Data-Driven Evolutionary Design of Multienzyme-like Nanozymes

Design and performance analysis of multi-enzyme activity-doped nanozymes assisted by machine learning

Traditional design approaches for nanozymes typically rely on empirical methods and trial-and-error, which hampers systematic optimization of their structure and performance, thus limiting the efficiency of developing innovative nanozymes. This study leverages machine learning techniques supported by high-throughput computations to effectively design nanozymes with multi-enzyme activities and to elucidate their reaction mechanisms. Additionally, it investigates the impact of dopants on the microphysical properties of nanozymes. We constructed a machine learning prediction framework tailored for dopant nanozymes exhibiting catalytic activities like to oxidase (OXD) and peroxidase (POD). This framework was used to evaluate key catalytic performance parameters, such as formation energy, density of states (DOS), and adsorption energy, through density functional theory (DFT) calculations. Various machine learning models were employed to predict the effects of different doping element ratios on the catalytic activity and stability of nanozymes. The results indicate that the combination of machine learning with high-throughput computations significantly accelerates the design and optimization of dopant nanozymes, providing an efficient strategy to address the complexities of nanozyme design. This approach not only boosts the efficiency and capability for innovation in material design but also provides a novel theoretical analytical avenue for the development of new functional materials.

Hyaluronan-modified nanoceria for dry eye disease treatment

Dry eye disease (DED), a prevalent ocular disorder, affects nearly half the global population, bringing enormous health and economic burden. Currently, the predominant treatments for DED involve the administration of artificial tears, which is often hindered by continuous administration and constant reactive oxygen species (ROS) stimulus. Therefore, hyaluronan (HA)-modified cerium oxide (CeO2) nanoparticles, HA-CeO2, were developed to achieve simultaneous ROS scavenging and enhanced tear film stability. HA-CeO2 was demonstrated to effectively scavenge ROS while concurrently downregulating the expression of inflammatory factors, such as MMP9 and IL-1β. Moreover, the anti-oxidative and anti-inflammatory effects of HA-CeO2 were further confirmed through a DED mouse model. In addition, the biocompatibility and safety of HA-CeO2 make it a promising treatment option for DED associated with inflammation and oxidative stress, offering novel insights into utilizing nanozymes in treating inflammation-oxidative stress-related diseases.

Copper-based biomimetic nanozymes with multi-enzyme activity for phosphate detection

Nanozymes are nanoparticles with enzymatic activity, which are widely used in environmental and antibacterial research. Herein, we designed and synthesized novel amorphous nanozyme Cu-Im NPs with multiple enzyme-mimicking activities. Cu-Im NPs have the same active sites as natural laccase. In addition, the active center is similar to that of carbonic hydrolase, replacing the zinc ions with copper ions. Meanwhile, Cu-Im NPs also possess peroxidase-like activity. We reveal the multi-enzyme catalytic mechanisms of Cu-Im NPs. Notably, phosphate inhibits the laccase-like and peroxidase-like activities of Cu-Im NPs while activating their hydrolase activity. Based on these findings, we have developed a sensitive and selective method for detecting phosphate anions.

t2 Occupancy as an Effective and Predictive Descriptor for the Design of High-Performance Spinel Oxide Peroxidase-like Nanozymes

Nanozymes are next generation of enzyme mimics. Due to the lack of activity descriptors, most nanozymes were discovered through trial-and-error strategies or by accident. While eg occupancy in an octahedral crystal field was proven as an effective descriptor, the t2 in a tetrahedral crystal field has rarely been explored. Here, we first identified t2 occupancy as an effective and predictive descriptor. Then, we predicted and demonstrated that spinel oxide nanozymes (AB2O4) with a t2 occupancy of around 4.4 at A site had the highest activity. Furthermore, we introduced Oβ content as a secondary descriptor. The dual descriptor strategy resulted in a three-dimensional volcanic curve, converging at a vertex. To surpass the limitations of volcanic curves, a dual site optimizing strategy was proposed, guiding the optimization of both A and B sites as Cu and Co, respectively. The designed CuCo2O4 exhibited the highest activity, achieving around 100- and 2-fold enhancement compared to initial material and the state-of-the-art spinel oxide nanozyme LiCo2O4, respectively. Density functional theory calculations provided a theoretical basis for the catalytic process. This work provides a new strategy for the rational design of nanozymes, and t2 occupancy may also be applicable to the design of other catalysts.

