Catalyst Characterization
The Fourier Transform Infrared (FTIR) spectrophotometer recognized functional groups in the MSN and Cu-MSN. It can be seen in Fig. 1 that there was a broad band around the 3430 cm-1 associated with the stretching vibration of silanol groups (Si–O–H) on the surface of the mesoporous frameworks. Compared with MSN, the intensity of this band declined in Cu-MSN. This phenomenon is due to the displacement of some hydroxyl groups with copper atoms [28]. Moreover, the band at 458 cm-1 was caused by Si-O-Cu groups. The observed bands at 1630 cm-1 and 800 cm-1 arose from the bending vibration of Si-O–Si groups. The bands at 1070 cm-1 and 458 cm-1 stemmed from asymmetric and symmetric stretching vibrations of the Si-O–Si groups. The creation of copper silicate groups (Si-O-Cu) in the mesoporous structure gets blamed for the decline in the intensity of these bands [29].
The results obtained from the XRD pattern of crystallographic nature of pure and copper-modified mesoporous silica structures (MSN, Cu-MSN) are presented in Fig. 2. As can be seen from Fig. 2A, the existence of ordered hexagonal mesoporous silica nanostructure (p6mm) with two-dimensional hexagonal space groups was approved by a sharp diffraction peak of (100) plane located at 2.5° and two weak diffraction peak of (110) and (200) planes located at 4.1° and 4.8° respectively. Significant reduction for these peaks in Cu-MSN was found with MSN compared. The observed decrease could be attributed loading of copper atoms into the structure, which cause disarray. As Fig. 2 B displays, a wide peak at about 2θ =20–30° could be related to the amorphous structure of pure MSN, whose intensity decreased in Cu-MSN. The diffraction peaks of 111, 200, and 220 with low intensity at the range of 40–70° suggest the copper species on the surface of the MSN structure [30].
The results obtained from nitrogen adsorption-desorption isotherms and pore size distributions of MSN and Cu-MSN based on the NLDFT method are presented in Fig. 3. It can be seen in Fig. 3A that all samples are the type IV isotherms with the H4 hysteresis loop. It seems possible that these results are due to mesoporous structures with cylindrical pores. There were
two significant inflections of the capillary condensation at P/P0= 0.0–0.05 and 0.05-0.8, suggesting the small pore sizes and volumes. Also, the lack of enhancement of the adsorbed nitrogen at higher pressure resulted from the successful incorporation of copper into the MSN structure (higher relative pressure not shown). Fig. 3B. approved the pore size narrow distribution for the as-prepared samples [31].
easurement for determination of structural attributes of MSN and Cu-MSN are illustrated in Table. 1. As it is apparent in Table. 1, a brief look at the surface area, pore volume, and pore size of samples reveals that there are significant differences. The surface area of MSN and Cu-MSN was computed at 998 m2g-1 and 228 m2g-1, respectively. This reduction arose from loading the metal on the mesoporous structure that blocks the MSN pores, creating a less-ordered 2D hexagonal mesoporous silica framework. Also, metal grafting caused pore volumes to come down dramatically from 0.82 cm3g-1 for the MSN to 0.24 cm3g-1 for the Cu-MSN and pore size to go up steady from 3.34 nm for the MSN to 4.36 nm for the Cu-MSN. This means that the loading of copper occurred successfully (low pore volume), which causes the construction of further framework structures on the surface of the catalyst (large pore size) [28-29].
Table 1
Physical characteristics of the MSN and Cu-MSN
Sample
|
S
(m2g-1)
|
Vp
(cm3g-1)
|
W
(nm)
|
MSN
|
998
|
0.82
|
3.34
|
Cu-MSN
|
228
|
0.24
|
4.36
|
S, surface area; Vp, total pore volume; W, pore size
|
FESEM and TEM analysis present a visual representation of the surface morphology of the Cu-MSN. It is evident from Fig. 4A that constituent nanoparticles appeared as uniform spherical forms with average sizes of 30-300 nm. The formation of Cu-MSN with well copper atom distributions on an ordered pore framework was proved through the TEM measurement, which is in agreement with the SEM and XRD findings (Fig. 4B). Also, the results of EDX provided evidence of the existence of the copper species that help to the improvements of the enzymatic activity (Fig. 4C).
