Efficient Design Strategies for Nanozymes

Jiangjiexing Wu; Hui Wei

doi:10.7536/PC201117

Progress in Chemistry ›› 2021, Vol. 33 ›› Issue (1) : 42-51 DOI: 10.7536/PC201117

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Efficient Design Strategies for Nanozymes

Jiangjiexing Wu ¹
, Hui Wei ¹^,²^,^*

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Abstract

The enzyme-like activity of nanozymes is an emerging effect of nanomaterials. Due to the excellent physicochemical properties and unique enzyme-like activities, nanozymes have become promising functional nanomaterials. Till now nanozymes have been used in biomedical sensing, diagnosis and therapeutics, as well as environment protection. Despite of the great success achieved in the past several decades, how to efficiently design nanozymes is still one of the bottlenecks in the field, which is originated from the complicated composition and ambiguity in the active sites of nanomaterials. To tackle these challenges, this insight first summarizes the current efficient design strategies of nanozymes, such as computation-aided high throughput screening, rational design, and biomimetic design. And then, the development of bio-inspired metal-organic framework(MOF) nanozymes, particularly the structure-activity relationship study, is highlighted. At the end, combined with current research trend, several directions and inspirations for the future study are suggested to advance the nanozymes research.

Contents

1 An emerging effect of nanomaterials:enzyme-like activity of nanozymes

2 One of the bottlenecks:how to efficiently design nanozymes

2.1 Computation-aided high throughput screening

2.2 Rational design

2.3 Biomimetic design

3 Bio-inspired design of MOF nanozyme and its structure-activity relationship

4 Conclusions and outlook

Graphical abstract

Keywords

nanozyme / computation-aided high throughput screening / rational design / biomimetic design / metal-organic framework / protein engineering / structure-activity relationship

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Jiangjiexing Wu, Hui Wei. Efficient Design Strategies for Nanozymes. Progress in Chemistry, 2021, 33(1): 42-51 DOI:10.7536/PC201117

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1 Nanoscale New Effect: Enzyme-like Catalysis of Nanoscale Enzymes

Nanoscience is a science that studies the composition, characteristics and applications of substances at the nanoscale (1 ~ 100 nm). Compared with macro-scale bulk materials, studies have shown that nano-scale endows materials with new special properties, such as surface effect, volume effect and quantum effect, which significantly changes the physical and chemical properties of nano-materials, such as light, electricity, magnetism and force (Fig. 1)^[1]^[2]^[3]^[4]. For example, compared with bulk magnetic particles, the coercivity of magnetic nanoparticles can be increased when the size is reduced to nano-scale, and the coercivity of magnetic nanoparticles will be reduced to 0 when the size is further reduced to less than 20 nm, showing superparamagnetism^[3]. Therefore, in recent years, with the development of nanotechnology, nanomaterials have been widely used in biomedicine, electronic equipment, chemical industry, people's livelihood, aerospace and other fields.

Nano-enzyme is a kind of functional nanomaterials with enzyme-like catalytic activity, which is a new effect of materials at the nanometer scale. Generally, nanomaterials (especially inorganic nanomaterials) are not considered to have biological effects, and when such biologically inert nanomaterials are used, some enzymes or other groups with catalytic properties need to be modified on their surfaces. For example, gold nanoparticles are modified to have certain enzyme-like catalytic activities, but these activities come from the ligands modified on the surface of gold nanoparticles, not from the gold nanoparticles themselves^[5]. In 2007, Chinese scientist Yan Xiyun and others found that ferroferric oxide magnetic nanoparticles themselves have peroxidase-like catalytic activity, and used them to replace natural enzymes for enzyme-linked immunoassay to detect some disease markers^[6]. This study reveals that inorganic nanomaterials contain enzymatic properties and opens up a new field of nano-enzyme research.

Compared with natural enzymes and other mimic enzymes, nano-enzymes not only have the advantages of high stability, low price and easy mass production, but also have excellent optical, electrical, magnetic and thermal properties endowed by nano-materials. In addition, the size effect, surface effect and morphology structure of nanomaterials provide an effective way to regulate the performance of nanomaterials on the one hand, and also provide the possibility for subsequent surface modification, that is, various biomolecules can be attached to the surface of nanometer-scale enzymes to construct bioanalytical probes. Therefore, as a new generation of mimetic enzyme, nano-enzyme has attracted wide attention in academia^[7]. According to incomplete statistics, more than 380 research groups from more than 30 countries, including China, the United States, Britain, Germany, France, Japan and Italy, are engaged in nanoenzyme research, involving hundreds of nanomaterials.Uch as superoxide dismutase-like fullerene derivatives, peroxidase-like ferroferric oxide, Prussian blue with various enzyme-like activities and the like, and is applied to the fields of biosensing, environmental protection, disease diagnosis and treatment and the like^[8⇓~10]. According to the statistics of Web of Science and Google Scholar, nearly 4000 academic papers have been published in the field of nano-enzymes, and continue to show an exponential upward trend (Figure 2).