Improving Nanozyme-Based Colorimetric Assays through Medium Composition Optimization in Nanozyme-Substrate Reaction

Nanozymes, while promising alternatives to natural peroxidases in colorimetric assays, are often hindered by lower catalytic efficiencies. Although numerous approaches have been developed to improve signal intensity in nanozyme-based assays, optimization of the reaction medium in which the nanozyme interacts with the substrate remains a significantly underexplored area. The vast majority of studies rely on standard sodium acetate buffers or commercially sourced reagents optimized for horseradish peroxidase, neglecting the unique catalytic properties of different nanozymes. This work presents a systematic optimization of 3,3',5,5'-tetramethylbenzidine (TMB)-based reaction medium composition for four common nanozymes: iron oxide, LaNiO3, Mn-doped CeO2, and platinum nanoparticles. Our findings reveal that while sodium acetate buffer is suitable for LaNiO3, alternative buffers significantly enhance signal intensity (41-68%) for the other nanozymes. Further optimization of ionic strength, organic cosolvent type and concentration, and TMB/H2O2 concentrations yielded improvements in signal intensity, analytical sensitivity, and assay time. This study also identifies common pitfalls encountered during optimization of reaction conditions and proposes potential solutions. We posit that reaction medium should be a standard optimization step in the development of nanozyme-based assays, and the use of commercially sourced reagents with undisclosed compositions should be avoided.

Construction of a CuO2@PDA Nanozyme with Switchable Dual Enzyme-Mimic Activities for Colorimetric Sensing of Catechol and Hydroquinone

The development of metal-based redox nanozymes represents a new frontier in pollutant sensing. In this field, designing highly active nanozymes and precisely regulating their enzymatic activity are key challenges. In this work, we report the construction of a copper peroxide@polydopamine (CuO2@PDA) nanozyme with dual enzyme-like activity, mimicking the active centers of laccase and peroxidase. Here, CuO2 acts as the catalytic center, while PDA serves as a carrier to prevent CuO2 aggregation and promotes conversion of CuII/CuI active sites via the reduction effect of its surface catechol groups to complete the catalytic cycle. As expected, the obtained CuO2@PDA nanozyme exhibits significant laccase- and peroxidase-mimetic activities. Moreover, its dual enzymatic activity can be systematically switched by adjusting pH and temperature. Specifically, laccase activity dominates near neutral pH, while CuO2 decomposition into Cu ions and H2O2 at acidic pH triggers peroxidase activity. Similarly, CuO2@PDA exhibits temperature-dependent dual enzymatic activity with peroxidase activity prevailing at low temperatures and laccase activity at high temperatures. According to enzymatic performance and XPS results, a possible catalytic mechanism of the dual enzymatic activity of CuO2@PDA has been proposed. Then, based on the pH-dependent dual enzymatic activity of CuO2@PDA, we constructed a detection system for the isomers of organic pollutants, catechol (CC) and hydroquinone (HQ). The laccase-like activity of CuO2@PDA enables direct oxidation of CC into yellow o-benzoquinone, while HQ discolors the preoxidized substrate generated via the peroxidase-like activity of CuO2@PDA. Moreover, selective sensing for CC and HQ with high sensitivity was achieved in real water samples. This approach can guide the design of nanozymes with multienzymatic activity and unveil their potential uses in environmental pollutant discrimination.

