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Article

Enhancement of the Peroxidase Activity of Metal–Organic Framework with Different Clay Minerals for Detecting Aspartic Acid

by
Chen Tian
1,2,*,
Lang Zhang
1,2,
Yali Yu
1,2,
Ting Liu
1,2,
Jianwu Chen
1,2,
Jie Peng
1,2,
Chu Dai
3 and
Jinhua Gan
1,2,*
1
Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan 430223, China
2
Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, China
3
School of Physics and Electromechanical Engineering, Hubei University of Education, Wuhan 430205, China
*
Authors to whom correspondence should be addressed.
Catalysts 2025, 15(12), 1172; https://doi.org/10.3390/catal15121172
Submission received: 10 November 2025 / Revised: 4 December 2025 / Accepted: 15 December 2025 / Published: 17 December 2025
(This article belongs to the Special Issue Advances in MOF/COF Catalysis: Tailored Structures for Enhanced Performance)
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Abstract

The strategic engineering of metal–organic frameworks (MOFs) through integration with clay minerals offers a promising route to tailor their functional properties and expand their application scope. In this study, a series of clay-MOF composites was constructed by introducing MOFs onto the surfaces of different clay minerals. By varying the type of clay mineral, the nature and strength of surface-active sites could be effectively modulated. Notably, the Kaolinite-based MOFs (Ka-MOF) composite exhibited superior sensitivity for the detection of aspartic acid (AA), outperforming other composite nanozymes using o-phenylenediamine (OPD) and hydrogen peroxide (H2O2) as substrates, with a linear detection range of 0–37.56 μM and a low detection limit of 55.7 nM. The enhanced peroxidase-like activity is attributed to the substitution of silicon in the kaolinite structure by MOF components, which increases the density of Lewis acid–base sites. These sites facilitate H2O2 adsorption and promote its decomposition to generate singlet oxygen (1O2), thereby enhancing the catalytic oxidation process. Furthermore, the probe yielded satisfactory recoveries of aspartic acid (94.2% to 98.5%) in different real water samples through spiking recovery experiments. This work not only elucidates the influence of crystal surface engineering on the optical and catalytic properties of nanozymes but also provides a robust platform for tracing amino acids and studying their environmental chemical behaviors.