2 One of the key problems in the development of nanomaterials is how to design nanomaterials efficiently?

Although the discovery of nano-enzymes has broken the traditional understanding of enzymes and nanomaterials, and the research of nano-enzymes has become a hot spot, and a series of breakthroughs have been made in recent years (such as the discovery of more than 500 nano-enzymes, the application of nano-enzyme biomedicine, etc.), there are still some bottlenecks in this field^[8,11]. One of them is that the design and synthesis of nanomaterials are mostly based on experience and "trial and error". However, according to the previous investigation and statistics of the existing peroxidase-like nanoenzymes by our research group, the activity of peroxidase-like nanoenzymes prepared by the existing trial-and-error method is generally low, which is several orders of magnitude lower than that of natural horseradish peroxidase (Figure 3). Therefore, how to design nanoenzyme efficiently is of great significance to further expand related research and promote practical application.

2.1 Computer-assisted high-throughput screening

The excellent properties of nanomaterials enrich the means of regulating the activity of nanomateries.With the development of nanosynthesis technology, the number of nanometer-scale enzymes prepared by experiments is increasing, and how to efficiently obtain high-performance nanometer-scale enzymes from such a large material library has become a huge challenge. The traditional experiment of trial and error has a certain degree of blindness, which not only costs a lot of time and money, but also results in the low performance of nano-enzyme. High-throughput computational screening may make up for the lack of experiment and become an effective means of efficient nano-enzyme design^[12].

Gao Xingfa and Zhao Yuliang et al. Proposed a general method for computationally assisted screening and design of peroxidase-like nanoenzymes, which was used to predict the catalytic activity of peroxidase-like nanoenzymes "de novo" (Fig. 4)^[13]. The high-throughput calculation of peroxidase-like nanoenzyme mainly adopts the density functional method, takes the earliest peroxidase-like iron oxide nanoenzyme as a model, and constructs 15 kinds of nano-iron oxide surfaces with different chemical compositions, exposed crystal planes, lattice defects and chemical modifications.The molecular mechanism and reaction kinetics of the catalytic oxidation of organic substrates by hydrogen peroxide molecules were studied, and the "three-step mechanism" characteristics of this catalytic reaction were summarized. Secondly, based on the principle of chemical reaction, they further derived the energy descriptor, volcanic curve and catalytic activity window for predicting the activity of iron oxide peroxidases. Finally, by calculating 57 metals, monometallic oxides, perovskites and carbon materials, they verified that the model can be applied to any other peroxidase-like nanoenzyme that follows a similar catalytic mechanism. This study confirms that high-throughput computational screening can achieve efficient design of nanocatalysts, accelerate the research in the field of nanocatalysts, and has certain guiding significance for experiments. However, it is worth noting that high-throughput computational screening, how to obtain appropriate database types, and how to select the best screening method and computational parameters need to be further considered and studied.

2.2 Rational design

In the existing research of enzyme nanomaterials, the trial-and-error experience method is mostly used to guide the experiment, based on the three-step method of preparation, structure and performance to explore and optimize the performance of the material, which is usually costly and time-consuming, and is not conducive to efficient design of enzyme nanomaterials. In addition to high-throughput computational screening, it can also be based on the physical and chemical principles of enzyme-like catalysis, such as the efficient design of nano-enzymes based on Sabatier rules, which transforms the traditional trial-and-error guided experiment into a rational design of theoretical prediction and experimental verification, and can predict the performance at the beginning of the experiment.