Kirkendall Effect-Mediated Transformation of ZIF-67 to NiCo-LDH Nanocages as Oxidase Mimics for Multicolor Point-of-Care Testing of β-Galactosidase Activity and Escherichia coli

Early and portable detection of pathogenic bacteria is crucial for ensuring food safety, monitoring product quality, and tracing the sources of bacterial infections. Moving beyond traditional plate-culture counting methods, the analysis of active bacterial components offers a rapid means of quantifying bacteria. Here, metal-organic framework (MOF)-derived NiCo-layered double hydroxide nanosheets (LDHs), synthesized via the Kirkendall effect, were employed as highly effective oxidase mimics to generate reactive oxygen species (ROS). These ROS quickly etched gold nanobipyramids (Au NBPs), producing a vivid multicolormetric response. Experimental results and theoretical calculations indicated that the exceptional oxidase-like activity of NiCo-LDHs stemmed from the presence of bimetallic active sites and oxygen vacancies modulating the local electronic structure of LDHs. Additionally, β-galactosidase (β-Gal), a biomarker of Escherichia coli, reacted with p-aminophenyl-β-d-galactopyranoside (PAPG) to form p-aminophenol (PAP), a reducing agent which consumes ROS, thereby inhibiting the etching of Au NBPs. Furthermore, a three-dimensional (3D)-printed point-of-care testing (POCT) shell was designed as a portable device to visually detect β-Gal and E. coli in conjugation with smartphones. This study not only provides a novel approach to the rational design of nanozymes but also establishes a vivid and portably visual biosensing platform for detecting β-Gal activity and pathogenic bacteria.

MnGA with multiple enzyme-like properties for acute wound healing by reducing oxidative stress and modulating signaling pathways

Nanozymes with specific catalytic activity inhibit inflammation and promote wound healing efficiently and safely. In this work, multifunctional manganese-based nanozymes (MnGA) with antioxidant properties were successfully constructed via a simple coordination reaction in which manganese chloride was used as the manganese source and gallic acid (GA) was used as the ligand solution. MnGA possesses both catalase-like (CAT-like) and superoxide dismutase-like (SOD-like) activities and a reactive nitrogen species (RNS) scavenging capacity, which enables it to efficiently inhibit the inflammatory response. Specifically, MnGA scavenges superoxide anions and produces H2O2 via SOD-like activity and then consumes H2O2 to convert it to nontoxic H2O and O2 via CAT-like activity, resulting in a cascade of catalytic reactions to scavenge reactive oxygen species (ROS). Moreover, the scavenging of RNS by MnGA can amplify the anti-inflammatory effect in combination with the scavenging of ROS. RNA sequencing of mouse skin tissue further revealed that MnGA significantly reduces inflammation by modulating the nuclear factor kappa-B (NF-κB), Toll-like receptor (TLR), and NOD-like receptor (NLR) signaling pathways and promotes skin regeneration. In summary, MnGA nanocatalysts possess excellent antioxidative and anti-inflammatory properties, highlighting their potential applications in wound healing and inflammation treatment.

D-Band-Center-Engineered Platinum-Based Nanozyme for Personalized Pharmacovigilance

A high-efficiency PtZnCd nanozyme was screened with density functional theory (DFT) and unique d-orbital coupling features for sensitive enrichment and real-time analysis of CO-releasing molecule-3 (CORM-3). Multicatalytic sites in the nanozyme showed a high reactivity of up to 72.89 min-1 for peroxidase (POD)-like reaction, which was 2.2, 4.07, and 14.67 times higher than that of PtZn (32.67 min-1), PtCd (17.89 min-1), and Pt (4.97 min-1), respectively. Normalization of the catalytic sites showed that the catalytic capacity of the active site in PtZnCd was 2.962 U μmol-1, which was four times higher than that of a pure Pt site (0.733 U μmol-1). DFT calculations showed that improved d-orbital coupling between different metals reduces the position of the center of the shifted whole d-band relative to the Fermi energy level, thereby increasing the contribution of the sites to the electron transfer from the active center, accompanied by enhanced substrate adsorption and intermediate conversion in the catalytic process. The potential adsorption principle and color development mechanism of CORM-3 on PtZnCd were determined, and its practical application in drug metabolism was validated in vitro and in zebrafish and mice models, demonstrating that transition-metal doping effectively engineers high-performance nanozymes and optimizes artificial enzymes.