1. Introduction

Amino acids, as the fundamental building blocks of life, play an indispensable role in maintaining normal physiological functions and metabolic processes [1,2]. Among them, aspartic acid (AA), a common amino acid, serves not only as a precursor for the synthesis of various biomolecules but also functions as a major excitatory neurotransmitter in the central nervous system, regulating neuronal signaling [3,4]. In clinical practice, AA and its derivatives have been utilized in the adjuvant treatment of various conditions, including cardiac diseases and hepatic dysfunction [5]. However, the homeostasis of amino acids is crucial, and their abnormal levels are often closely associated with overall health status. For instance, excessive intake of aspartic acid may induce neurotoxicity and has been linked to an increased risk of neurological disorders such as stroke and epilepsy [6]. Consequently, establishing sensitive and rapid detection methods for aspartic acid is of great significance for disease diagnosis, food safety, and environmental risk assessment.
Currently, the detection of aspartic acid primarily relies on analytical techniques such as gas chromatography, inductively coupled plasma atomic emission spectroscopy, and electrochemical methods [7,8,9]. However, the widespread practical application of these techniques is often hampered by limitations, including high instrument costs, complex sample pretreatment procedures, and difficulties in achieving on-site rapid detection. In contrast, colorimetric sensing exhibits considerable potential due to its advantages of operational simplicity, low cost, visual signal response, and capacity for real-time monitoring [10,11]. In recent years, nanozymes, as nanomaterials with enzyme-like catalytic activities, have garnered extensive attention in the fields of environmental analysis and biochemical sensing [12,13]. Their tunable catalytic activity provides diversity for constructing detection principles, while their efficient catalytic signal amplification capability lays the foundation for highly sensitive quantitative analysis. Although notable progress has been made in nanozyme-based sensors for amino acid detection, typically achieved indirectly by modulating the oxidation process of H2O2, several challenges remain in their practical application. These include the susceptibility of exposed active sites leading to insufficient nanozyme stability, and the lack of specific binding sites for target substrates, which limits their selectivity and reliability.
MOFs have demonstrated unique advantages in the design and application of nanozymes due to their high specific surface area, tunable pore structures, and enzyme-like hydrophobic microenvironments [14,15]. As a typical MOF, MIL-101(Fe) has been confirmed to possess excellent peroxidase-mimicking activity and has exhibited superior catalytic performance compared to natural horseradish peroxidase in the detection of small molecules such as glucose, antibiotics, and uric acid [16,17]. Nevertheless, inherent drawbacks of MOF materials, including limited pore size, susceptibility of active sites to being embedded, and poor cycling stability, constrain their performance in practical detection. To address these limitations, researchers have attempted to incorporate materials such as Fe3O4, g-C3N4, and carbon nanotubes to enhance their properties [18,19,20]. However, the excessive introduction of transition metals or synthetic carriers may lead to issues such as secondary pollution and increased synthesis costs, which are detrimental to green and sustainable applications [21,22,23].
Mineral materials, owing to their wide availability, structural stability, and abundance of surface-active sites, have gradually gained attention for enhancing nanozyme performance [24,25,26]. Recent studies have confirmed that certain mineral materials possess the ability to enhance peroxidase-like activity, thereby improving the efficiency of detection systems [27,28,29,30]. As common and environmentally friendly mineral materials, clay minerals possess stable structures, high specific surface areas, and abundant Lewis acid–base sites-AlO6 octahedra. The AlO6 in their structures has been proven capable of activating hydrogen peroxide, yet the corresponding mechanistic explanation remains scarce. As a widely existing natural mineral, hydroxyapatite has been used for activating hydrogen peroxide due to its porosity, stability, and abundant hydroxyl groups. Its surface possesses only Lewis acidity characteristics, lacking basic sites. Therefore, we selected two typical clay mineral materials, pyrophyllite and kaolinite, as the primary subjects of study, employing MOFs loaded onto their surfaces. Hydroxyapatite serves as a contrast to demonstrate the role of Lewis acid–base sites in the mechanism. In addition, research on the construction of high-performance nanozymes by compositing mineral materials with MOFs is still in its infancy. The variety of such composite materials remains limited, and the intrinsic mechanism underlying their synergistically enhanced catalytic performance is still unclear.
Based on this, the present study aims to construct nanozyme materials with oxidase-like activity by compositing MIL-101(Fe) with mineral materials such as pyrophyllite, kaolinite, and hydroxyapatite, and to apply them for the sensitive detection of aspartic acid in water bodies. The morphology and structural composition of the catalysts were systematically characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). Furthermore, the mechanisms for enhanced oxidase-like activity and generation of reactive oxygen species were investigated through quenching experiments, electron spin resonance (ESR) spectroscopy, and CO2/NH3 temperature-programmed desorption (TPD) analysis. The accuracy and applicability of the developed sensor were also evaluated via standard addition and recovery experiments in real water samples. These findings not only provide novel materials for the high-performance colorimetric detection of amino acids but also offer theoretical insights into the mechanism of enzyme-mimetic activity enhancement in mineral-MOF composites, holding reference value for the development of new nanozyme sensors for detecting small molecules in environmental matrices.

