧光蛋白的表达相耦合，或者使用荧光标记的CO₂类似物进行流式细胞术分选^[47]。近年来，微液滴流控技术允许将单个细胞包裹在皮升级微滴中进行反应和分选，极大地提高了突变体的高通量筛选效率。Li等^[48]通过表面增强拉曼光谱技术监测PEPC酶促反应产物丁二酸的特征拉曼信号变化(图3)，从数万个突变体中筛选出PEPC突变体(D210G/V886A/L406P)，其在低HCO₃⁻浓度下的催化效率较野生型提高了4.6倍，且对天冬氨酸的反馈抑制表现出明显耐受性。

理性设计与定向进化代表了固碳酶工程化改造的2条演进路径：前者基于“先知”的逻辑试图精准重塑分子细节，后者基于“优胜劣汰”的法则在广袤的序列空间中挖掘惊喜。然而，RuBisCO等复杂酶类的改造现状表明，单一策略通常难以突破天然酶的进化瓶颈——理性设计难以捕捉长程的动态效应，而定向进化则常受限于筛选系统的开发难度与盲目性。这种现状迫切要求转变研究范式，将蛋白质工程从传统的“湿实验驱动”推向“数据驱动”。构建专门针对固碳酶的标准化、高质量数据库是打破当前“数据荒岛”状态的关键，更是利用AI进行突变预筛选、缩小实验探索空间的必要前提(图4)，最终从盲目筛选走向精准重塑，在更小的实验成本下实现固碳酶功能的跨越式提升。

5 固碳酶数据库的构建和AI辅助固碳酶设计

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5.1 固碳酶数据库的构建与整合

目前固碳酶的相关数据分散于多个通用型生物数据库和大量文献中，缺乏系统性的整合与功能注释，给研究者带来了显著障碍。现有的通用型生物数据库，如UniProt、PubMed和Protein Data Bank (PDB)，尽管积累了海量的蛋白质序列、文献和结构信息，但它们并非专门针对固碳酶设计，缺少能够将酶序列、结构、功能与途径背景关联起来的统一分类体系，导致研究者难以高效识别关键催化剂或比较不同物种来源的同源酶。此外，这些数据库缺乏专门的分析工具，如基于结构的聚类分析和辅助酶推荐功能，限制了它们在固碳研究中的应用性。已有一些专门的功能导向数据库，如整合固氮酶相关信息的NFixDB以及汇总细胞色素P450酶及其催化反应的P450Rdb，充分展示了针对特定酶家族进行数据整合与功能开发的价值^[49-50]。然而，目前尚无一个数据库能够全面涵盖参与CO₂固定的多样化酶家族，也未能提供跨途径的比较框架。尽管已报道了6条天然固碳途径，近年来人工固碳途径也取得了重要进展，但相关酶的关键信息仍然分散在不同数据库和出版物中，这种碎片化对高效的酶挖掘、途径设计以及工程化应用构成了实质性阻碍。

随着固碳酶研究数据的爆发式增长，开发高度集成且功能化的专用固碳酶数据库已成为驱动该领域发展的需求。Peng等^[51]采用Python网络爬虫技术与简单对象访问协议(simple object access protocol, SOAP)相结合的方式，对已有数据库进行系统性数据提取，并从现有文献中人工整理了辅因子、反应类型、操作参数及氨基酸序列等补充信息。在此基础上，利用Java编程语言及Spring Boot和MyBatis集成框架开发了稳健、安全且以用户为中心的网络应用程序；该数据库实现了基于产物、底物、酶名称和EC号等关键字段的结构化过滤系统，支持布尔运算符(AND、OR、NOT)以实现灵活精确的查询。值得一提的是，该工作不仅系统整合了现有公用数据库中的核心信息，更针对科研实操需求人工增补了大量文献中的关键参数，包括辅因子偏好、反应动力学参数及环境操作参数等(表4)。相较于传统的序列存储，Greenase引入了2个极具前瞻性的功能模块。首先是基于结构聚类的功能挖掘模块，该模块利用ColabFold大规模预测了固碳酶的三维结构，并通过TM-score算法实现了层次聚类。这种从“序列相似性”向“结构相似性”的维度跨越，为发现远源同源酶及理解结构多样性提供了强有力的工具。其次是基于底物结构相似性的辅助酶推荐系统，该模块利用化学摩根指纹识别，能够根据用户输入的目标化合物自动匹配并推荐潜在的催化酶类，这一功能极大地简化了人工合成路径设计中的元件搜索过程(图5)。

