Catalytic Efficiency Of Enzyme Research Articles

Assay Replicability in β-Glucosidase Enzyme Kinetics Across Laboratories

Replicability is the foundation of research in any scientific discipline. Despite this fact, few studies address experimental variability within and across multiple institutions that operate under the same protocol. While consistency is usually well documented within the same lab, multi-institutional experiments may introduce new variables and, therefore, variability that may lead to inconsistent results. This study seeks to explore intra- and interinstitutional variability among enzyme catalytic efficiency values (KM and Kcat/KM) for the wild type of β-Glucosidase derived from Paenibacillus polymyxa. A standardized protocol for the assay was provided to all institutions that participated in the study. The analysis was conducted using data from 13 laboratories across the United States. The information was collected through the Design2Data CURE database. A total of 132 independent assays of β-Glucosidase were analyzed. Statistical analysis of Kcat/KM , KM, and T50 was conducted using SPSS, and Whisker Plots with a 90% confidence interval were generated for all parameters. Acceptance intervals for the parameters assayed of β-Glucosidase were determined; these could be used in all future experiments in the network as a reference by current and incoming laboratory members that incorporate into the network yearly. Ultimately, we aim to identify possible errors and misunderstandings in the protocol we use in the laboratories of the D2D network to improve assay replicability across institutions. High variability may be a concern when data is interpreted across institutions. This specific assay is used as a control for other, more complex assays in the CURE network and, therefore, the variability found can potentially lead to incorrect interpretation of results. It also highlights the high variability of a simple enzymatic assay when it is replicated in laboratories with different personnel and equipment, regardless of using the same standardized protocol.

Enhanced Catalytic Activity of a de novo Enzyme in a Coacervate Phase

Biomolecular condensates are membraneless organelles that orchestrate various metabolic pathways in living cells. Understanding how these crowded structures regulate enzyme reactions remains yet challenging due to their dynamic and intricate nature. Coacervate microdroplets formed by associative liquid‐liquid phase separation of oppositely charged polyions have emerged as relevant condensate models to study enzyme catalysis. Enzyme reactions within these droplets show altered kinetics, influenced by factors such as enzyme and substrate partitioning, crowding, and interactions with coacervate components; it is often challenging to disentangle the contributions of each. Here, we investigate the peroxidase activity of a de novo enzyme within polysaccharide‐based coacervates. By comparing the reaction kinetics in buffer, in a suspension of coacervates and in the bulk coacervate phase collected after centrifugation of the droplets, we show that the coacervate phase significantly increases the enzyme catalytic efficiency. We demonstrate that the main origin of this enhanced activity lies in macromolecular crowding coupled to changes in the conformational dynamics of the enzyme within the coacervate environment. Altogether, these findings underline the crucial role of the coacervate matrix in enzyme catalysis, beyond simple partitioning effects. The observed boost in enzyme activity within the coacervate phase provides insights for designing biocatalytically active synthetic organelles.

Understanding the Interactions of Ubiquitin-Specific Protease 7 with Its Substrates through Molecular Dynamics Simulations: Insights into the Role of Its C-Terminal Domains in Substrate Recognition.

Ubiquitin-specific protease 7 (USP7) is a deubiquitinase enzyme that plays a critical role in regulating various cellular processes by cleaving ubiquitin molecules from target proteins. The C-terminal loop (CTL) motif is a specific region at the C-terminal end of the USP7 enzyme. Recent experiments suggest that the CTL motif plays a role in USP7's catalytic activity by contributing to the enzyme's structural stability, substrate recognition, and catalytic efficiency. The objective of this work is to elucidate these roles through the utilization of computational methods for molecular simulations. For this, we conducted extensive molecular dynamics (MD) simulations to investigate the conformational dynamics and protein-protein interactions within the USP7 enzyme-substrate complex with the substrate consisting of the ubiquitin tagged with the fluorescent label rhodamine 110-gly (Ub-Rho). Our results demonstrate that the CTL motif plays a crucial role in stabilizing the Ubl domains' conformation and augmenting the stability of active conformations within the enzyme-substrate complex. Conversely, the absence of the CTL motif results in increased flexibility and variability in Ubl domains' motion, leading to a reduced percentage of active conformations. Furthermore, our analysis of protein-protein interactions highlights the significance of the CTL motif in anchoring the Ubl45 domains to the catalytic domain (CD), thereby facilitating stable interactions with the substrate. Overall, our findings provide valuable insights into the conformational dynamics and protein-protein interactions inherent in the USP7 enzyme-substrate complex. These insights shed light on some mechanistic details of USP7 concerning the substrate's recognition before its catalytic action.