2. Results and Discussion

2.1. Structure Characterization of Clay-MOF Catalysts

For the three MOF minerals (Py-MOF, OH-MOF, and Ka-MOF), as shown in Figure 1A, within the scanning range of 10–90°, Py-MOF and OH-MOF exhibited peaks at 36.7°, 45.1°, 59.1°, and 65.7°, which match well with the standard XRD pattern of MOF. Ka-MOF showed peaks at 22.4°, 34.9°, 39.5°, 48.7°, and 67°, corresponding closely to the standard XRD pattern of Ka-MOF (JCPDS card No. 03-0897) [31]. These results indicate that the synthesized minerals possess high crystallinity without impurity peaks, and that Py-MOF, OH-MOF, and Ka-MOF all maintain the crystal structures of the original mineral catalysts.
As seen in Figure 1B, the loading of MOF materials on the mineral surfaces did not markedly alter the active structural sites, indicating that the incorporation of MOF did not disrupt the original crystal structures of the minerals. However, after introducing MOF into the kaolinite structure, the peaks at 1039 cm−1 (C-O-C) and 550 cm−1 (Fe-O) were significantly enhanced [32,33]. Therefore, further characterization and analysis of the surface structures of the three MOF minerals are warranted. Figure 1C–E displays the crystal structures of the three MOF minerals. The morphology and microstructure were examined using scanning electron microscopy (SEM). Analysis revealed that all MOF minerals are composed of multiple fine nanowires with diameters ranging approximately from 100 to 300 nm. When MOF was incorporated into the structures of the three minerals, no significant changes in the overall morphology were observed.
Accordingly, inductively coupled plasma optical emission spectrometry (ICP-OES) and X-ray photoelectron spectroscopy (XPS) were used to analyze the chemical compositions of the three types of clay-MOF materials. The specific results are summarized in Table 1. The Py-MOF material contained 4.54% Al, 4.89% Fe, 6.62% Si, and 39% O. In the OH-MOF catalyst, the proportion of Fe showed no significant change, while the oxygen content increased by approximately 12%. For the Ka-MOF material, the Fe content increased by about 5%, whereas the Si content decreased by around 4.2%. The carbon (C) element accounts for 44.74%, 39.69%, and 45.45% in the Py-MOF, OH-MOF, and Ka-MOF nanozyme materials, respectively. The sum of the elemental percentages for all three nanozyme materials is 100%. The results indicate that the MOF material has successfully been combined with the kaolin surface and formed new chemically active sites.
The three peaks centered at 530.9 eV, 531.8 eV can be attributed to the lattice oxygen species and defective O2− species, respectively [34,35]. As shown in Figure 2A,B, both peaks have a blue shift to higher binding energy with the increase in MOF, which implies a decrease in electron density of the O species. In addition, these results suggested that some oxygen vacancies might be generated when MOF was replaced with Si ions in the Ka-MOF crystal structure, which exposed more Fe-O structures and consequently altered the content of Lewis acid and base sites on the catalyst surface.
Subsequently, temperature-programmed desorption (TPD) was employed to analyze changes in the acid and base sites on the clay mineral surfaces [36,37]. In the NH3-TPD profile, the characteristic peaks observed within specific temperature ranges 160–190 °C, 220–260 °C, and 320 °C or above are attributed to weak, medium-strength, and strong acid sites on the catalyst surface, respectively. Correspondingly, the CO2-TPD profiles exhibit characteristic peaks in the regions of 140–160 °C, 200–230 °C, and 300 °C or higher, which are assigned to weak, medium-strength, and strong basic sites, respectively. As shown in Figure 2C, all three composite MOF materials exhibit characteristic peaks associated with Lewis strong basic sites. Notably, Ka-MOF shows desorption peaks at approximately 250 °C and 650 °C, with significantly higher intensity compared to the other two materials, indicating the presence of both medium-strength and strong basic sites on its surface. Furthermore, analysis of the NH3-TPD profiles in Figure 2D reveals that both Py-MOF and Ka-MOF display characteristic peaks around 200 °C and 240 °C, suggesting the existence of medium-strength acid sites on their surfaces.
Furthermore, the introduction of MOF significantly enhances the intensity of the characteristic peaks associated with both strong Lewis acid and strong Lewis base sites. This is attributed to the incorporation of MOF materials onto the kaolinite surface, which involves disrupting the original Al-O-Si bonds and facilitating the formation of new Al-O-Fe linkages. Within this structure, the bridging oxygen (-O-) acts as a conventional Lewis basic site, while the Fe and Al centers function as Lewis acid sites, thereby generating a substantial number of Lewis acid–base pairs.

2.2. Peroxidase Activity of Clay-MOF Catalysts

In order to explore the influence of environmental factors on the peroxidase activity of material, 0.1 mg/mL of Ka-MOF, 20 mM of H2O2, 1.6 mM of OPD, and a reaction temperature 25 °C were selected as the final experimental parameters. Under the selected experimental parameters, Py-MOF, OH-MOF, and Ka-MOF can keep the catalytic performance stable for 20 min, which can meet the needs of practical detection. Furthermore, the apparent steady-state kinetic experiments were performed by changing the concentrations of substrates H2O2 and OPD in the system (Figure 3). The Vmax and Km of Py-MOF, OH-MOF, and Ka-MOF were calculated by the Lineweaver–Burk double inverse curve, respectively (Table 2). Compared to horseradish peroxidase (HRP), the three nanozymes show substantially higher Vmax values for both H2O2 and OPD, suggesting a superior capacity for catalyzing the oxidation of peroxidase substrates. In line with this kinetic evidence, all three CM nanozymes are confirmed to exhibit excellent peroxidase-like activity [38].
The surface structures of different minerals significantly influence peroxidase-like catalytic activity. As shown in Figure 4A,B, Py-MOF, OH-MOF, and Ka-MOF exhibited distinctly differentiated enzymatic activities toward two amino acids: AA and glutamic acid (GA). Furthermore, the differential responses of the amino acids to the various mineral-MOF catalysts were clearly demonstrated. Notably, AA consistently exhibited an inhibitory effect on all catalysts at every concentration tested, indicating that Ka-MOF catalysts can selectively and significantly identify AA.
The intensity of Ka-MOF exhibited a positive correlation with the concentration of AA within the range of 0–37.56 μM, as illustrated in Figure 4C. The regression equation was determined to be y = −0.09539x + 0.94451 (R2 = 0.949). The limit of detection (LOD) for AA was calculated to be 5.57 × 10−8 M using the formula LOD = 3σ/k, where k represents the slope of the calibration curve, and σ denotes the standard deviation of the tests. These results indicate that Ka-MOF exhibits high sensitivity toward AA. To evaluate the advantages of the Ka-MOF probe over other sensing platforms, we compared its effectiveness in detecting AA with that of previously reported fluorescence sensors used for pesticide residue detection (Table 3) [39,40,41,42,43,44]. The probe developed in this study demonstrates a lower detection limit and a faster response time compared to other probes listed in Table 3 for the detection of AA.
The Ka-MOF nanozyme material can catalyze the conversion of H2O2 into reactive oxygen species (e.g., hydroxyl or superoxide radicals), which subsequently oxidize o-phenylenediamine (ox-OPD) to generate OPD, a product with fluorescent and chromogenic properties exhibiting an absorbance peak at 417 nm. As shown in Figure 4D,E, it can be observed that when only OPD is present, no significant characteristic peak appears at 417 nm. However, in the presence of both OPD and H2O2 together with the Ka-MOF material, a distinct characteristic peak emerges at 417 nm. This confirms that our selection of 417 nm as the analytical wavelength is consistent with previously reported results in the literature. Furthermore, upon introducing AA into the system, a noticeable decrease in the characteristic peak at 417 nm was observed, demonstrating that the Ka-MOF nanozyme exhibits a specific response toward AA.
Among them, Ka-MOF demonstrated the highest detection efficiency and was therefore selected for further investigation. The specific detection of common interfering anions, including Cl−, NO3−, HCO3−, Ac−, Na+, K+, Cu2+, and Fe2+, by the Ka-MOF sensing system is illustrated in Figure 4F. Initially, the absorption spectra of ox-OPD in the presence of various anions (10 μM) were recorded. Subsequently, AA (100 μM) was introduced into the aforementioned solutions, and the intensity was measured. It was observed that the Ka-MOF sensing system maintained high selectivity toward AA in aqueous solution even at interferent concentrations as high as 0.1 mM, demonstrating its suitability for the analysis of AA content in water samples.