Greenase数据库当前版本涵盖24 647条详细的酶数据记录，代表1 552种不同的固碳酶。这些酶来源于超过436个物种，涵盖163个固碳反应及85种相关化合物。数据库可通过http:// 103.236.90.94:8000/访问，主要功能包括支持按产物、底物、酶名称和EC号的多元检索，集成用于序列功能分析的本地BLAST引擎，提供蛋白质结构预测与聚类模块，以及基于底物结构相似性的酶推荐模块。同时通过甲醛缩合酶途径和RuBisCO表达实验案例研究，Greenase证明了其在加速固碳酶的筛选、代谢途径重构以及指导酶工程理性改造方面的巨大应用潜力。Greenase将每6个月更新整合一次来自原始文献和数据库中新发现的酶数据集，后续还将引入动力学建模与酶稳定性预测工具，与高通量实验流程实现更紧密的耦合。这些进展将使Greenase能够支撑完整的“设计-构建-测试-学习”循环，从而加速面向可持续生物制造与气候减缓的碳固定途径的工程化开发。

5.2 AI辅助固碳酶设计

在高质量数据库的基础上，AI辅助固碳酶设计正成为该领域的核心驱动力。与传统的理性设计或定向进化不同，AI方法能够从海量的序列和结构数据中自动学习固碳酶的“序列-结构-功能”关系，从而在巨大的突变空间中高效筛选出有益突变，甚至从头设计具有全新功能的固碳酶。目前，主流的AI策略包括基于蛋白语言模型的序列嵌入、基于图神经网络的结构建模，以及融合多模态信息的联合预测框架。

一个将AI计算设计与实验验证成功结合的典范是FLS酶的创制与应用。早在2015年，Siegel等^[52]报道了利用计算蛋白设计方法从头开发甲醛缩合酶的工作，该研究的出发点是为了构建一条全新的人工C1同化途径。自然界中并不存在能够直接将3个甲醛分子缩合为二羟基丙酮的酶，因此研究者转向计算设计，分析了苯甲酰甲酸脱羧酶家族的序列与结构特征，通过Rosetta设计平台对活性中心进行重新编程，最终设计出完全非天然的FLS酶；在体外实验中，FLS成功将甲醛转化为磷酸二羟丙酮及其他中心代谢产物，验证了计算设计策略在创造新型固碳酶方面的可行性。这项工作证明了AI计算设计不仅能够“改造”天然酶，更能够“创造”自然界不存在的酶。在此之后，针对FLS催化活性较低的瓶颈，Cheng等^[23]采用了一种结合计算模拟与实验进化的策略来优化FLS性能，研究团队首先聚焦于活性中心周围8 Å范围内的25个残基位点；与传统的随机定向进化不同，研究人员并未盲目筛选随机突变文库，而是利用分子动力学模拟对突变效应进行预筛选：通过模拟WT及突变体与底物的结合模式，计算活性中心疏水环境的分布，预测不同氨基酸替换对辅因子-底物中间体稳定性的影响；基于模拟结果，研究者优先选择了那些被预测能增加活性中心局部疏水性的突变组合进行实验验证，通过对约5 000个突变体的筛选发现S236F突变使DHA生成活性提升了7.6倍；分子动力学模拟进一步揭示，该突变增加了活性中心的局部疏水性，使辅因子-C2中间体更易受到第三分子甲醛的亲核攻击，从而促进了C3产物的形成。值得注意的是，该研究发现的优势突变位点是传统定向进化未能触及的，彰显了计算辅助策略在突破局部最优解方面的独特价值。

这2项关于FLS的研究代表了AI辅助固碳酶设计的2种范式：前者以计算设计为核心，从无到有创造新型催化功能；后者以计算模拟辅助筛选，在已知骨架上实现“优中选优”。2种策略相互补充，共同展示了AI与数据驱动方法在加速固碳酶开发中的巨大潜力。

5.3 AI辅助多酶级联固碳与系统优化

AI辅助固碳酶设计的最终目标并非仅在于改造单个酶，而是将其整合到高效的多酶级联反应系统中，实现从CO₂到目标产物的连续转化。多酶级联固碳反应涉及多个酶的协同工作、辅因子的再生平衡以及中间代谢物的浓度控制，其设计复杂度远高于单酶体系。传统的路径设计依赖研究者对已知途径的组合与调试，不仅耗时费力，而且难以覆盖未知的催化可能性。AI技术的引入正在改变这一局面，使得从“人工设计”到“自动设计”的范式转变成为可能(图6)。