Balancing the pretreatment effect of deep eutectic solvents on biomass and the activity of β-glucosidase originating from Paenibacillus sp. LLZ1

The two major impediments to biomass resourcing are the catalytic efficiency of enzymes and the effectiveness of biomass pretreatment. In this study, six genes encoding β-Glucosidases (BGLs) derived from Paenibacillus sp. LLZ1 were cloned and expressed. The activity of BGL-F, which had the highest enzyme activity, was 24.1 U/mg, which was 39.8–83.7% higher than that of the other BGLs. Molecular docking and surface charge analyses showed that the binding energy of BGL-F to cellobiose and its electronegative ligand-binding pocket were greater than those of other BGLs. On the other hand, by calculating and comparing the Kamlet–Taft (KT) values of deep eutectic solvent (DES) composed of different hydrogen bond donors (HBD) and hydrogen bond acceptors (HDA), it was found that DES composed of betaine and glycerol had the highest α value of 0.97, meaning that it could provide the highest hydrogen bonding capacity, and thus it had the best pretreatment effect on biomass. Analysis by circular dichroism (CD) spectroscopy revealed a decrease in α-helix and an increase in β-strand in the secondary structure of the DES-treated BGL-F, implying an increase in enzyme activity and stability. This result was also confirmed experimentally by the fact that the Km and Vmax of the enzyme in the DES system increased by 13.2% and 57.9%, respectively, and the inactivation rate (kd) decreased by 21.4%. The results of this study showed that DES consisting of glycerol-betaine achieved a better balance between the promotion of enzyme activity and biomass pretreatment.

Nanomaterials for co‐immobilization of multiple enzymes

AbstractIn order to co‐immobilize multiple enzymes, a wide range of nanomaterials has been designed to achieve synergistic enzyme activity and enhance catalytic efficiency. Nanomaterials, as carriers for enzyme co‐immobilization, possess various advantages such as tunable morphology and size, high specific surface area, and abundant chemically active sites. They can significantly enhance enzyme stability, activity, and catalytic efficiency. We overview the commonly used methods and strategies of enzyme co‐immobilization. This review further summarizes the latest research advances in nanomaterials for enzyme co‐immobilization applications over the past 5 years. Meanwhile, the advantages and challenges of these nanomaterials used for enzyme co‐immobilization as well as some potential future directions are also discussed.

Protein-directed hydrogen-bonded organic framework with enhanced enzyme stability and catalytic efficiency for sensitive colorimetric/fluorometric immunoassays

The fragility inherent in enzymes can be overcome by immobilizing them within nano-carriers, which offer designability and controllability and serve as a promising strategy for overcoming the inherent fragility of enzymes. While enzyme immobilization enhances enzyme stability and reusability, it can potentially hinder their bioactivity and catalytic efficiency. In this study, we present an enzyme-directed biomimetic mineralization approach for the in situ encapsulation of horseradish peroxidase (HRP) within hydrogen-bonded organic frameworks (HOFs) to obtain HOF@HRP nanocomposites. Remarkably, the HOF@HRP nanocomposites exhibit an ultrahigh protein content and demonstrate comparable catalytic activity to that of the free enzyme. Moreover, the HOFs act as protective shields, safeguarding the internal enzymes against various environmental disturbances. Leveraging the unique properties of HOF@HRP, we propose a dual-modal enzyme-linked immunosorbent assay for the sensitive detection of prostate-specific antigen in human serum. The resultant biosensor exhibits a good linear range, excellent sensitivity, and selectivity, showcasing its promising potential and clinical application in the field of diagnostic medicine.

Substrate Positioning Dynamics Involves a Non-Electrostatic Component to Mediate Catalysis.

Substrate positioning dynamics (SPD) orients the substrate in the active site, thereby influencing catalytic efficiency. However, it remains unknown whether SPD effects originate primarily from electrostatic perturbation inside the enzyme or can independently mediate catalysis with a significant non-electrostatic component. In this work, we investigated how the non-electrostatic component of SPD affects transition state (TS) stabilization. Using high-throughput enzyme modeling, we selected Kemp eliminase variants with similar electrostatics inside the enzyme but significantly different SPD. The kinetic parameters of these mutants were experimentally characterized. We observed a valley-shaped, two-segment linear correlation between the TS stabilization free energy (converted from kinetic parameters) and substrate positioning index (a metric to quantify SPD). The energy varies by approximately 2 kcal/mol. Favorable SPD was observed for the distal mutant R154W, increasing the proportion of reactive conformations and leading to the lowest activation free energy. These results indicate the substantial contribution of the non-electrostatic component of SPD to enzyme catalytic efficiency.