Catalytic activity
In an attempt to prove the potential of Cu-MSN as a peroxidase mimic, a series of catalytic oxidation reactions were developed. Following this, among chromogenic substrates of peroxidase, TMB was picked out owing to its non-cancerous, high sensitivity, and harmless to the human body. As Fig. 5A displays, it is evident that oxidizing TMB (colorless) to ox-TMB (blue product) can occur only in the Cu-MSN+TMB+H2O2 reaction system. To further clarify, other control reactions, the TMB+H2O2 system and TMB system were carried out in a similar time cycle; none displayed color and absorption intensity. Therefore, these findings lend support peroxidase-like behavior of Cu-MSN similar to natural peroxidase (HRP). A possible explanation for this is that Cu2+ ions were well scattered on the surface of the MSN which has robust interaction with the TMB in presence of H2O2. A similar proposed procedure with ABTS as one of the other peroxidase substrates was done to ensure the peroxidase-like activity of Cu-MSN, which corroborates the above findings (Fig. 5B).
Kinetic studies
To gain better insight into the catalytic mechanism of Cu-MSN as a promising peroxidase mimic, the steady-state kinetic assay was employed by altering the amount of (ABTS or TMB) and H2O2 as the substrates in a specific range, respectively. The oxidation reaction of ABTS and TMB have proven to be relatively reliable criteria for evaluating the efficiency of nanomaterials as artificial enzyme catalysts. ABTS can be defined as a negative peroxidase substrate. It encompasses sulfonic groups with a substantial electrostatic tendency toward the oppositely charged nanoparticles. Whereas TMB with two amine groups can be defined as a positive peroxidase substrate with a substantial tendency to the negatively charged nanoparticles. The enzyme's apparent kinetic parameters (km, Vmax, kcat, and kcat/km) were obtained by data processing in the Lineweaver-Burk and Eadie-Hofstee plot based on the Michaelis-Menten model (Fig.6).
The results, as shown in Table S1, overall, indicate the superiority of catalyst performance in the ABTS oxidation reaction over the TMB oxidation reaction. Numerous studies have attempted to explain the peroxidation activity of nanomaterials, km is well-known as an indicator to distinguish the affinity between enzyme and substrate. As can be seen from the table, lower km values of Cu-MSN toward ABTS, TMB, and H2O2 reflected the superb peroxidase-like activity of the proposed nanozyme than the other nanomaterials. It is noteworthy that comparing the turnover rate (kcat) of this catalyst as catalytic constants with others is further support for the superiority of catalytic activity of Cu-MSN. kcat/km as one of the prominent scales for comparing the catalytic efficiency validated the excellent performance of the as-prepared catalyst that stemmed from the high surface area and more metal-active site of Cu-MSN that makes it available for catalytic processes.
Evaluation of assay conditions
Considering Cu-MSN as an artificial peroxidase, it is critical to optimize environmental conditions such as temperature and pH values. The catalytic performance of natural peroxidase and its nanomaterial mimetics is strictly related to these parameters. Accordingly, the ABTS oxidation reaction was repeated at the pH range from 3 to 9 and the temperature range from 20 ◦C to 70 ◦C, respectively. As Fig. 7a displays, it is evident that the relative activity of Cu-MSN in pH=4 excelled the other pHs; the reason can be that electron transfer is easily run to achieve the ultimate product. In more pHs, H2O2 as a critical component is degraded, leading to the subside of the catalytic efficiency in the reaction system. In temperature investigations, Fig.7b shows an approximately steady trend from 20 °C to 70 °C that confirmed the stability of Cu-MSM in harsh conditions. Considering the utilization of the Cu-MSN as a biosensor for the biological sensing system, 37 °C was selected as the optimum temperature.