2.3. Possible Mechanisms

The surface electronic properties of the MOF and Ka-MOF nanozyme materials were characterized by electrochemical impedance spectroscopy (EIS) and Zeta potential. As shown in Figure S3, the electrochemical impedance spectroscopy (EIS) results indicate that the introduction of MOF onto the kaolinite surface led to a smaller curve radius, demonstrating a stronger charge transfer capability of the Ka-MOF material. As shown in Figure S4, the Zeta potential results indicate that the potentials of Ka-MOF are higher than those of the MOF material, proving that Ka-MOF is more stable in the reaction system than MOF. These two experiments demonstrate that the introduction of MOF onto the kaolinite surface enhanced both the surface electron transfer ability and stability.
To investigate the types of reactive oxygen species (ROS) present in the reaction system, a series of scavenger experiments was conducted. It is well known that MeOH and p-BQ are considered as effective quenching agents for OH• and O2•− (kOH/MeOH = 9.7 × 108 M−1 s−1) [45,46]. As shown in Figure 5A, the addition of MeOH had no significant effect on the detection efficiency, indicating that hydroxyl radicals (OH•) contributed negligibly to the suppression of AA detection in the Ka-MOF/H2O2 system. When TEMP (2,2,6,6-Tetramethyl-4-piperidinol) was introduced into the system, the absorbance ratio trend of AA became consistent with those of other amino acids, suggesting that 1O2 played a dominant role in the reaction.
Furthermore, electron spin resonance (ESR) spectroscopy was employed to identify the major ROS generated in the Ka-MOF/H2O2 system. TEMP, a specific trap for 1O2, reacts directly with 1O2 to form a stable adduct exhibiting a characteristic 1:1:1 triplet signal [47,48]. As depicted in Figure 5B, a clear triplet signal was observed in the Ka-MOF/H2O2 system, confirming the generation of 1O2. When 1 µL of DMPO was added to the system, it reacted with both OH• to form spin adducts detectable by ESR [49,50]. Characteristic signals of DMPO-OH• and were detected (Figure 5C), and their intensities decreased when AA was added in the Ka-MOF + OPD + H2O2 system. Similarly, the triplet signal of the TEMP-1O2 adduct also decreased with AA added. These results indicate the presence of all three types of reactive oxygen species in the Ka-MOF/H2O2 system, and all three reactive oxygen species were produced.
Finally, phosphate and pyrrole were used to inhibit the Lewis acid and base sites on the surface of Ka-MOF, respectively [51,52]. As illustrated in Figure 5D, the introduction of phosphate caused no significant change in the absorbance ratio of AA. In contrast, the addition of pyrrole resulted in an increase in the ratio from 0.6 to 0.9, indicating that Lewis basic sites on Ka-MOF play a major role in the reaction system. This finding is consistent with previous characterization results.
Based on all the above results, the proposed catalytic mechanism is illustrated in Figure 6. The Ka-MOF system involves two reaction pathways. As shown in Figure S4, the generation of O2•− was detected during the reaction. This is attributed to the initial adsorption of H2O2 and OPD onto the Lewis acid sites on the catalyst surface. H2O2 reacts directly with Fe3+ in the Al-O-Fe(III) structure, reducing Fe3+ to Fe2+ and generating O2•−. The Fe2+ in Al-O-Fe(II) subsequently reacts more readily with H2O2 to produce OH• radicals (Equations (1) and (2)). The XPS Fe 2p results before and after the reaction show no significant peak shift, indicating that the Fe3+/Fe2+ cycle remained largely unaffected. These two radical species then react to form 1O2 (Equation (3)) [53,54]. On the other hand, the abundant Lewis base sites present in Ka-MOF also serve as crucial active sites for activating H2O2 to generate reactive oxygen species. These sites are key active centers promoting the self-decomposition of H2O2 into 1O2 [55]. Consequently, the Lewis base sites on the Ka-MOF surface can directly generate 1O2 from H2O2 (Equations (4) and (5)). The synergistic effect of these three reactive oxygen species leads to the enhancement of the UV absorption peak of ox-OPD. As shown in Figure 5B,C, when AA was introduced into the system, it occupied the Lewis base sites on the Ka-MOF catalyst surface, resulting in a weakened 1O2 signal and a significantly reduced UV absorption peak of ox-OPD, while the OH• signal was not noticeably affected. This confirms that 1O2 is the primary species responsible for oxidizing OPD to ox-OPD in this reaction process.
Furthermore, we have supplemented the manuscript with the XPS Fe 2p spectra obtained before and after the reaction to demonstrate the role of the Fe3+/Fe2+ cycle in the reaction system.
H2O2 + Al-O-Fe (III) + e− ⟶ O2•− + Al-O-Fe (II) + 2H+
H2O2 + Al-O-Fe (II) +e− ⟶ Al-O-Fe (III) + 2OH•
O2•− + OH•+ H+ ⟶ 1O2 + H2O
H2O2 + Al-O ⟶ Al-O• + 2OH− + e−
2Al-O• + H2O2 → 2Al-OH+ 1O2
1O2, OH•+ OPD ⟶ ox-OPD