Redox interference-free bimodal paraoxon sensing enabled by an aggregation-induced emission nanozyme catalytically hydrolyzing phosphoesters specifically

In view of the current serious situation of organophosphorus pesticides (OPs) residue contamination, developing rapid and accurate OPs sensors is a matter of urgency. Redox-nanozyme based colorimetric sensors have been widely researched and utilized in OPs residue determination, but overcoming the interference of external redox substances and the effect of single-signal modes on detection performance is still a challenge. Here we fabricated a Zr-based metal-organic framework (MOF) featuring specific phosphatase-like activity and strong aggregation-induced emission (AIE) fluorescence for redox interference-free bimodal pesticide sensing. In the MOF, the activity-tunable Zr4+ node offered high hydrolytic activity and affinity toward P-O containing substrates, and the rigid framework structure effectively enhanced the fluorescence emission of the ligand 1,1,2,2-tetra(4-carboxylphenyl)ethylene. The developed AIEzyme could efficiently catalyze the hydrolysis of paraoxon to yellow p-nitrophenol, which further reduced the intrinsic AIE fluorescence of AIEzyme through internal filtration effect. Thereby, a natural enzyme-free dual-mode colorimetric/fluorescence approach was established for paraoxon detection with no interference from redox substances, and a smartphone-assisted portable platform was further developed to enable the facile, rapid, and high-performance sensing of the pesticide in complex practical matrices.

Unveiling Generally-ignored Co-substrate Effect of Catalase-inherent Peroxidase Mimic for Self-verifiable Detection of High-concentration Hydrogen Peroxide

One nanoparticle possessing both peroxidase (POD) and catalase (CAT) activities is a prevalent co-substrate nanozyme system, distinct from the extensively researched cascade nanozyme system. During the sensing of hydrogen peroxide by POD, the impact of CAT is actually ignored in most studies. In this study, the CAT effect on hydrogen peroxide detection is thoroughly investigated based on POD catalysis by finely tuning the relative activity of POD and CAT. It is discovered that the CAT effect can be changed by delaying the injection of chromogenic substrate after adding hydrogen peroxide and that the linear range grows with the delayed time. Then, a theoretical mechanism showed that the time-delay mediated CAT effect magnification does not change the Vmax, but it causes Km to linearly increase with delayed time, consistent with the experiment results. Furthermore, the detection of high concentrations of hydrogen peroxide is successfully realized in contact lens care solutions by utilizing time-delay-mediated POD/CAT nanozyme. On the other hand, its linear range-tunable characteristic is used to produce multiple standard curves, then enabled self-verifying hydrogen peroxide detection. Overall, this work investigates the role of CAT in CAT-inherent POD nanozymes both theoretically and experimentally, and confirms POD/CAT nanozyme's priority in developing high-performance sensors.