AI辅助设计多酶级联反应通常包含3个核心环节：路径搜索与生成、热力学与动力学评估以及酶元件匹配^[53]。以CETCH循环为例，该循环由德国马普陆地微生物研究所开发，包含17个酶、8个辅因子，是目前体外固碳效率最高的人工固碳途径之一。然而，CETCH循环的设计与优化过程耗时接近5年，远未达到高通量或自动化。近年来，研究者开始引入机器学习模型来加速这一过程。Pandi等^[54]开发了一个基于高斯过程的主动学习工作流程，用于优化CETCH循环中限速步骤的酶组合和反应条件，该工作流程通过初始少量实验数据训练模型，选择模型预测不确定性最高的实验条件进行下一轮验证，从而以最少的实验迭代次数找到最优条件；在仅经过6轮(每轮约100个数据点)的主动学习循环后，研究者成功将CETCH循环的CO₂固定速率提升了约3倍，而传统优化方法通常需要数千次实验才能达到同等效果。这一工作展示了AI不仅在酶元件层面，更在系统整合层面赋能固碳途径设计的巨大潜力。

除了对已知途径的优化，AI正在开启从零开始设计全新、非天然多酶级联固碳系统的崭新范式。目前，研究者已开始尝试将大规模生化反应规则库与深度学习神经网络相结合，构建端到端的“目标导向型”固碳路径设计管线。在该体系下，用户只需输入预期的目标产物(如淀粉、乙醇或乙醛酸等)，系统即可利用逆向合成策略自动搜索潜在的CO₂固定路径。通过集成热力学可行性评价算法与酶数据库的自动化匹配，系统能够输出一套完整的、具备实验可操作性的路径构建方案。尽管目前由AI设计的大多数非天然路径仍处于计算验证阶段，但诸如“人工CO₂合成淀粉”等里程碑式工作的成功，已充分证明了该路径的可行性。未来的研究方向将聚焦于进一步缩小计算预测与湿实验验证之间的“鸿沟”：通过引入更精准的酶活力预测模型和代谢流动态仿真技术，AI将能够更好地应对非天然反应在细胞底盘中的适配性问题。

6 典型工程应用案例分析

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6.1 RuBisCO酶工程案例

从实验室的理论研究到实际应用，固碳酶的工程化已涌现出一批典型范例，其发展逻辑呈现出从单酶改造到多酶协同再到体系集成的清晰脉络。通过将大肠埃希氏菌(Escherichia coli)改造为RuBisCO依赖型菌株，研究者得以在模拟大气CO₂浓度的选择压力下，通过定向进化筛选出F140I等优势突变体，这种基于代谢背景的整体提升在蓝藻底盘中表现出显著的生物质转化优势，证明在真实胞内环境下维持羧化通量比追求单一参数极限更具应用价值^[55]。与此同时，针对底物供给瓶颈的模块化策略展现了另一种维度，即利用柔性连接肽或表面电荷互补的静电引导，使碳酸酐酶与RuBisCO形成精密的空间邻近效应。这种通过工程化手段重构的微环境大幅提升了局部CO₂浓度，在大肠埃希氏菌系统中实现了固碳速率的数倍飞跃，成功跳出了对活性中心精细雕刻的传统桎梏。针对工业烟气等高温特种场景，从热泉宏基因组直接挖掘的Form Ⅱ家族Tk-RuBisCO等天然耐热元件，在辅以简化版碳浓缩模块后能够在55 ℃等极端环境下保持长期催化稳定，为异构底盘提供了跨越物种界限的固碳能力^[56-58]。这些尝试共同勾勒出未来RuBisCO工程化的核心逻辑：不再单向追求酶学的通用性最优，而是通过高通量筛选、空间组织优化及环境适应性元件的灵活组装，实现酶与特定代谢网络、物理环境的深度适配。这种从“更好”向“更适用”的范式转变正加速固碳技术从实验室理想模型向工业生产车间的跨越进程。