2.4. Influences of Various Reaction Conditions

The practical application potential of the designed sensor was evaluated through spike-and-recovery tests for AA in deionized water, pond water, and aquatic products such as Asian swamp eel and bream. All water samples underwent simple pretreatment and were spiked with AA at different concentrations (0.1 and 1 mg/L). As shown in Table 4, the recovery rates of AA across three replicate experiments ranged from 94.2% to 98.5%, with relative standard deviations (RSDs) all below 4%. These results demonstrate that the proposed method exhibits good reproducibility and stability, indicating its applicability for the detection of AA in aquaculture environments.

3. Experimental

3.1. Reagents and Chemicals

FeCl3·6H2O, NaCl, terephthalic acid (TA), NaHCO3, NaOH, H2O2, ethanol, urea and all amino-acid reagents were purchased from Sinopharm Chemical Reagent Co., Ltd (Sinopharm Chemical Reagent Co., Ltd., Wuhan, China). Pyrophyllite, kaolinite, hydroxyapatite and 2,2,6,6-Tetramethyl-4-piperidinol (TEMP, 99%) were purchased from Sigma Aldrich (Sigma Aldrich. Shanghai, China). All reagents were used directly and without any purification.

3.2. Synthesis of Different Iron Aluminate Catalysts

MIL-101(Fe) was synthesized hydrothermally according to the following procedure [19,56]. Iron (III) chloride hexahydrate (FeCl3·6H2O, 0.675 g) and terephthalic acid (0.2075 g) were dissolved in 30 mL of N, N-dimethylformamide (DMF). The mixture was subjected to ultrasonication and vigorous stirring until complete dissolution of the powders was achieved. The resulting solution was then transferred into a Teflon-lined stainless-steel autoclave and heated at 110 °C for 20 h. After the reaction was complete, the autoclave was allowed to cool naturally to room temperature. The solid product was collected by centrifugation, washed thoroughly three times with DMF and subsequently three times with ethanol, and finally dried overnight in a vacuum oven at 55 °C. The final products can be abbreviated as MIL-101(Fe).
The Clay Mineral@MIL-101(Fe) catalysts (where Clay Mineral = pyrophyllite, hydroxyapatite, or kaolinite) were synthesized using a modified hydrothermal method. Clay mineral powder (0.2 g), FeCl3·6H2O (0.675 g), and TA (0.2075 g) were co-dissolved in 30 mL of DMF. The mixture was ultrasonicated and stirred vigorously to ensure complete dissolution/dispersion of the solids. The homogeneous suspension/solution was then sealed in a Teflon-lined autoclave and reacted hydrothermally at 110 °C for 20 h. Upon cooling to ambient temperature, the resultant composite material was isolated by centrifugation. Purification involved sequential washing cycles: three times with DMF followed by three times with ethanol. The final product was dried overnight under vacuum at 55 °C, yielding the Clay Mineral@MIL-101(Fe) composite powder (named as Py-MOF, OH-MOF, and Ka-MOF).