UniKP: a unified framework for the prediction of enzyme kinetic parameters

Prediction of enzyme kinetic parameters is essential for designing and optimizing enzymes for various biotechnological and industrial applications, but the limited performance of current prediction tools on diverse tasks hinders their practical applications. Here, we introduce UniKP, a unified framework based on pretrained language models for the prediction of enzyme kinetic parameters, including enzyme turnover number (kcat), Michaelis constant (Km), and catalytic efficiency (kcat / Km), from protein sequences and substrate structures. A two-layer framework derived from UniKP (EF-UniKP) has also been proposed to allow robust kcat prediction in considering environmental factors, including pH and temperature. In addition, four representative re-weighting methods are systematically explored to successfully reduce the prediction error in high-value prediction tasks. We have demonstrated the application of UniKP and EF-UniKP in several enzyme discovery and directed evolution tasks, leading to the identification of new enzymes and enzyme mutants with higher activity. UniKP is a valuable tool for deciphering the mechanisms of enzyme kinetics and enables novel insights into enzyme engineering and their industrial applications.

Recent advances in poly phosphate kinase (PPK) and the construction of PPK-mediated ATP regeneration system

Adenosine triphosphate (ATP) regeneration systems are essential for efficient biocatalytic phosphoryl transfer reactions. Polyphosphate kinase (PPK) is a versatile enzyme that can transfer phosphate groups among adenosine monophosphate (AMP), adenosine diphosphate (ADP), ATP, and polyphosphate (Poly P). Utilization of PPK is an attractive solution to address the problem of ATP regeneration due to its ability to use a variety of inexpensive and stable Poly P salts as phosphate group donors. This review comprehensively summarizes the structural characteristics and catalytic mechanisms of different types of PPKs, as well as the variations in enzyme activity, catalytic efficiency, stability, and coenzyme preference observed in PPKs from different sources. Moreover, recent advances in PPK-mediated ATP regeneration systems and protein engineering of wild-type PPK are summarized.

Engineered β-glycosidase from Hyperthermophilic Sulfolobus solfataricus with Improved Rd-hydrolyzing Activity for Ginsenoside Compound K Production.

Hyperthermophilic Sulfolobus solfataricus β-glycosidase (SS-βGly), with higher stability and activity than mesophilic enzymes, has potential for industrial ginsenosides biotransformation. However, its relatively low ginsenoside Rd-hydrolyzing activity limits the production of pharmaceutically active minor ginsenoside compound K (CK). In this study, first, we used molecular docking to predict the key enzyme residues that may hypothetically interact with ginsenoside Rd. Then, based on sequence alignment and alanine scanning mutagenesis approach, key variant sites were identified that might improve the enzyme catalytic efficiency. The enzyme catalytic efficiency (kcat/Km) and substrate affinity (Km) of the N264D variant enzyme for ginsenoside Rd increased by 60% and decreased by 17.9% compared with WT enzyme, respectively, which may be due to a decrease in the binding free energy (∆G) between the variant enzyme and substrate Rd. In addition, Markov state models (MSM) analysis during the whole 1000-ns MD simulations indicated that altering N264 to D made the variant enzyme achieve a more stable SS-βGly conformational state than the wild-type (WT) enzyme and corresponding Rd complex. Under identical conditions, the relative activities and the CK conversion rates of the N264D enzyme were 1.7 and 1.9 folds higher than those of the WT enzyme. This study identified an excellent hyperthermophilic β-glycosidase candidate for industrial biotransformation of ginsenosides.