Sabatier's rule, proposed by French chemist Paul Sabatier around 1920, means that in catalytic reactions, the interaction between catalyst and reactant (product) should be neither too strong nor too weak^[14,15]. If the effect is too strong, the reaction product is difficult to desorb and the catalyst is easy to be poisoned; If the action is too weak, the reactants are difficult to combine with the catalyst, so that the reaction occurs slowly. A volcano graph can usually be made by varying the reaction rate with the adsorption of reactants on the catalyst surface, and the peak of the volcano is the best performance point in the reaction. In order to facilitate the prediction of catalytic performance and rational design of efficient catalysts, researchers have developed the use of activity descriptors to guide the design of catalysts, that is, directly using a physical/chemical property of a material as a scale to measure its catalytic reaction speed^[16]. For example, our group used ABO₃ perovskite oxide nanomaterials as model oxides to systematically study the effect of electronic structure of metal oxide nanomaterials on their peroxidase-like catalytic activity^[17]. It is found that the peroxidase-like activity of the perovskite oxide with ABO₃ varies with the number of electrons in the e_g orbital at point B, and a very obvious volcanic curve can be drawn (fig. 5). When the number of e_g electrons at the top of the volcano curve is 1.2, the performance of the LaNiO_3-δ nanoenzyme is the best. However, when the number of electrons in the e_g deviates from 0 or 2, the performance of the nanoenzyme is the worst. Furthermore, it is found that there is also an obvious volcanic relationship between the number of electrons in the e_g orbital and the peroxidase-like activity of the binary metal oxides coordinated by BO₆. Therefore, the electron occupation of the e_g orbital can be used as a descriptor for the activity of the transition metal oxide peroxidases, which provides guidance for the rational design of metal oxide nanoenzymes in the future. However, the authors also realize that on the one hand, the universality of e_g electrons as descriptors needs to be further investigated; On the other hand, it is necessary to select one or more activity descriptors to match the catalytic activity of different materials and enzymes.

2.3 Bionic design

In addition to the excellent characteristics of nanomaterials, nano-enzymes also have enzymological characteristics. Natural enzyme itself is a highly efficient catalyst, so researchers can select some dominant factors to design nanoenzymes efficiently according to the structure and catalytic principle of natural enzymes. For example, inspired by natural peroxidase, Yan Xiyun and Gao Lizeng constructed a microenvironment similar to natural enzyme by modifying histidine on the surface of ferroferric oxide (Fig. 6)^[18]. Compared with the unmodified ferroferric oxide, the affinity of the modified ferroferric oxide for hydrogen peroxide is enhanced by at least 10 times because the imidazole of the histidine side chain can form hydrogen bonds with hydrogen peroxide. Accordingly, that catalytic efficiency of the peroxidase-like enzyme is enhance by more than 20 times. Benefiting from the significantly enhanced affinity for hydrogen peroxide, the catalase-like activity of the modified Fe3O4 was also increased. Liu Juewen et al combined charged monomers with molecular imprinting on the surface of ferroferric oxide to construct a selective binding space for substrate 3,3 ', 5,5' -tetramethylbenzidine, thus significantly improving the activity and selectivity of the nanoenzyme. The catalytic efficiency and selectivity of the modified Fe3O4 nanoenzyme for 3,3 ', 5,5' -tetramethylbenzidine were 15 times and 98 times higher than those of 2,2 '-azido-bis (3-ethyl-benzothiazole-6-sulfonic acid) diammonium salt, respectively^[19]. In addition, similar to natural enzymes, researchers also regulate the activity of nano-enzymes by adjusting pH and temperature. For example, acidic conditions are favorable for peroxidase-like activity, while neutral and alkaline conditions promote superoxide dismutase-like and catalase-like activity. In most studies, researchers systematically study the pH and temperature dependence of nanoenzyme activity and then find the optimal pH and temperature^[20⇓~22].

Although the above biomimetic design can effectively control nanomatase to a certain extent, these control methods still have a large degree of randomness and limitation. In recent years, Metal-organic frameworks (MOFs) have been widely used to mimic natural enzymes because of their structural similarities with metalloproteases^[23,24]. As shown in fig. 7, MOF is a kind of organic-inorganic hybrid porous material with topological structure formed by self-assembly of metal ions or metal clusters and organic ligands. It has a clear secondary structure, independent metal sites and weakly coordinated ligands around it, similar to the structure of metalloprotease.The diversity of metal ions and ligands in the MOF structure makes its structure, pore and surface properties have greater controllability, which can effectively regulate the interaction between the MOF and reactants, thus producing higher catalytic activity and selectivity^[25]. Therefore, as an excellent biomimetic catalytic material, MOF has attracted the attention of researchers because of its unique composition, structural diversity and size controllability, and has been widely used in many fields such as analysis and detection, environmental protection and disease diagnosis and treatment^[8,26,27]. In the following, the author will introduce in detail the development and application of MOF nanoenzyme design in recent years (Note: due to space constraints, only the research on MOF framework as support material and the research on carbonization of MOF to prepare its derivatives will not be introduced here).