6.2 CA酶工程案例

碳酸酐酶的工程改造则侧重于活性和稳定性的提升，以及在复合体中的定位，设计出的变体dGCA1A对底物的催化效率提升了746倍，同时其熔解温度从67.8 ℃显著提高至96.1 ℃，且在50%极性有机溶剂中仍能保持高催化活性^[56]。通过表面电荷优化，获得了在盐度高达2 mol/L NaCl条件下仍保持活性的α-CA突变体，适用于海水或高盐工业尾气的碳捕集。此外，将CA与RuBisCO或羧酶体外壳蛋白进行融合表达，通过特定的肽标签(如来自羧酶体壳蛋白的靶向序列)将CA精准锚定到RuBisCO附近或羧酶体内部。这种空间上的“近邻效应”极大地提高了局部CO₂浓度，使得RuBisCO的羧化效率提升了3-5倍^[57]，展示了构建人工碳浓缩机制的巨大潜力。在固定化技术方面，将CA固定在SBA-15介孔分子筛上，在40 ℃下6 d后仍保持96%的初始活性；而将CA封装在ZIF-8中，储存10 d后固定化酶保留40%活性，游离酶仅剩9%^[59-60]。CA的工程化进展表明，高效固碳体系的构建需要分子鲁棒性、空间组织力与材料兼容性三位一体。未来的研究重点应进一步聚焦于如何精确匹配CA的水合速率与下游固碳酶的消耗速率，并在复杂的动态多相界面中维持这种动态平衡，从而为实现规模化、低能耗的人工生物固碳提供坚实的元件基础。

6.3 FLS酶工程案例

针对FLS催化活性的提升，研究者采取了“计算辅助筛选+定向进化验证”的混合策略。与传统的随机突变筛选不同，Cheng等^[23]首先聚焦于活性中心周围8 Å范围内的25个残基位点，利用分子动力学模拟对突变效应进行预筛选：通过模拟野生型及突变体与底物的结合模式，计算活性中心疏水环境的分布，预测不同氨基酸替换对TPP辅因子-甲醛中间体稳定性的影响；基于模拟结果，研究者优先选择了那些被预测能增加活性中心局部疏水性的突变组合进行实验验证，通过对约5 000个突变体的筛选，发现S236F单点突变使二羟基丙酮生成活性提升了7.6倍；分子动力学模拟进一步揭示，苯丙氨酸的引入增加了活性中心的局部疏水性，使TPP-C2中间体更易于受到第三分子甲醛的亲核攻击，从而促进C3产物的形成；值得注意的是，该研究发现的数个优势突变位点位于活性中心外围区域，是传统定向进化中容易被忽略的“远端调控位点”，彰显了计算辅助策略在突破局部最优解方面的独特价值。在体系集成方面，FLS与甲醛脱氢酶、醛缩酶、磷酸酶等多酶级联反应相偶联，构建了从甲酸(CO₂还原产物)到淀粉的完整人工途径。通过优化途径中酶的表达比例和反应条件，ASAP途径最终实现了22.0 nmol/(min·mg)的CO₂到淀粉转化速率，较玉米中淀粉合成速率高约8.5倍^[61]。

FLS的工程化案例为人工固碳酶的开发提供了重要启示：首先，计算设计可以从头创造具有全新催化功能的酶，突破天然酶库的限制；其次，分子动力学模拟等计算工具能够有效指导实验进化，尤其善于发现远端调控位点；最后，单酶改造必须与途径集成相协同才能真正实现从CO₂到高值产物的高效转化。这一从“创造”到“优化”再到“集成”的完整链条，代表了固碳酶工程化的发展方向。

6.4 多酶体系级联案例

体系级整合案例代表了当前工程化水平，人工重构羧酶体是代表性工作之一。研究人员将蓝藻羧酶体的外壳蛋白(CcmK、L、M、N)以及内部的RuBisCO和CA等组分导入大肠埃希氏菌等异源宿主中，成功地自组装形成了功能性的“人工碳浓缩微区”。这些微区能够主动富集HCO₃^-，并通过CA将其转化为高浓度的CO₂，供应给内部的RuBisCO，从而显著抑制了副反应并提高了异养菌中RuBisCO的固碳效率^[62]。Xu等^[63]将FDH、FADH和ADH共固定在海藻酸盐-二氧化硅杂化凝胶中，甲醇收率可达98.1%，储存60 d后收率仍可达76.2%。更进一步的策略是将碳捕集酶模块与产物合成模块[如乙酰辅酶A羧化酶ACC、丙酮酸脱氢酶(pyruvate dehydrogenase, PDH)]进行整合，构建“碳捕-转化”一体化途径，直接将固定的CO₂导向目标高值化学品的合成。Gleizer等^[5]通过对大肠埃希氏菌进行系统的代谢工程和实验室进化，成功地使其实现了化能自养生长；该工程菌株被导入了来自嗜热红菌的Form Ⅱ RuBisCO和磷酸核酮糖激酶(phosphoribulokinase, PRK)，并敲除了内源的中心碳代谢关键基因，同时通过进化适应，增强了NADPH的再生能力，最终使得菌株能够仅以CO₂为唯一碳源生长。类似地，在枯草芽孢杆菌中整合CA与碱性转运系统，使其能在高pH环境下高效利用CO₂在模式蓝藻中，共过表达RuBisCO及其激活酶Rca，显著提高了宿主在波动光照下的光合固碳效率^[64-65]。这些案例充分证明了，通过对固碳酶进行深度工程化改造并与其宿主代谢网络进行精密整合能够创造出性能远超自然界的生物固碳体系。