MECE: a method for enhancing the catalytic efficiency of glycoside hydrolase based on deep neural networks and molecular evolution

The demand for high efficiency glycoside hydrolases (GHs) is on the rise due to their various industrial applications. However, improving the catalytic efficiency of an enzyme remains a challenge. This investigation showcases the capability of a deep neural network and method for enhancing the catalytic efficiency (MECE) platform to predict mutations that improve catalytic activity in GHs. The MECE platform includes DeepGH, a deep learning model that is able to identify GH families and functional residues. This model was developed utilizing 119 GH family protein sequences obtained from the Carbohydrate-Active enZYmes (CAZy) database. After undergoing ten-fold cross-validation, the DeepGH models exhibited a predictive accuracy of 96.73%. The utilization of gradient-weighted class activation mapping (Grad-CAM) was used to aid us in comprehending the classification features, which in turn facilitated the creation of enzyme mutants. As a result, the MECE platform was validated with the development of CHIS1754-MUT7, a mutant that boasts seven amino acid substitutions. The kcat/Km of CHIS1754-MUT7 was found to be 23.53 times greater than that of the wild type CHIS1754. Due to its high computational efficiency and low experimental cost, this method offers significant advantages and presents a novel approach for the intelligent design of enzyme catalytic efficiency. As a result, it holds great promise for a wide range of applications.

Investigating the effect of substrate binding on the catalytic activity of xylanase.

XynAF1 from Aspergillus fumigatus Z5 is an efficient thermophilic xylanase belonging to glycoside hydrolase family 10 (GH10). The non-catalytic amino acids N179 and R246 in its catalytic center formed one and three intermolecular H-bonds with the substrate in the aglycone region, respectively. Here we purified XynAF1-N179S and XynAF1-R246K, and obtained the protein-product complex structures by X-ray diffraction. The snapshots indicated that mutations at N179 and R246 had decreased the substrate-binding ability in the aglycone region. XynAF1-N179S, XynAF1-R246K, and XynAF1-N179S-R246K lost one, three, and four H-bonds with the substrate in comparison with the wild-type XynAF1, respectively, but this had little influence on the protein structure. As expected, N179S, R246K, and N179S-R246K led to a gradual decrease of substrate affinity of XynAF1. Interestingly, the enzyme assay showed that N179S increased catalytic efficiency, while both R246K and N179S-R246K had decreased catalytic efficiency. KEY POINTS: • The non-catalytic amino acids of XynAF1 could form H-bonds with the substrate. • The protein-product complex structures were obtained by X-ray diffraction. • The enzyme-substrate-binding capacity could affect enzyme catalytic efficiency.

Advancing Enzyme's Stability and Catalytic Efficiency through Synergy of Force-Field Calculations, Evolutionary Analysis, and Machine Learning.

Thermostability is an essential requirement for the use of enzymes in the bioindustry. Here, we compare different protein stabilization strategies using a challenging target, a stable haloalkane dehalogenase DhaA115. We observe better performance of automated stabilization platforms FireProt and PROSS in designing multiple-point mutations over the introduction of disulfide bonds and strengthening the intra- and the inter-domain contacts by in silico saturation mutagenesis. We reveal that the performance of automated stabilization platforms was still compromised due to the introduction of some destabilizing mutations. Notably, we show that their prediction accuracy can be improved by applying manual curation or machine learning for the removal of potentially destabilizing mutations, yielding highly stable haloalkane dehalogenases with enhanced catalytic properties. A comparison of crystallographic structures revealed that current stabilization rounds were not accompanied by large backbone re-arrangements previously observed during the engineering stability of DhaA115. Stabilization was achieved by improving local contacts including protein-water interactions. Our study provides guidance for further improvement of automated structure-based computational tools for protein stabilization.

Soil enzyme kinetics and thermodynamics in response to long-term vegetation succession

Our current knowledge regarding soil organic matter (SOM) turnover during vegetation succession is often limited to conventional C decomposition models. However, microbial enzyme-mediated SOM degradation and nutrient cycling are mainly reflected in the kinetic parameters of these enzymes. Changes in the composition and structure of plant communities are typically accompanied by alterations in soil ecological functions. Therefore, it is important to clarify the kinetic parameters of soil enzymes and their temperature sensitivity in response to vegetation succession, especially under the current trend of climate change-related global warming; however, these are still understudied. Here, we examined the kinetic parameters of soil enzymes, their temperature sensitivity, and their associations with environmental variables over long-term (approximately 160 years) vegetation succession on the Loess Plateau using a space-for-time substitution method. We found that the kinetic parameters of soil enzymes changed significantly during vegetation succession. Specific response characteristics varied depending on the enzyme. Overall, the temperature sensitivity (Q10, 0.79–1.87) and activation energy (Ea, 8.69–41.49 kJ·mol−1) remained stable during long-term succession. Compared with N-acetyl-glucosaminidase and alkaline phosphatase, β-glucosidase was more sensitive to extreme temperatures. In particular, two kinetic parameters (i.e., maximum reaction rate, Vmax; half-saturation constant, Km) of β-glucosidase were decoupled at low (5 °C) and high (35 °C) temperatures. Overall, Vmax was the primary determinant of variations of enzyme catalytic efficiency (Kcat) during succession, and soil total nutrients had a greater impact on Kcat than available nutrients. Our results suggested that soil ecosystems played an increasingly important role as a C source during long-term vegetation succession, as indicated by the positive responses of the C cycling enzyme Kcat, while the factors related to soil N and P cycling remained relatively stable.