Detection of H2O2 and GSH
Most of the studies so far verified the importance of Hydrogen peroxide (H2O2) in many chemical reactions, pharmaceutical industries40, and medical diagnoses [41]. H2O2 can be defined as a hydroxyl radical (OH˙) producer that excessive amounts of it can cause irreparable damage. Concerning potential risks, the measurement of this factor is a crucial role in various processes [42]. Colorimetric methods have received particular attention among all analytical techniques due to their precision, reliability, sensitivity, and cost-effectiveness.
Given the superior potential catalytic activity of Cu-MSN as an enzyme mimic, a sensing protocol for H2O2 was developed without the need for sophisticated instruments and trained experts. The results of catalyst performance on H2O2 detection are illustrated in Fig. 8 (A-B). It is clear from this Fig that there was a significant increase in the absorption intensity of reaction product formation with the rise of H2O2 concentration in the oxidation cycle of ABTS. The analyses revealed that this Cu-MSN- based method can detect H2O2 with the limit of detection (LOD) of 0.2 µM in the range of 0.9 to 100 μM. The multiple comparisons with the different enzyme mimic in the literature shown in Table 2 confirm that Cu-MSN outperformed the others.
GSH, one of the most significant polypeptide thiol in organisms, can be a crucial defensive agent against pathogens like toxins and free radicals [43]. Besides, it is widely believed that GSH exerts an influence on many biological processes such as intracellular redox activities and gene regulation, which is why excessive GSH levels pose a severe threat to health [44]. Thus, the invention of simple and accurate procedures for GSH detection is an increasingly important area in the medicine and pharmaceutical industry. Due to the presence of the thiol group in its structure, this compound can be considered powerful and reduces oxidative radicals. According to this, a colorimetric method has been introduced to measure GSH based on the potential of Cu-MSN in enzyme mimics.
Herein, the GSH detection strategy was designed according to the outstanding peroxidase-like mimetic behavior of Cu-MSN via the colorimetric method. Fig. 8C visually represents significant absorption changes in the GSH measurement cycle. It is clear from this graph that there is a potent relationship between the two variables of the study (GSH, ABTSox). According to the results, the oxidation of ABTS noticeably declined with a steady rise in GSH concentration from 0.01 to 100 µM. This means that a competitive reaction occurs on the surface of the as-prepared enzyme-mimic in the presence of H2O2, which causes the green ABTSox to be slightly converted to colorless ABTS.
Fig. 8D illustrates the preliminary analysis of GSH detection in the [Cu-MSN+ ABTS+H2O2] system. A linear relationship (LOD) was gained in the range from 0.042 μM to 1 μM with a detection limit of 0.0126 μM (3σ/slope), which verified the high potential of Cu-MSN as a peroxidase mimetic in GSH detection. The multiple comparisons in different nanozymes and other methods display that Cu-MSN performed significantly better than the others, and also, the proposed method can be a reliable, simple, and prompt alternative in the sensing systems (Table. 2).
Table 2
Comparison of diverse nanomaterials for H2O2 and GSH detection systems
Catalyst H2O2 GSH
|
|
Methods
|
Linear range(µM)
|
LOD(µM)
|
Linear range(µM)
|
LOD(µM)
|
Ref
|
Cu-MSN
|
Colorimetry
|
0.9-100
|
0.2
|
0.042-1
|
0.0126
|
This work
|
FeS2 NPs
|
Colorimetry
|
80-200
|
0.91
|
0.3-35
|
0.15
|
[45]
|
Por-ZnFe2O4/rGa
|
Colorimetry
|
0.7-30
|
0.54
|
2-40
|
0.76
|
[46]
|
V2O5-Mtb
|
Colorimetry
|
30-400
|
4
|
0.1-30
|
0.069
|
[47]
|
PdCo@MSNs
|
Colorimetry
|
-
|
-
|
2-20
|
0.33
|
[48]
|
Si-CoO
|
Colorimetry
|
2-10
|
4.32
|
1-5
|
0.45
|
[49]
|
MoS2/rGO
|
Fluorimetry
|
-
|
-
|
60-700
|
25
|
[50]
|
g-C3N4-MnO2
|
Fluorimetry
|
-
|
-
|
0-2000
|
0.2
|
[51]
|
Co-MOCP/CPEc
|
Electrochemistry
|
-
|
-
|
2.5-950
|
2.5
|
[52]
|
Pt-ZnO
|
Electrochemistry
|
50-1000
|
5
|
-
|
-
|
[53]
|
a Por-ZnFe2O4/rGO: porphyrin modified ZnFe2O4/reduced graphene oxide; b V2O5-Mt: V2O5-montmorillonite; c Co-MOCP/CPE: Co-based metal-organic coordination polymer;
|
The proposed sensing mechanism
As one of the principal biothiols, the design of a prompt and reliable sensing platform for detecting GSH dosage is a current research interest in various fields, especially disease diagnosis [54]. Fig. 9A presents a visual representation of a feasible mechanism for the proposed colorimetric detection procedure. It is clear from this scheme, Cu-MSN and H2O2 can easily oxidize common chromogenic substrates like ABTS and TMB through the peroxidase catalytic reaction described as follows:
Metal active sites on the surface of Cu-MSN react with H2O2 to produce the reactive free radical based on its peroxidase-like activity, which converts the substrate (hydrogen donor) to oxidized form by electron transfer. Sharp absorbance at 652 and 414 nm verify the above mechanism.
