Zhiling Zhu

Single‐node interventions often fail against tumor metabolic networks due to dynamic compensation and pathway redundancy, necessitating synergistic, multi‐node strategies. However, translating high‐dimensional single‐cell omics into physicochemical parameters for materials design remains a major challenge. Herein, a cross‐scale inverse design paradigm for therapeutic nanozymes is proposed that maps single‐cell metabolic demands onto quantum‐chemical descriptors. Using hepatocellular carcinoma (HCC) as a model, integrated single‐cell transcriptomic and metabolic flux analyses revealed a triple vulnerability network involving lactate accumulation, focal hypoxia, and oxidative stress imbalance. Guided by first‐principles calculations and multiparameter screening based on reaction energy barriers and Bader charge transfer, 260 candidate materials were evaluated. This screening identified a nitrogen–phosphorus dual‐coordinated gold single‐atom nanozyme (APNC) with exceptional lactate oxidase (LOX)‐, catalase (CAT)‐, and peroxidase (POD)‐like activities and strong piezoelectric polarization. In vitro and in vivo studies demonstrated that APNC remodels the HCC microenvironment by depleting lactate and alleviating hypoxia, thereby disrupting glycolysis and triggering immunogenic cell death (ICD). APNC‐mediated piezocatalytic therapy achieved 95% tumor inhibition in vivo. This inverse design strategy bridges single‐cell metabolic profiling and atomic‐scale material engineering, establishing a versatile framework for precision nanozyme development across tumors and metabolic disorders.

Peptide bond hydrolysis is essential to biology, yet the kinetic stability of amide bonds makes efficient and selective artificial proteolysis challenging. Here, we report a biomimetic Cu single‐atom nanozyme, Cu‐NC HSA, that integrates mixed d ⁹ ‐d ¹⁰ Cu‐N ₄ active sites with a hydrogen‐substituted graphdiyne overlayer for selective protein hydrolysis. Mechanistic studies indicate that the Cu centers provide balanced Lewis acidity for carbonyl polarization and water activation, while the hydrophobic H‐GDY microenvironment preferentially enriches substrates bearing nonpolar residues. Under mild conditions (25°C, pH 6.0–10.0), Cu‐NC HSA hydrolyzes bovine serum albumin with a marked preference for peptide bonds adjacent to hydrophobic residues (86%). Beyond catalysis, Cu‐NC HSA shows potent antibiofilm activity, achieving biofilm removal in vitro and enabling sustained marine antifouling performance in a real marine environment. This work offers a multiscale biomimetic strategy for selective protein hydrolysis and marine antifouling applications.

Most laccase‐mimetic nanozymes fail to replicate the synergistic, division‐of‐labor catalysis of natural multicopper laccases, limiting activity gains. A key bottleneck lies in the construction of atomically defined and spatially organized active sites that integrate oriented structural motifs with multistate electronic configurations. Here, we report a graphdiyne‐derived Cu single‐atom/nanocluster nanozyme (CCG) in which the sp‐carbon scaffold hierarchically organizes Cu single atoms (SAs) and nanoclusters (NCs) to mimic the asymmetric microenvironment and electronic structure of native laccase active sites. Cu SAs serve as electron transfer centers, while Cu NCs reproduce the oxygen‐accepting characteristics of multinuclear Cu sites. Electronic structure analyses reveal that the sp‐carbon precisely modulates Cu coordination geometries and spin states, generating tri‐site electronic features analogous to the T1/T2/T3 ensemble in natural laccases. Steady‐state kinetics reveal that CCG exhibits 5.21‐fold higher specific activity than ZmLac3 with enhanced substrate affinity. In salt‐stressed maize seedlings, CCG functionally compensated for endogenous ZmLac3 and regulated lignin biosynthesis, increasing root lignin content and cell wall thickness by 27.6% and 47.7%, and improving root activity and biomass by 61.2% under 300 mM NaCl. This study establishes an atomic‐precision design paradigm that integrates hierarchical site construction with multistate electronic coordination, guiding the development of next‐generation high‐performance biomimetic nanozymes.

Eco-nanozymology, as an emerging interdisciplinary field, integrates nanotechnology with principles of enzymology to offer innovative strategies for energy conversion and environmental remediation. In contrast with conventional enzymology, eco-nanozymology enhances catalytic efficiency through the precise regulation of interfacial microstructures, electronic distributions, active site configurations, multienzyme cascade catalysis, and functionalized carrier engineering. By harnessing and amplifying natural ecological processes, eco-nanozymology enables effective modulation of energy flow and material cycling within ecosystems. This review focuses on recent advances in the application of eco-nanozymology across energy-related domains, including nitrogen fixation, carbon fixation, methane oxidation, hydrogen production, and energy conversion devices. It further provides an in-depth analysis of the recent progress in the efficient degradation of environmental pollutants and resource-oriented valorization of low-value biomass, such as lignin, agricultural residues, livestock manure, and microplastics. These studies highlight the pivotal role of eco-nanozymology in enhancing the efficiency of environmental management, accelerating the development of green energy technologies, and advancing carbon neutrality goals. The continued development of eco-nanozymology is expected to open new horizons for the deepening and expansion of nanozyme applications, offering green, environmentally friendly, and sustainable technological pathways to address global energy and environmental challenges.

A single-atom nanozyme with a Lewis acid–base microenvironment was designed via boron-modulated electronic polarization of g-C ₆ N ₆ .

The growing prevalence of infectious diseases and the increasing threat of bacterial resistance have drawn widespread attention to antimicrobial inorganic nanomaterials. However, the diversity, abundance, and complex mechanisms of these materials present significant challenges in identifying new agents that are both efficient and cost-effective with broad-spectrum activity. In response, this study applied machine learning for the first time to discover antimicrobial inorganic nanomaterials. Information on over 2,000 antimicrobial nanomaterials was extracted from more than 8,000 papers. An unsupervised machine learning analysis was conducted to assess data distribution and explore the relationships between material features and antimicrobial activity in high-dimensional space. A series of machine learning models were trained. Through the evaluation of six performance metrics, five key features were identified from 27 dimensions. To further quantify the structure-activity relationships, a genetic programming-symbolic classification model was employed to generate a precise mathematical formula with a prediction accuracy of 0.83. Using this formula, 43 new antimicrobial inorganic nanomaterials were predicted. Of these, four nanomaterials were synthesized and their antibacterial properties were experimentally validated. This work not only provides a next generation approach for designing antimicrobial inorganic nanomaterials but also opens new avenues for applying machine learning in materials science.

This review presents a comprehensive overview of bioinspired rational design of nanozymes, guided by the catalytic mechanisms and structural characteristics of natural enzymes, and enhanced by emerging trend of machine learning assisted strategies.