Peptide nanozymes: An emerging direction for functional enzyme mimics

The abundance of molecules on early Earth likely enabled a wide range of prebiotic chemistry, with peptides playing a key role in the development of early life forms and the evolution of metabolic pathways. Among peptides, those with enzyme-like activities occupy a unique position between peptides and enzymes, combining both structural flexibility and catalytic functionality. However, their full potential remains largely untapped. Further exploration of these enzyme-like peptides at the nanoscale could provide valuable insights into modern nanotechnology, biomedicine, and even the origins of life. Hence, this review introduces the groundbreaking concept of "peptide nanozymes (PepNzymes)", which includes single peptides exhibiting enzyme-like activities, peptide-based nanostructures with enzyme-like activities, and peptide-based nanozymes, thus enabling the investigation of biological phenomena at nanoscale dimensions. Through the rational design of enzyme-like peptides or their assembly with nanostructures and nanozymes, researchers have found or created PepNzymes capable of catalyzing a wide range of reactions. By scrutinizing the interactions between the structures and enzyme-like activities of PepNzymes, we have gained valuable insights into the underlying mechanisms governing enzyme-like activities. Generally, PepNzymes play a crucial role in biological processes by facilitating small-scale enzyme-like reactions, speeding up molecular oxidation-reduction, cleavage, and synthesis reactions, leveraging the functional properties of peptides, and creating a stable microenvironment, among other functions. These discoveries make PepNzymes useful for diagnostics, cellular imaging, antimicrobial therapy, tissue engineering, anti-tumor treatments, and more while pointing out opportunities. Overall, this research provides a significant journey of PepNzymes' potential in various biomedical applications, pushing them towards new advancements.

Mucin-Triggered Osmium Nanoclusters as Protein-Corona-Like Nanozymes with Photothermal-Enhanced Peroxidase-Like Activity for Tumor-Specific Therapy

Nanomaterials with peroxidase-like activity and photothermal conversion efficiency have garnered significant attention for their ability to generate cytotoxic hydroxyl radicals and provide synergistic therapeutic effects. Selecting nanozymes with suitable properties and carriers is crucial for maximizing efficacy. While the mucin family is known for its mucoadhesive, glycosylated structures that enhance drug bioavailability and targeting, its potential in nanozymes remains underexplored. Here, we utilize mucin-2 to facilitate osmium nanoclusters (Os@Mucin), creating protein-corona-like nanozymes. This configuration bestows Os@Mucin with excellent peroxidase-like activity (769 U/mg) and photothermal conversion efficiency (22.83%, 808 nm). Mucin-2 promotes Os uptake by cells, allowing Os@Mucin to exhibit tumor environment-responsive peroxidase-like activity, further enhanced under photothermal conditions for targeted cytotoxicity and synergistic effects. In vivo experiments demonstrate that this integration effectively treats triple-negative breast cancer. This study innovatively highlights the potential of the mucin family and underscores the promising role of Os nanozymes in tumor therapy.

Papain functionalized Prussian blue nanozyme colloids of triple enzymatic function

Prussian blue nanozymes were surface engineered with papain enzyme to develop processable nanoparticle dispersions with antioxidant and hydrolytic activities for biocatalytic applications. Enzyme coating improved the colloidal stability of the nanozymes and the obtained papain-Prussian blue hybrid showed remarkable peroxidase (vmax = 8.82 × 10-9 M s-1, KM = 12.3 mM), superoxide dismutase (IC50 = 14.6 ppm) and protease-like (41.2 U L-1) activities.

Structural Regulation of Au-Pt Bimetallic Aerogels for Catalyzing the Glucose Cascade Reaction

Bimetallic nanostructures are promising candidates for the development of enzyme-mimics, yet the deciphering of the structural impact on their catalytic properties poses significant challenges. By leveraging the structural versatility of nanocrystal aerogels, this study reports a precise control of Au-Pt bimetallic structures in three representative structural configurations, including segregated, alloy, and core-shell structures. Benefiting from a synergistic effect, these bimetallic aerogels demonstrate improved peroxidase- and glucose oxidase-like catalytic performances compared to their monometallic counterparts, unleashing tremendous potential in catalyzing the glucose cascade reaction. Notably, the segregated Au-Pt aerogel shows optimal catalytic activity, which is 2.80 and 3.35 times higher than that of the alloy and core-shell variants, respectively. This enhanced activity is attributed to the high-density Au-Pt interface boundaries within the segregated structure, which foster greater substrate affinity and superior catalytic efficiency. This work not only sheds light on the structure-property relationship of bimetallic catalysts but also broadens the application scope of aerogels in biosensing and biological detections.