As Fig. 9B displays, it is evident that the generation of the color product underwent some changes after introducing the GSH into the peroxidase cycle. Absorbance comparison between the s(Cu-MSN+ABTS+H2O2) and (Cu-MSN+ABTS+GSH+H2O2) approve that the existence of thiol in GSH creates an inhibitor environment that gives rise to the reduction of the absorbance value of ABTSox through the block of the active sites and reducing OH radicals result from the decomposition of H2O2.
Selectivity
Selectivity is the most critical factor in demonstrating the ability of biosensors in a detection system. Following this, a series of control
experiments with various metal ions and amino acids was performed under the optimal reaction conditions to check the specificity of Cu-MSN as a biosensor as can be seen in Fig.10. although the interferents group is 20 times higher than the GSH, none of them can prevent TMB oxidation except cysteine (Cys). Taking the high content of GSH compared to the cysteine in mammalian cells, L-Cys interference can be ignored. Therefore, the only conclusion that suggests itself is that the proposed sensing procedure based on the peroxidase-like activity of Cu-MSN has high selectivity towards GSH. Regarding the excellent capability of the as-prepared catalyst, the proposed colorimetric detection was utilized in biological samples for further investigation.
Analysis of real samples
Human serum was recruited as real biological fluid to investigate the potential of the proposed colorimetric procedure in medical diagnostics. All samples obtained from the local hospital were diluted 500 times the primary concentration because GSH concentration is strikingly high (0.9~1.2 mM) in humans [55] . After dilution, steady amounts of GSH were introduced into the serum and then similar to the above procedure, were utilized to compute the analytical parameters like recovery and relative standard deviation (RSD). As it is described in Table. S2, a brief look at RSD (0.18%-3.08%) and recovery (99%-99.9%) confirm previous findings and contribute additional evidence that suggests the proposed sensor-based colorimetric platform has satisfactory reliability in the analysis of biological applications.
Stability of catalyst
To confirm the superior intrinsic catalytic activity of Cu-MSN as a reliable alternative for natural peroxidase, long-term stability and reusability experiments were designed to monitor the practicability of the proposed catalyst in harsh conditions. The long-term stability was evaluated by analyzing the oxidation reaction of ABTS in the presence of a stock solution of Cu-MSN that was dispersed in 0.5 mM NaAc buffer and stored at room temperature for 30 days. From the results in (Fig. S1A), it is apparent that relative activity for the Cu-MSN/ABTS/H2O2 system was approximately steady in the first ten days; however, after that slight reduction in absorbance was found until 1 month. Retention of more than 87% of the initial catalytic activity in the storage period suggests the excellent stability of the prepared catalyst. The results of the reusability of Cu-MSN within seven peroxidase cycles are reported in Fig. S1B. It is clear from this Figure that the observed relative activity is higher than 90% after the seven catalytic cycles. An implication of these findings contributes additional evidence that suggests Cu-MSN can be a potent substitute for peroxidase in various applications.