7 总结与展望

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从天然微生物的代谢网络到人工设计的无细胞级联催化系统，固碳酶的研究正经历一场从“被动发现与解析”向“主动改造与创造”的范式跃迁。借助Cryo-EM等高分辨结构解析技术、多维度的蛋白质工程手段以及蓬勃发展的AI驱动计算生物学，对固碳酶催化机制的理解达到了前所未有的深度。人工淀粉合成途径、CETCH循环以及工程化自养大肠埃希氏菌等里程碑式成果无一不彰显了固碳酶工程化在重塑生物地球化学碳循环中的巨大潜力。

然而，要将这些实验室级别的突破真正转化为工业级别的碳中和生产力，固碳酶的研究仍面临诸多挑战。展望未来，该领域有望在以下几个核心维度迎来重大突破。

突破动态催化机制的计算瓶颈与AI模型升维。尽管AlphaFold等AI模型在预测蛋白质静态结构方面取得了革命性进展，但固碳酶的催化通常依赖于复杂的构象动力学变化(如柔性底物通道的开闭、生物素臂的摆动、多酶复合体间的别构通讯)。未来的计算酶学需要开发能够精确预测底物-酶过渡态相互作用的高精度分子动力学以及量子力学/分子力学混合模型。从“序列-静态结构”向“序列-构象系综-动态功能”的AI预测模型升维，将是实现理性设计跨越式发展的关键。

实现从“体外高通量”到“体内深适配”的系统跃迁。当前许多人工设计的固碳酶及多酶级联途径在体外表现出极高的催化速率，但在导入底盘细胞(如大肠埃希氏菌、蓝藻或酵母)时通常因面临胞内代谢流竞争、辅因子(如NADPH/ATP)失衡、中间有毒代谢物(如甲醛)积累等问题而效率大幅衰减。未来的工程化必须超越“单酶至上”的局限，采用全细胞代谢网络建模。利用多组学数据与通量平衡分析，为人工固碳酶量身定制“即插即用”的辅助代谢模块，实现人造固碳机器与宿主天然代谢网络的完美耦连。

加速从头设计与全新非天然固碳化学的开拓。大自然并未穷尽所有可能的固碳化学反应空间。正如FLS酶的成功创制所展示的，未来的研究应更加大胆地探索非天然固碳途径。依托算力的提升与Greenase等专业数据库的不断扩充，研究人员可以利用生成式AI模型和逆合成算法，探索出热力学和动力学均优于现有自然途径的全新固碳网络，并依靠从头设计(de novo design)创造出完全不依赖于天然支架的高效人工羧化酶或醛缩酶，彻底摆脱自然进化的系统发生学包袱。

推动电/光-酶耦合与工业级生物制造的深度融合。固碳酶的应用最终必须落脚于工业场景。单纯依靠生物系统自身的光合或化能驱动，通常受限于能量转化效率。未来，将高稳定性的工程化固碳酶与光电催化材料、微纳流控反应器深度融合，构建“电/光-生物杂合系统”(如电驱动固碳合成平台)，是一条极具前景的破局之路。同时，针对工业废气的极端环境，定向进化出具备超强耐热、耐酸碱、抗毒物毒化的极端固碳酶，将打通从工业碳排放源到高附加值生物化学品的大规模制造转化链。

综上所述，固碳酶的研究处于生物学、化学、信息科学与工程学的多学科交叉前沿。随着“数据驱动+AI辅助计算+高通量实验验证”闭环的不断完善，有理由相信，新一代具有颠覆性催化效率的人工生物固碳系统将在不久的将来走向成熟，为应对全球气候危机、实现绿色可持续的生物经济提供最强有力的技术支撑。

基金

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广东省重点领域关键技术攻关项目(2024B1111160005)
国家重点研发计划(2022YFC2105700)
国家自然科学基金(22378032)
重庆市人力资源和社会保障局项目(cx2023036)

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2026年第66卷第9期

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doi: 10.13343/j.cnki.wsxb.20260414