3.3. Characterization of Clay Mineral@MIL-101(Fe) Catalysts

Powder X-ray diffraction (XRD) patterns were recorded by a Rigaku Multiflex diffractometer (Rigaku Multiflex diffractometer, Wuhan, China) with Cu Kα radiation over a 2θ range from 10 to 90°. Scanning electron microscope (SEM) images were studied using Hitachi SU8100 (Hitachi SU8100, Wuhan, China). The X-ray photoelectron spectroscopy (XPS) was performed with a MULTILAB2000 electron spectrometer (MULTILAB2000 electron spectrometer, Wuhan, China) from VG Scientific by using 300 W Al Kα radiation (225 W, 15 mA, 15 kV). The surface acid or base property of different catalysts was measured by temperature-programmed desorption (TPD). FTIR spectroscopy measurements are performed on a Nicolet Magna 750 spectrometer (Nicolet Magna 750 spectrometer, Wuhan, China) equipped with a vacuum cell.

3.4. Study on Peroxidase Activity over Clay Mineral@MIL-101(Fe) Catalysts

To investigate the influence of detection conditions on the nanozyme activity, the catalytic reaction conditions-including the type of clay mineral@MIL-101(Fe) catalyst, catalyst dosage, and the concentration of OPD, were systematically optimized to identify the most suitable reaction parameters. The solution pH was adjusted using a sodium acetate-acetic acid (NaAc-HAc) buffer solution, and the absorbance at 417 nm was recorded. Based on the optimal pH, the concentration of MIL-101(Fe) was varied from 0.1 mg/mL to 0.5 mg/mL, and the OPD concentration was varied from 0.4 mM to 2.0 mM, ultimately determining the conditions for maximal nanozyme activity.
Under the optimized catalytic conditions, the peroxidase-like catalytic kinetic parameters of clay mineral@MIL-101(Fe) were investigated using OPD and H2O2 as substrates. Reactions were conducted at room temperature for 15 min in NaAc-HAc buffer (0.2 M, pH = 4.0). Absorbance at 417 nm was recorded for solutions containing varying concentrations of OPD (0.4, 0.8, 1.2, 1.6, 2.0 mM) and H2O2 (0.20, 0.40, 0.60, 0.80, 1.0 mM). The concentration of the reaction product (ox-OPD) was calculated using its molar extinction coefficient at 417 nm (ε = 16,700 M−1 cm−1). Lineweaver–Burk plots (double-reciprocal plots) were constructed from the inverse of the initial reaction rate (1/V) versus the inverse of the substrate concentration (1/[S]) [57]. The Michaelis–Menten constant (Km) and maximum reaction rate (Vmax) were derived using the equation (Equation (7)):
1/V = (Km/Vmax) × (1/[S]) + 1/Vmax
where V represents the initial velocity, [S] is the substrate concentration, Km is the Michaelis constant, and Vmax is the maximum reaction velocity.
A series of 2 mL centrifuge tubes was prepared. To each tube, 20 μL of the clay mineral@MIL-101(Fe) catalyst solution was added, followed by 1.9 mL of acetate buffer (pH = 4.5), 10 μL of H2O2 solution, and 50 μL of OPD solution. The mixture was thoroughly vortexed to form the detection solution. Subsequently, 200 μL aliquots of different amino acid solutions (e.g., aspartic acid and glutamic acid) were added to individual detection solutions. After thorough mixing, the reaction was initiated and timed for 15 min. Upon completion, 2 mL of the reaction mixture was transferred to a quartz cuvette, and the corresponding UV-vis absorption spectrum was recorded, with the primary signal acquisition wavelength set at 417 nm.

3.5. Mechanism of Peroxidase Activity over Clay Mineral@MIL-101(Fe) Catalysts

In addition, quenching experiments were performed with the addition of MeOH, p-BQ and TEMP, which were widely employed as scavengers for OH• and 1O2, respectively. ESR spectra were used to identify ROS such as OH• and 1O2. More details were shown in Text S1. Pyrrole and Na (PO4)3 were used to inhibit Lewis base and acid sites on catalyst’s surface, respectively.

3.6. Determination of Amino Acids in Aquatic Products

The aquatic products sample was pretreated by high-speed centrifugation at 10,000 rpm for 5 min to remove a small amount of the sediment and by filtration through a 0.45 μm filter. The pretreated fish sample solution was subjected to amino acid detection according to the experimental steps of 3.4, and the amino acid content in the corresponding aquaculture water was measured.