Exploring Nanozymes for Organic Substrates: Building Nano-organelles

Since the discovery of the first peroxidase nanozyme (Fe3O4), numerous nanomaterials have been reported to exhibit intrinsic enzyme-like activity toward inorganic oxygen species, such as H2O2, oxygen, and O2 -. However, the exploration of nanozymes targeting organic compounds holds transformative potential in the realm of industrial synthesis. This review provides a comprehensive overview of the diverse types of nanozymes that catalyze reactions involving organic substrates and discusses their catalytic mechanisms, structure-activity relationships, and methodological paradigms for discovering new nanozymes. Additionally, we propose a forward-looking perspective on designing nanozyme formulations to mimic subcellular organelles, such as chloroplasts, termed "nano-organelles". Finally, we analyze the challenges encountered in nanozyme synthesis, characterization, nano-organelle construction and applications while suggesting directions to overcome these obstacles and enhance nanozyme research in the future. Through this review, our goal is to inspire further research efforts and catalyze advancements in the field of nanozymes, fostering new insights and opportunities in chemical synthesis.

Computer-aided nanodrug discovery: recent progress and future prospects

Nanodrugs, which utilise nanomaterials in disease prevention and therapy, have attracted considerable interest since their initial conceptualisation in the 1990s. Substantial efforts have been made to develop nanodrugs for overcoming the limitations of conventional drugs, such as low targeting efficacy, high dosage and toxicity, and potential drug resistance. Despite the significant progress that has been made in nanodrug discovery, the precise design or screening of nanomaterials with desired biomedical functions prior to experimentation remains a significant challenge. This is particularly the case with regard to personalised precision nanodrugs, which require the simultaneous optimisation of the structures, compositions, and surface functionalities of nanodrugs. The development of powerful computer clusters and algorithms has made it possible to overcome this challenge through in silico methods, which provide a comprehensive understanding of the medical functions of nanodrugs in relation to their physicochemical properties. In addition, machine learning techniques have been widely employed in nanodrug research, significantly accelerating the understanding of bio-nano interactions and the development of nanodrugs. This review will present a summary of the computational advances in nanodrug discovery, focusing on the understanding of how the key interfacial interactions, namely, surface adsorption, supramolecular recognition, surface catalysis, and chemical conversion, affect the therapeutic efficacy of nanodrugs. Furthermore, this review will discuss the challenges and opportunities in computer-aided nanodrug discovery, with particular emphasis on the integrated "computation + machine learning + experimentation" strategy that can potentially accelerate the discovery of precision nanodrugs.

Nanozyme-Based Microfluidic Chip System for pH-Regulated Pretreatment and Sensitive Sensing

Nanozymes, possessing nanomaterial properties and catalytic activities, offer great opportunities to design sensitive analytical detection systems. However, the low interference resistance of nanozymes poses a significant limitation on the precise detection of target substances. Herein, a nanozyme-based microfluidic chip system for pH-regulated pretreatment and sensitive sensing of cysteine (Cys) is reported. The copper metal-organic framework (Cu MOF) exhibits good cysteine oxidase-like activity at pH 7.0, while demonstrating excellent laccase-like activity at pH 8.0. Taking advantage of the pH-regulated enzyme-like activity, the integrated microfluidic device involving the immobilization of Cu MOF eliminates the interference of dopamine (DA) and accurately detects the target Cys. Compared with the untreated reaction system, the developed nanozyme system shows a significantly improved accuracy in detecting Cys, with an R2 value of 0.9914. This work provides an efficient method to enhance the interference resistance of nanozymes and broadens the application in sample pretreatment.