3 Biomimetic Design and Structure-Activity Relationship of MOF Nanoparticl

Initially, the biomimetic design of MOF nanocatalysts was mainly inspired by iron-porphyrin Fe-TCPP (TCPP = tetrakis (carboxyphenyl) porphyrin) as a prosthetic group for peroxidases and proteins, and a series of MOF nanocatalysts containing iron porphyrins were constructed, such as peroxidase-like three-dimensional porous coordination network PCN-222, PCN-600, two-dimensional sheet M-TCPP (Fe) (M is metal cobalt, zinc and copper) and copper-hemin^[28]^[29]^[30,31]^[32,33]. PCN-222 is a three-dimensional porous structure (Fig. 8) prepared by Zhou Hongcai et al. In 2012 by using metal Zr as a node to coordinate with Fe-TCPP ligand, which has good peroxidase-like catalytic activity^[28]. On the one hand, the three-dimensional porous structure can better protect the active center of porphyrin, avoid self-polymerization or decomposition, and resist harsh conditions such as acidity or high temperature; On the other hand, the active site density of the MOF can be increased to improve the catalytic efficiency, for example, the active site density of PCN-222 (Fe) can reach 34 times of that of horseradish peroxidase per molecular mass. When the coordination of the metal center of the metalloporphyrin was changed to change the catalytic activity, it was found that only PCN-222 (Fe) could react with TMB in the presence of hydrogen peroxide, while other metals (Mn, Co, Ni, Cu, Zn, etc.) Could not react with TMB.

In order to further control the catalytic activity, our group prepared a two-dimensional sheet M-TCPP (Fe) (M is metal cobalt, zinc and copper) MOF. Due to the larger specific surface area, more exposed active centers and smaller diffusion resistance of the two-dimensional structure, the two-dimensional MOF has better catalytic activity than the three-dimensional MOF, thus ensuring a more sensitive detection range (for example, the linear detection range of heparin is 0.1 to 10 μg/mL) and a lower detection limit (for example, the detection limit of heparin is 15 ng/mL)^[30]. In addition, inspired by the cascade catalytic reaction system of multiple enzymes in the subcellular region of organisms, our group also loaded a noble metal Pt nanoenzyme with good catalytic activity into PCN-222 (Mn) to improve the overall enzymatic activity of the complex by reducing the diffusion barrier of reactants and increasing the local concentration of intermediate products. The composite cascade nano-enzyme can perform synergistic catalysis and efficiently remove active oxygen substances, thereby successfully achieving the effect of treating two models of ulcerative colitis and Crohn's enteritis in mice^[34].

In addition to the above iron porphyrins as catalytically active ligands to construct MOF nanoenzymes, researchers have found that metal nodes in MOF structures can also provide biomimetic catalytic sites.For example, in view of the similarity between the structure of the Lewis acid Zr (IV) -bridged hydroxyl group in MOF (Zr-OH-Zr) and the catalytic center structure of phosphotriesterase (Zn-OH-Zn), many zirconium-based MOF materials have been used to mimic phosphotriesterase, for example, to hydrolyze phosphate bonds in chemical military agents (Fig. 9)^{[23,35⇓⇓⇓ ~39]}. A representative MOF series with Zr as the metal center, UiO-n (University of Oslo), is prepared by mixing metal zirconium and terephthalic acid, and has been widely used to simulate phosphotriesterase. For example, in 2014, Hupp, Farha et al. Found that the 400-nm-sized UiO-66 metal organic framework could catalyze the hydrolysis of diethyl p-nitrophenyl phosphate at room temperature, and the half-life of substrate hydrolysis was 45 min^[40]. Compared with the window size of the MOF (66 Å), the large size (11 × 4.55 Å) of p-nitrophenyl diethyl phosphate makes the whole catalytic reaction mainly occur on the surface of the MOF, only about 0.75% of the metal nodes participate in the reaction, and the local conversion number is 0.4 s^-1. In further research, they modified the amino group of UiO-66 to provide a proton donor-acceptor center for the Lewis acid Zr (Ⅳ). Compared with the UiO-66,UiO-66-NH₂, the half-life of the hydrolysis reaction of p-nitrophenyl diethyl phosphate is shortened to 1 min, and the surface conversion number is increased by about 20 times^[41]. In addition to UiO-66, other MOFs with similar bridging structures, such as NU-1000 and MOF-808, have been synthesized and used to hydrolyze chemical military agents. The catalytic activity of NU-1000 and MOF-808 is higher than that of UiO-66 because the coordination number of zirconium center in NU-1000 and MOF-808 is 8 and 6, respectively, which is less than that of 12-coordinated UiO-66^[42,43].