4. Conclusions

In this work, the introduction of MOFs onto the surfaces of different clay minerals was found to directly influence the type and strength of their active sites, leading to distinct peroxidase-like activities. Compared to the individual Py-MOF, OH-MOF, and other oxidase-active materials reported, Ka-MOF exhibited superior oxidase-like activity and enabled specific detection of AA. The substitution of silicon in the kaolinite structure by MOF materials increased the density of Lewis acid–base sites on the surface, which facilitated the adsorption of H2O2 and promoted its self-decomposition to generate 1O2, thereby enhancing peroxidase-like catalytic activity. The probe signal intensity showed a good linear relationship with AA concentration in the range of 0–37.56 μM, with a detection limit of 55.7 nM. Compared with previously reported probes, this system offers high selectivity, strong anti-interference ability, and a low detection limit, demonstrating promising application potential in related fields. This study not only provides a new strategy for amino acid detection by utilizing various clay mineral-supported MOFs but also proposes a rational design pathway for the construction and functionalization of MOF-based sensing platforms.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/catal15121172/s1, Text S1. Detailed steps for ESR tests. Table S1. Quantitative analysis of acid or basic sites of various nanozyme. Figure S1. SEM diagrams of MOF. Figure S2. The Fe 2p of XPS characterization. Figure S3. EIS analysis of Ka-MOF and MOF. Figure S4. Zeta potentials of Ka-MOF and MOF. Figure S5. ESR spectra of DMPO-O2•− in Ka-MOF. Figure S6. (A) ESR spectra of DMPO-OH• and (B) TEMP1O2 in MOF. Figure S7. The Fe 2p of XPS characterization before and after reaction.

Author Contributions

C.T.: Conceptualization, Investigation, Funding acquisition. L.Z.: Data curation, Writing—original draft. J.C.: Formal analysis. J.G.: Supervision, Funding acquisition. Y.Y.: Formal analysis, Resources. C.D.: Writing—review and editing. T.L.: Writing—review and editing. J.P.: Writing—original draft. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Central Public-interest Scientific Institution Basal Research Fund (grant number 2025JBFM12) and the Central Public-interest Scientific Institution Basal Research Fund (grant number 2020XT08).