接收时间：2026-05-16
首发时间：2026-09-09
出版时间：2026-09-04

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出版历史

收稿日期：2026-05-16
录用日期：2026-06-28

基金

the Key Research and Development Project of Key Areas in Guangdong Province(2024B1111160005)

广东省重点领域关键技术攻关项目(2024B1111160005)

the National Key Research and Development Program of China(2022YFC2105700)

国家重点研发计划(2022YFC2105700)

the National Natural Science Foundation of China(22378032)

国家自然科学基金(22378032)

the Chongqing Human Resources and Social Security Bureau Project(cx2023036)

重庆市人力资源和社会保障局项目(cx2023036)

作者信息

^1.低碳合成生物制造重庆市高校重点实验室，重庆

^2.重庆大学化学化工学院，重庆

^3.中国科学院天津工业生物技术研究所，低碳合成工程生物学全国重点实验室，天津

^4.中国科学院天津工业生物技术研究所，工业酶国家工程研究中心，天津

^5.国家合成生物技术创新中心，天津

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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Carbon fixation pathway	Key carbon fixation enzymes	Substrate	Thermodynamic efficiency	Theoretical maximum carboxylation rate	Catalytic features
CBB cycle	RuBisCO	CO₂	3 ATP+2 NADPH/CO₂	3-10 s^-1(plants), 10-30 s^-1(cyanobacteria/microbes)	Relies on RuBP enediolate intermediate; most extensively studied and widely distributed^[11]
rTCA cycle	OGOR, IDH	CO₂	2 ATP/CO₂	OGOR 1-5 s^-1	Ferredoxin-dependent reductive carboxylation, two key carboxylation steps^[12]
WL pathway	FDH, CODH/ACS	CO₂	1 ATP/CO₂	CODH/ACS 1-10 s^-1; FDH 10-100 s^-1	FDH catalyzes CO₂ reduction to formate, CODH/ACS coupled via hydrophobic channel, simultaneously forming C-C and C-S bonds^[13]
3-HP cycle	ACC, PCC	HCO₃^-	2.33 ATP/CO₂	PCC 5-15 s^-1	Uses HCO₃^- as substrate, independent of CO₂; ACC and PCC cooperate to complete the dual-cycle CO₂ fixation^[14]
3-HP/4-HB cycle	ACC, PCC	HCO₃^-	4.5 ATP/CO₂	Lower than 3-HP	Similar to 3-HP cycle, integrated with a 4-hydroxybutyrate module^[14]
Di/4-HB cycle	PFOR, PEPC	CO₂/HCO₃^-	5 ATP/CO₂	PEPC 50-200 s^-1; PFOR 0.5-5 s^-1	PFOR utilizes reduced ferredoxin; PEPC is biotin-independent with irreversible reaction^[15]
Carbon concentrating module	CA	CO₂	No ATP consumption	k_cat 10⁴-10⁶ s^-1	Efficiently and reversibly catalyzes CO₂/HCO₃^- conversion; used to construct carbon-concentrating modules^[16]
Methane metabolism pathway	MMO	Methane	-	sMMO 10-50 nmol/(min·mg)	Uses O₂ as electron acceptor oxidant to oxidize methane to methanol, forming the first intermediate of the methane metabolism pathway^[17]
Methanol metabolism pathway	MDH	Methanol	-	NAD-MDH 10-100 s^-1; PQQ-MDH 100-1 000 s^-1	Catalyzes oxidation of methanol to formaldehyde, playing a central role in C1 metabolism of methylotrophs^[18]
Serine pathway	SHMT	Formaldehyde	3 ATP/formaldehyde	-	Key step of C1 fixation in the serine pathway^[19-20]
Serine pathway	Tetrahydrofolate-dependent enzyme	C1 units	3 ATP/formaldehyde	-	Multi-enzyme cooperation responsible for transport of formyl, methylene, and other C1 units^[19-20]
RuMP pathway	HPS, PHI	Formaldehyde	No ATP consumption	-	Formaldehyde fixation^[21]

Carbon fixation pathway

Key carbon fixation enzymes

Substrate

Thermodynamic efficiency

Theoretical maximum carboxylation rate

Catalytic features

CBB cycle

RuBisCO

CO₂

3 ATP+2 NADPH/CO₂

3-10 s^-1(plants), 10-30 s^-1(cyanobacteria/microbes)