In addition to the above two typical biomimetic MOF structures, in recent years, with the development of nanoenzyme field, many types of MOF have been reported to have enzyme-like catalytic activity, such as the MOF series of Material Institute of Lavoisier (e.g. MIL-53, MIL-88 and MIL-101), the MOF series of Hong Kong University of Science and Technology (e.g. HKUST-1) and other MOFs (e.g. Cu-MOFs, Co-MOFs and bimetallic Co/2Fe^{[44⇓⇓⇓~48]}^[49]^[50⇓~52]. Recently, inspired by the double copper ion active center in natural catechol oxidase, Dong Shaojun et al. Synthesized MOF-818 structure with three copper ion centers in the ligand, which can be used to simulate natural catechol oxidase^[53]. However, it is worth noting that the performance regulation methods of these MOF nanomaterials in the existing reports are relatively limited, such as the enzyme-like performance regulation through the post-modification of ligands or metal nodes and the combination of other nanomaterials, and lack of systematic structure-activity relationship studies^[26].

As we all know, the study of structure-activity relationship of nanomaterials is severely limited by their heterogeneous elemental composition, vague active sites and complex catalytic mechanism, so the development of most nanomaterials still relies on trial-and-error methods. For natural metalloproteinases with clear structure, researchers can clearly elaborate their structure-activity relationship based on protein regulation engineering^[54]. Inspired by this, our research group selected MIL-53 (Fe) framework material with similar metal and ligand assembly structure with natural metalloprotease (Figure 10)^[55]. MIL-53 (Fe) is a one-dimensional pore structure constructed by the coordination of terephthalic acid and Fe. The effects of different substituent ligands on the activity of MIL-53 (Fe) -X oxidase-like enzyme were systematically studied by adjusting the X(X=NH₂,CH₃,H,OH,F,Cl,Br,NO₂) of the substituent on the terephthalic acid ligand. The results show that the stronger the electron-withdrawing ability of the ligand substituent is, the stronger the oxidase-like activity of MIL-53 (Fe) -X nanoenzyme is, and the Hammett linear free energy relationship between the catalytic activity and the Hammett constant of the substituent is obvious. Among them, the substitution of the strongest electron-withdrawing group nitro can increase the activity by more than ten times. In addition, the universality of this Hammett linear structure-activity relationship has been well verified in the systems of other catalytic substrates, another metal center MIL-53 (Cr) -X and another MOF structure MIL-101 (Fe) -X. This study provides a new idea for the study of structure-activity relationship of nanomaterials, and provides a solid theoretical guidance and working foundation for the subsequent efficient design of nanomaterials.

Based on the above research, our research group further used metal V to coordinate with terephthalic acid with different substituents to form MIL-47 (V) nanomatase. In this study, MOF nanomatase with glutathione peroxidase (GPx) -like activity was synthesized for the first time and used for broad-spectrum anti-inflammatory therapy (Fig. 11)^[56]. GPx is an important antioxidant enzyme in the organism, which can protect the body from oxidative damage and participate in the regulation of inflammation by catalyzing glutathione to scavenge reactive oxygen species. However, it should be pointed out that there has been no report on the use of GPx-like nanomatase alone in therapy. The reason is that the current research on GPx nanomaterials is limited by the following two factors: first, the types of materials with GPx-like enzymatic activity are limited, and only a few materials have been reported to have GPx-like enzymatic activity; Second, the activity of these GPx-like nanoenzymes is moderate, and they usually need to be combined with other antioxidants for treatment. Therefore, under the guidance of the above structure-activity relationship, a novel high-performance GPx-like nanoenzyme was efficiently designed and used in the treatment of mouse ear inflammation and enteritis, which further verified the guiding significance of the structure-activity relationship of nanoenzyme and expanded the research of biomimetic MOF.