Data Availability Statement

The data supporting the findings of this study are available from the corresponding author upon reasonable request. All data have been processed and analyzed as presented in the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Catalysts 15 01172 g001
Figure 1. (A) XRD patterns and (B) FTIR spectra of Py-MOF, OH-MOF and Ka-MOF, respectively. (C–E) SEM diagrams of Py-MOF, OH-MOF and Ka-MOF.
Figure 1. (A) XRD patterns and (B) FTIR spectra of Py-MOF, OH-MOF and Ka-MOF, respectively. (C–E) SEM diagrams of Py-MOF, OH-MOF and Ka-MOF.
Catalysts 15 01172 g001
Catalysts 15 01172 g002
Figure 2. (A) XPS pattern of Py-MOF, OH-MOF and Ka-MOF. (B) Binding energy changes in O 1s XPS spectra in Ka-MOF. (C,D) The results of CO2-TPD (C) and NH3-TPD (D) over different catalysts.
Figure 2. (A) XPS pattern of Py-MOF, OH-MOF and Ka-MOF. (B) Binding energy changes in O 1s XPS spectra in Ka-MOF. (C,D) The results of CO2-TPD (C) and NH3-TPD (D) over different catalysts.
Catalysts 15 01172 g002
Catalysts 15 01172 g003
Figure 3. (A–D) are the influence curves of the OPD and H2O2 concentrations on the catalytic rate of peroxidase, respectively. ([OPD]= 1.6 mM; [H2O2] = 20 mM; [Ka-MOF] = 0.1 mg/mL; T = 25 °C).
Figure 3. (A–D) are the influence curves of the OPD and H2O2 concentrations on the catalytic rate of peroxidase, respectively. ([OPD]= 1.6 mM; [H2O2] = 20 mM; [Ka-MOF] = 0.1 mg/mL; T = 25 °C).
Catalysts 15 01172 g003
Catalysts 15 01172 g004
Figure 4. (A,B) Histogram showing the differences in absorbance at 417 nm for Ka-MOF in the presence of varying concentrations of aspartic acid and glutamic acid (calculated as (A − A0)/A0). (C) linear relationship between intensity at 417 nm and concentration of aspartic acid. (D,E) UV absorption spectra under different mixed solutions (417 nm). (F) absorbance response of the probe when the interfering substance coexisted with aspartic acid. ([OPD] = 1.6 mM; [H2O2] = 20 mM; [Ka-MOF] = 0.1 mg/mL; T = 25 °C; [AA or GA] = 100 μM; [Ions] =10 μM).
Figure 4. (A,B) Histogram showing the differences in absorbance at 417 nm for Ka-MOF in the presence of varying concentrations of aspartic acid and glutamic acid (calculated as (A − A0)/A0). (C) linear relationship between intensity at 417 nm and concentration of aspartic acid. (D,E) UV absorption spectra under different mixed solutions (417 nm). (F) absorbance response of the probe when the interfering substance coexisted with aspartic acid. ([OPD] = 1.6 mM; [H2O2] = 20 mM; [Ka-MOF] = 0.1 mg/mL; T = 25 °C; [AA or GA] = 100 μM; [Ions] =10 μM).
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Catalysts 15 01172 g005
Figure 5. (A) The effect of different scavengers on absorbance response of aspartic acid; (B) ESR spectra of TEMP-1O2 and (C) DMPO-OH•. (D) absorbance response of the probe when the Lewis acid and base sites scavengers coexist with aspartic acid.
Figure 5. (A) The effect of different scavengers on absorbance response of aspartic acid; (B) ESR spectra of TEMP-1O2 and (C) DMPO-OH•. (D) absorbance response of the probe when the Lewis acid and base sites scavengers coexist with aspartic acid.
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Catalysts 15 01172 g006
Figure 6. Proposed mechanism of Ka-MOF.
Figure 6. Proposed mechanism of Ka-MOF.
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Table 1. Different element ratios of various catalysts.
Table 1. Different element ratios of various catalysts.
NanozymeOFeAlSiC
Py-MOF39.34.94.56.644.7
OH-MOF51.46.01.21.739.7
Ka-MOF38.210.13.92.445.5
Table 2. Comparison of Km and Vmax parameters of different catalysts.
Table 2. Comparison of Km and Vmax parameters of different catalysts.
NanozymeKm (mM)Vmax (10−7 M min−1)
H2O2OPDH2O2OPD
Py-MOF1.20.457.017.2
OH-MOF0.30.727.835.0
Ka-MOF0.050.420.724.3
HPR0.21.84.67.2
Table 3. Comparison of LOD and response time of Ka-MOF with other probes.
Table 3. Comparison of LOD and response time of Ka-MOF with other probes.
ProbeLimit of DetectionLinear RangeResponse TimeReference
Eu/Gd-MOF18 μM0–5.0 mM15 min[41]
Cu/Tb@Zn-MOF4.132 μM20–140 μM- 30 min[42]
[Eu-(L) (H2O)2]10−4 M0–10 mM20 min[43]
Tb-MOF7.95 × 10−6 M0–100 μM30 min[44]
Ni (II)-MOF2.51 mmol/L0–1.136 mmol/L10 min[45]
Cd-MOF2.68 × 10−6 M0–10 μM30 min[46]
Ka-MOF55.7 nM0–37.46 μM20 minThis work
-: The response time in Cu/Tb@Zn-MOF is 30 min.
Table 4. Spiking and recovery experiments of AA in deionized water, pond water and aquatic products.
Table 4. Spiking and recovery experiments of AA in deionized water, pond water and aquatic products.
SampleSpiked Concentration (μM)Found (μM)Recovery
(%)		RSD (%, n = 3)
Deionized water10.974797.51.8
21.95297.62.4
54.92698.52.1
Pond water10.95395.31.36
21.88394.12.05
54.82096.41.82
Aquatic products10.945894.62.6
21.860932.8
54.75295.02.5
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Tian, C.; Zhang, L.; Yu, Y.; Liu, T.; Chen, J.; Peng, J.; Dai, C.; Gan, J. Enhancement of the Peroxidase Activity of Metal–Organic Framework with Different Clay Minerals for Detecting Aspartic Acid. Catalysts 2025, 15, 1172. https://doi.org/10.3390/catal15121172

AMA Style

Tian C, Zhang L, Yu Y, Liu T, Chen J, Peng J, Dai C, Gan J. Enhancement of the Peroxidase Activity of Metal–Organic Framework with Different Clay Minerals for Detecting Aspartic Acid. Catalysts. 2025; 15(12):1172. https://doi.org/10.3390/catal15121172

Chicago/Turabian Style

Tian, Chen, Lang Zhang, Yali Yu, Ting Liu, Jianwu Chen, Jie Peng, Chu Dai, and Jinhua Gan. 2025. "Enhancement of the Peroxidase Activity of Metal–Organic Framework with Different Clay Minerals for Detecting Aspartic Acid" Catalysts 15, no. 12: 1172. https://doi.org/10.3390/catal15121172

APA Style

Tian, C., Zhang, L., Yu, Y., Liu, T., Chen, J., Peng, J., Dai, C., & Gan, J. (2025). Enhancement of the Peroxidase Activity of Metal–Organic Framework with Different Clay Minerals for Detecting Aspartic Acid. Catalysts, 15(12), 1172. https://doi.org/10.3390/catal15121172

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