Relies on RuBP enediolate intermediate; most extensively studied and widely distributed^[11]

rTCA cycle

OGOR, IDH

CO₂

2 ATP/CO₂

OGOR 1-5 s^-1

Ferredoxin-dependent reductive carboxylation, two key carboxylation steps^[12]

WL pathway

FDH, CODH/ACS

CO₂

1 ATP/CO₂

CODH/ACS 1-10 s^-1; FDH 10-100 s^-1

FDH catalyzes CO₂ reduction to formate, CODH/ACS coupled via hydrophobic channel, simultaneously forming C-C and C-S bonds^[13]

3-HP cycle

ACC, PCC

HCO₃^-

2.33 ATP/CO₂

PCC 5-15 s^-1

Uses HCO₃^- as substrate, independent of CO₂; ACC and PCC cooperate to complete the dual-cycle CO₂ fixation^[14]

3-HP/4-HB cycle

ACC, PCC

HCO₃^-

4.5 ATP/CO₂

Lower than 3-HP

Similar to 3-HP cycle, integrated with a 4-hydroxybutyrate module^[14]

Di/4-HB cycle

PFOR, PEPC

CO₂/HCO₃^-

5 ATP/CO₂

PEPC 50-200 s^-1; PFOR 0.5-5 s^-1

PFOR utilizes reduced ferredoxin; PEPC is biotin-independent with irreversible reaction^[15]

Carbon concentrating module

CO₂

No ATP consumption

k_cat 10⁴-10⁶ s^-1

Efficiently and reversibly catalyzes CO₂/HCO₃^- conversion; used to construct carbon-concentrating modules^[16]

Methane metabolism pathway

MMO

Methane

sMMO

10-50 nmol/(min·mg)

Uses O₂ as electron acceptor oxidant to oxidize methane to methanol, forming the first intermediate of the methane metabolism pathway^[17]

Methanol metabolism pathway

MDH

Methanol

NAD-MDH 10-100 s^-1; PQQ-MDH 100-1 000 s^-1

Catalyzes oxidation of methanol to formaldehyde, playing a central role in C1 metabolism of methylotrophs^[18]

Serine pathway

SHMT

Formaldehyde

3 ATP/formaldehyde

Key step of C1 fixation in the serine pathway^[19-20]

Serine pathway

Tetrahydrofolate-dependent enzyme

C1 units

3 ATP/formaldehyde

Multi-enzyme cooperation responsible for transport of formyl, methylene, and other C1 units^[19-20]

RuMP pathway

HPS, PHI

Formaldehyde

No ATP consumption

Formaldehyde fixation^[21]

Carbon fixation pathway	Key carbon fixation enzymes	Substrate	Thermodynamic efficiency	Theoretical maximum carboxylation rate	Catalytic features
CETCH cycle	ECR	HCO₃^-	5 ATP+6 NADPH	0.05-0.5 s^-1	Simultaneously achieves enoyl-CoA reduction and carboxylation, NADPH-dependent, engineered variant showed a 5.5-fold improvement in k_cat/K_m compared to the wild-type^[22]
ASAP pathway	FLS	Formaldehyde	No ATP consumption	0.8-4 s^-1	TPP-dependent, catalyzes the condensation of 2 formaldehyde molecules to form glycolaldehyde, saturation mutagenesis at the active site improved its catalytic activity by 7.6-fold^[23]
SACA pathway	GALS, PK	Formaldehyde	1 ATP/2 HCHO	GALS 0.01-0.1 s^-1; PK 1-10 s^-1	GALS was obtained through de novo computational design, PK was engineered via computational simulation and structural analysis to expand its substrate spectrum^[24]

Carbon fixation pathway

Key carbon fixation enzymes

Substrate

Thermodynamic efficiency

Theoretical maximum carboxylation rate

Catalytic features

CETCH cycle

ECR

HCO₃^-

5 ATP+6 NADPH

0.05-0.5 s^-1

Simultaneously achieves enoyl-CoA reduction and carboxylation, NADPH-dependent, engineered variant showed a 5.5-fold improvement in k_cat/K_m compared to the wild-type^[22]

ASAP pathway

FLS

Formaldehyde

No ATP consumption

0.8-4 s^-1

TPP-dependent, catalyzes the condensation of 2 formaldehyde molecules to form glycolaldehyde, saturation mutagenesis at the active site improved its catalytic activity by 7.6-fold^[23]

SACA pathway

GALS, PK

Formaldehyde

1 ATP/2 HCHO

GALS

0.01-0.1 s^-1;

PK 1-10 s^-1

GALS was obtained through de novo computational design, PK was engineered via computational simulation and structural analysis to expand its substrate spectrum^[24]