The yeast ALA synthase C-terminus positively controls enzyme structure and function.

5-Aminolevulinic acid synthase (ALAS) is a pyridoxal 5'-phosphate (PLP)-dependent enzyme that catalyzes the first and rate-limiting step of heme biosynthesis in α-proteobacteria and several non-plant eukaryotes. All ALAS homologs contain a highly conserved catalytic core, but eukaryotes also have a unique C-terminal extension that plays a role in enzyme regulation. Several mutations in this region are implicated in multiple blood disorders in humans. In Saccharomyces cerevisiae ALAS (Hem1), the C-terminal extension wraps around the homodimer core to contact conserved ALAS motifs proximal to the opposite active site. To determine the importance of these Hem1 C-terminal interactions, we determined the crystal structure of S. cerevisiae Hem1 lacking the terminal 14 amino acids (Hem1 ΔCT). With truncation of the C-terminal extension, we show structurally and biochemically that multiple catalytic motifs become flexible, including an antiparallel β-sheet important to Fold-Type I PLP-dependent enzymes. The changes in protein conformation result in an altered cofactor microenvironment, decreased enzyme activity and catalytic efficiency, and ablation of subunit cooperativity. These findings suggest that the eukaryotic ALAS C-terminus has a homolog-specific role in mediating heme biosynthesis, indicating a mechanism for autoregulation that can be exploited to allosterically modulate heme biosynthesis in different organisms.

Differences in available phosphorus in temperate and subtropical forest soils

Soil P availability is influenced by the acid phosphomonoesterase (ACP) activity, microbial biomass P (MBP), pH, and other soil properties. To date, there is no clear understanding about how the enzyme catalytic efficiency (Vmax/Km) and the abundance of the phoC and phoD genes that encode ACP and alkaline phosphomonoesterase (ALP) influence the available P contents at different depths in temperate and subtropical forest soils. We investigated how the soil enzyme kinetic parameters, phoC and phoD gene abundance, pH, total P contents, and other soil properties influenced the P availability in soils from a temperate forest (ChangBai Mountain) and a subtropical forest (QianYanZhou Plantation). The results showed that the DNA contents and the ACP and ALP activities were positively correlated with the available P contents in the temperate forest soil. The phoC and phoD gene abundance and the ALP activity were positively correlated with the available P contents in the subtropical forest soil. The ACP-Vmax/Km and DNA contents were positively correlated with the available P contents in topsoil (0–10 cm). The total P contents, pH, MBP, and ACP-Vmax/Km in subsoil (10–30 cm) were positively correlated with the available P contents. A structural equation model showed that DNA content had the greatest effect on the soil available P in temperate forest soil, and phoC and phoD gene abundance had the greatest effect on the soil available P in subtropical forest soil. The mechanism of H+ dissolution affected the P availability through low pH in the topsoil and weathering in the subsoil. Overall, these findings provided an improved understanding about how the catalytic efficiencies of ACP and ALP and the phoC and phoD gene abundance, influenced the P availability in temperate and subtropical forest soils at different depths. We also gained insights into how the P availability was affected by H+ dissolution and the parent material in topsoil and subsoil, respectively.

Dual/Triple Template-Induced Evolved Emulsion for Controllable Construction of Anisotropic Carbon Nanoparticles from Concave to Convex.