4 Conclusion and prospect

In this review, we focus on the efficient design of nanomaterials, introduce the latest progress in high-throughput computational screening, rational design and biomimetic design strategies, summarize the biomimetic regulation methods of MOF nanomaterials, and show the rapid development trend in this field. Although some progress has been made in the efficient design of nanomaterials, the research in this field is still in its early stage. Moreover, the exponential growth of nanoenzymes has put forward higher requirements for their efficient design strategies, so there are still many works to be improved in this field to meet the rapid development needs of nanoenzymes. Some current unconventional means and methods provide new opportunities for accelerating the research and development of materials. Therefore, the author will discuss with readers the following work that can be further carried out in the field of efficient design of nanomaterials in the light of current research trends (Fig. 12).

(1) Computer-assisted high-throughput screening. Due to the long time and high cost of experimental preparation and testing, computer-assisted high-throughput screening has become a popular and effective screening method in recent years, which can quickly evaluate the specific properties of a large number of materials, so as to screen out the required materials. The existing computer-assisted high-throughput screening mainly relies on molecular simulation and quantum theory for calculation.With the development of software (such as machine learning algorithm) and hardware (such as new computer), simulation and machine learning can be further combined for efficient design of nano-enzyme.

(2) Experiment-assisted high-throughput screening. Although automation and assembly line production have become the main modes in modern industry, most scientific experiments still rely on manual operation. Therefore, limited by the experimental cycle, research costs and other factors, experiment-assisted high-throughput screening has not attracted the attention of researchers. In recent years, researchers have begun to build automated laboratories. For example, in 2020, Cooper et al published an intelligent scientific robot in Nature, which can replace human beings to complete experiments that would take several months in 2 to 3 days, optimize experimental conditions, and obtain materials with better activity than existing catalysts^[57]. Therefore, with the advent of intelligent robots and the development of experimental synthesis technologies such as soft lithography and microfluidics, experiment-assisted high-throughput screening will also become an effective means for efficient design of nanoenzymes.

It is worth noting that when the database constructed in computation-assisted and experiment-assisted high-throughput screening is large enough, the design strategy assisted by big data will also accelerate the research and development process of efficient design of nano-enzymes, and have great guiding significance for subsequent experimental design and preparation, and promote the application and development of nano-enzymes.

(3) Rational design. Nano-enzyme is a kind of functional nanomaterials, so it has some special physical and chemical properties of nanomaterials. In previous studies, our group has reported that e_g electrons can be used as descriptors to predict the effect of electronic structure of metal oxide nanomaterials on their peroxidase-like catalytic activity. However, the universality of this descriptor for different material systems and different enzyme catalytic activities needs to be further studied. Clarifying the mechanism of enzyme-like catalytic activity of various nano-enzyme materials and exploring other descriptors will be conducive to the efficient and rational design of nano-enzymes. For example, in compounds with superoxide dismutase activity, researchers have found that there is a clear volcanic curve relationship between the reduction potential E_1/2 of the compound and its catalytic activity^[58]. Therefore, in the follow-up study, we can try to study the reduction potential E₁_/₂, d-band charge density and hydroxyl adsorption energy of the material, and use them as descriptors to quickly design efficient nanoenzymes.

(4) Bionic design. In the above strategies, it can be seen that most of the existing regulation is based on the excellent performance of nanomaterials, while ignoring the attention to their intrinsic enzymatic characteristics. Nano-enzyme is not only a nanomaterial, but also has a new effect of nanomaterials-enzyme catalytic activity at the nanometer scale. Therefore, the efficient design of nano-enzymes can be inspired and guided by efficient and specific natural enzymes. Although some achievements have been made in the study of structure-activity relationship of MOF nanoenzyme, there are still few studies in this area, which need further development. For example, the existing regulation is inspired by the protein regulation engineering of natural metalloprotease, which regulates some weak ligands around the metal site. However, in the regulation of natural enzymes, the regulation of secondary structures also has a greater impact on the performance, so how to use these ordered three-dimensional porous structures (such as MOF, COF, etc.) To design nanoenzymes that can systematically study the impact of secondary structures,To reveal the intrinsic structure-activity relationship and improve the theoretical system of nanocatalysis will further promote the efficient design of nanocatalysis. In addition, combined with the Nobel Prize in Chemistry in 2018, how to apply the directed evolution of enzymes to nano-enzymes and achieve efficient design and development in the field of nano-enzymes should also be paid enough attention to, so as to better develop high-performance nano-enzymes, replace natural enzymes, and realize the unique and irreplaceable applications of nano-enzymes.

In a word, as a new generation of mimetic enzyme, the research of nano-enzyme is in the ascendant, and the efficient design of nano-enzyme will play an important role in promoting the development of nano-enzyme, and related research will be developed rapidly.

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