Engineering inorganic nanozyme architectures for decomposition of reactive oxygen species

Enzyme-mimicking nanomaterials (nanozymes) with antioxidant activity are at the forefront of research efforts towards biomedical and industrial applications. The selection of enzymatically active substances and their incorporation into novel inorganic nanozyme structures is critically important for this field of research. To this end, the fabrication of composites can be desirable as these can either exhibit multiple enzyme-like activities in a single material or show increased activity compared to the nanozyme components. Conversely, by modifying the structure of a nanomaterial, enzyme-like activities can be induced in formerly inert particles. We identify herein the three main routes of composite nanozyme synthesis, namely, surface functionalization of a particle with another compound, heteroaggregation of individual nanozymes, and modification of the bulk nanozyme structure to achieve optimal antioxidant activity. We discuss in particular the different inorganic support materials used in the synthesis of nanozyme architectures and the advantages brought forth by the use of composites.

Nanozyme-Enabled Biomedical Diagnosis: Advances, Trends, and Challenges

As nanoscale materials with the function of catalyzing substrates through enzymatic kinetics, nanozymes are regarded as potential alternatives to natural enzymes. Compared to protein-based enzymes, nanozymes exhibit attractive characteristics of low preparation cost, robust activity, flexible performance adjustment, and versatile functionalization. These advantages endow them with wide use from biochemical sensing and environmental remediation to medical theranostics. Especially in biomedical diagnosis, the feature of catalytic signal amplification provided by nanozymes makes them function as emerging labels for the detection of biomarkers and diseases, with rapid developments observed in recent years. To provide a comprehensive overview of recent progress made in this dynamic field, here an overview of biomedical diagnosis enabled by nanozymes is provided. This review first summarizes the synthesis of nanozyme materials and then discusses the main strategies applied to enhance their catalytic activity and specificity. Subsequently, representative utilization of nanozymes combined with biological elements in disease diagnosis is reviewed, including the detection of biomarkers related to metabolic, cardiovascular, nervous, and digestive diseases as well as cancers. Finally, some development trends in nanozyme-enabled biomedical diagnosis are highlighted, and corresponding challenges are also pointed out, aiming to inspire future efforts to further advance this promising field.

Progress in the Computer-Aided Analysis in Multiple Aspects of Nanocatalysis Research

Making the utmost of the differences and advantages of multiple disciplines, interdisciplinary integration breaks the science boundaries and accelerates the progress in mutual quests. As an organic connection of material science, enzymology, and biomedicine, nanozyme-related research is further supported by computer technology, which injects in new vitality, and contributes to in-depth understanding, unprecedented insights, and broadened application possibilities. Utilizing computer-aided first-principles method, high-speed and high-throughput mathematic, physic, and chemic models are introduced to perform atomic-level kinetic analysis for nanocatalytic reaction process, and theoretically illustrate the underlying nanozymetic mechanism and structure-function relationship. On this basis, nanozymes with desirable properties can be designed and demand-oriented synthesized without repeated trial-and-error experiments. Besides that, computational analysis and device also play an indispensable role in nanozyme-based detecting methods to realize automatic readouts with improved accuracy and reproducibility. Here, this work focuses on the crossing of nanocatalysis research and computational technology, to inspire the research in computer-aided analysis in nanozyme field to a greater extent.

Machine learning in nanozymes: from design to application

Nanozymes, a distinctive class of nanomaterials endowed with enzyme-like activity and kinetics akin to enzyme-catalysed reactions, present several advantages over natural enzymes, including cost-effectiveness, heightened stability, and adjustable activity. However, the conventional trial-and-error methodology for developing novel nanozymes encounters growing challenges as research progresses. The advent of artificial intelligence (AI), particularly machine learning (ML), has ushered in innovative design approaches for researchers in this domain. This review delves into the burgeoning role of ML in nanozyme research, elucidating the advancements achieved through ML applications. The review explores successful instances of ML in nanozyme design and implementation, providing a comprehensive overview of the evolving landscape. A roadmap for ML-assisted nanozyme research is outlined, offering a universal guideline for research in this field. In the end, the review concludes with an analysis of challenges encountered and anticipates future directions for ML in nanozyme research. The synthesis of knowledge in this review aims to foster a cross-disciplinary study, propelling the revolutionary field forward.