Anisotropic mesoporous carbon (AMC) nanoparticles with asymmetric external morphologies, topological internal structure, and superior performance of carbon species are attracting great attention because of their seductive features differentiating them from symmetric nanoparticles. However, a bewildering challenge but crucial desire remains to endow them with flexibly tunable morphology and pore structure. Herein, a dual/triple-templating evolved emulsion strategy for tunable fabrication of AMC nanoparticles with distinctive defined structure by interface-energy-induced self-assembly is first reported based on a brand-new mechanism. It describes the possible formation process of the concave-cavity structure and allows for manipulation of the longitudinal and lateral sizes systematically by adjusting emulsion polarity and sodium oleate dosage, respectively. Interestingly, the internal pore structure can be rearranged into radial channels and the external morphology can realize structural transformation from concave to convex by innovatively introducing the third template n-hexanol, which is unprecedented at nanoscale. Remarkably, due to the excellent properties of carbon species and unique structural characteristics, AMC nanoparticles not only demonstrate good biocompatibility but also exhibit splendid performance in improving the dissolution and release rates of insoluble drug and enhancing the enzyme catalytic efficiency. Generally, this approach provides new inspiration and insights for expanding exquisite anisotropic nanomaterials for many potential applications.

Engineering magnetic nanobiocatalytic systems with multipurpose functionalities for biocatalysis, biotechnology and bioprocess applications

Enzymes are high-performance natural biological catalysts with wide-ranging applications in agricultural, medical, food and environmental sectors. Nevertheless, lack of efficient recovery, reusability, and high cost of the soluble form of enzymes are the most daunting challenges rendering biocatalytic systems inadequate for industrial exploitation. In order to deal with these inadequacies, immobilization appears to be a prodigious approach for enhancing the stability and catalytic efficiency of enzymes, as well as enabling their separation and reusability in continuous reaction batches. Among different nanostructures, magnetic nanomaterials have garnered supreme interest as support matrices for biomolecules and enzymes immobilization because of their substantial surface area, larger surface-to-volume ratio, modifiable surface, and adjustable surface particle size, stability, and high mass transferring ability. In addition, they can be quickly recovered from the complex reaction system by a simple external magnetic field. Magnetic nanoparticles incorporated biocatalysts demonstrated a broad-working temperature and pH profile and augmented storage and thermal stabilities compared to their native derivatives. This paper provides a recent and state-of-the-art overview of the development and application of multifunctional magnetic nanobiocatalytic systems for an array of biotechnological purposes. In the first half, the development, functionalization, and use of nanostructured magnetic materials as enzyme immobilization supports are delineated. Then the prospective applications of magnetic nanobiocatalytic systems in different industrial sectors, including wastewater treatment, biodiesel and butanol production, hydrolysis of lignocellulosic biomass, glucose monitoring, fruit juice extraction and clarification, and synthesis of non-natural benzylisoquinoline alkaloid are comprehensively vetted with representative examples. Finally, the conclusive points and future prospects in this evolving field are also directed.

Co‐compartmentalization of Enzymes and Cofactors within Pickering Emulsion Droplets for Continuous‐Flow Catalysis

AbstractCo‐immobilization of enzymes and cofactors in a manner suitable for use in continuous flow catalysis remains a great challenge because of the difficulty in ensuring the free accessibility of immobilized enzymes and cofactors. Herein, we present a continuous flow catalysis system based on co‐compartmentalization of enzymes and cofactors within Pickering emulsion droplets, enabling regeneration of cofactors within the droplets. As exemplified by enzyme‐catalyzed ketone enantioselective reduction and enantioselective transamination, our systems exhibit long‐term stability (300–400 h), outstanding total turnover number (TTN, 59204 mol mol−1) and several‐fold enhancement in the enzyme catalytic efficiency (CEe) in comparison to conventional biphasic reactions. As well as giving insight into the co‐compartmentalization effects, our system will provide the opportunity to significantly advance continuous‐flow biocatalysis towards the level of practical applications.

Co-compartmentalization of Enzymes and Cofactors within Pickering Emulsion Droplets for Continuous-Flow Catalysis.

Co-immobilization of enzymes and cofactors in a manner suitable for use in continuous flow catalysis remains a great challenge because of the difficulty in ensuring the free accessibility of immobilized enzymes and cofactors. Herein, we present a continuous flow catalysis system based on co-compartmentalization of enzymes and cofactors within Pickering emulsion droplets, enabling regeneration of cofactors within the droplets. As exemplified by enzyme-catalyzed ketone enantioselective reduction and enantioselective transamination, our systems exhibit long-term stability (300-400 h), outstanding total turnover number (TTN, 59204 mol mol-1 ) and several-fold enhancement in the enzyme catalytic efficiency (CEe ) in comparison to conventional biphasic reactions. As well as giving insight into the co-compartmentalization effects, our system will provide the opportunity to significantly advance continuous-flow biocatalysis towards the level of practical applications.