Strategy	Representative example	Key structural features	Engineering implications
Directed transfer of substrates and intermediates	CODH/ACS	Single-particle cryo-EM revealed the fine arrangement of the Ni-Fe cluster active centers, and identified a hydrophobic gas channel connecting CODH and ACS for directed CO transport	Design artificial channel proteins to directionally transport intermediates in tandem enzyme reactions, improving catalytic cascade efficiency
Spatial organization of electron transfer systems	PFOR/OGOR	Multiple [Fe₄S₄] clusters are linearly distributed along specific pathways within each subunit, constituting an efficient electron transfer network	Rationally design oxidoreductase complexes in artificial carbon fixation pathways, optimize cofactor spatial arrangement, and enhance electron transfer rates
Conformational dynamics-driven catalytic regulation	ACC	The BC and CT domains are connected by a flexible linker peptide; the biotin arm carrying the carboxyl group undergoes large-scale “swinging” between the two domains to complete carboxyl transfer	Utilize allosteric sites to construct metabolite-responsive biosensors, or engineer allosteric effector specificity via directed evolution to achieve orthogonal metabolic regulatory circuits
PEPC	The cleft between subunits of the homotetramer stabilizes the active site conformation and forms allosteric regulatory sites that respond to signals such as acetyl-CoA (activation) and aspartate (inhibition)

Strategy

Representative example

Key structural features

Engineering implications

Directed transfer of substrates and intermediates

CODH/ACS

Single-particle cryo-EM revealed the fine arrangement of the Ni-Fe cluster active centers, and identified a hydrophobic gas channel connecting CODH and ACS for directed CO transport

Design artificial channel proteins to directionally transport intermediates in tandem enzyme reactions, improving catalytic cascade efficiency

Spatial organization of electron transfer systems

PFOR/OGOR

Multiple [Fe₄S₄] clusters are linearly distributed along specific pathways within each subunit, constituting an efficient electron transfer network

Rationally design oxidoreductase complexes in artificial carbon fixation pathways, optimize cofactor spatial arrangement, and enhance electron transfer rates

Conformational dynamics-driven catalytic regulation

ACC

The BC and CT domains are connected by a flexible linker peptide; the biotin arm carrying the carboxyl group undergoes large-scale “swinging” between the two domains to complete carboxyl transfer

Utilize allosteric sites to construct metabolite-responsive biosensors, or engineer allosteric effector specificity via directed evolution to achieve orthogonal metabolic regulatory circuits

PEPC

The cleft between subunits of the homotetramer stabilizes the active site conformation and forms allosteric regulatory sites that respond to signals such as acetyl-CoA (activation) and aspartate (inhibition)

Feature	Greenase	General databases (UniProt, PubMed, PDB)	Specialized databases (NFixDB, P450Rdb)
Scope	Focuses on carbon-fixing enzymes from natural and artificial carbon fixation pathways	Broad biological scope, but not specifically targeting carbon fixation	Focuses on specific enzyme systems (nitrogenases, P450)
Functional annotation	Contains K_m/k_cat data, EC number search, and descriptions related to catalytic conditions	Annotation is general or incomplete	Limited to annotations related to specific enzyme families
Pathway integration	Carbon fixation pathways	Not pathway-oriented, information is scattered	Limited to a single metabolic or catalytic pathway
Tools	Structure clustering and auxiliary enzyme recommendations	Provides raw structural data	Basic structure or reaction visualization
Design purpose	Enzyme discovery and biocatalytic applications in the field of carbon fixation	General biological reference	Specialized research for specific enzyme classes

Feature

Greenase

General databases (UniProt, PubMed, PDB)

Specialized databases (NFixDB, P450Rdb)

Scope

Focuses on carbon-fixing enzymes from natural and artificial carbon fixation pathways

Broad biological scope, but not specifically targeting carbon fixation

Focuses on specific enzyme systems (nitrogenases, P450)

Functional annotation

Contains K_m/k_cat data, EC number search, and descriptions related to catalytic conditions

Annotation is general or incomplete

Limited to annotations related to specific enzyme families

Pathway integration

Carbon fixation pathways

Not pathway-oriented, information is scattered

Limited to a single metabolic or catalytic pathway

Tools

Structure clustering and auxiliary enzyme recommendations

Provides raw structural data

Basic structure or reaction visualization

Design purpose

Enzyme discovery and biocatalytic applications in the field of carbon fixation

General biological reference

Specialized research for specific enzyme classes