Integrated GC–MS Profiling and Phytosynthesis of MnO₂ Nanoparticles Using Moringa oleifera: Assessment of Antioxidant, Cytotoxicity, and Potential In Vitro and In Silico Inhibitory Effects on α‐Amylase and α‐Glucosidase

ABSTRACT

Bioactive compounds from medicinal plants can enhance the therapeutic potential of trace metal–oxide nanoparticles. This study contributed to identifying the main volatile compounds and synthesizing manganese dioxide nanoparticles (MnO₂ NPs) using Moringa oleifera (MO) leaf extract and explored their biological applications. Gas chromatography–mass spectrometry (GC–MS) analysis identified 21 volatile compounds with known bioactivities from the leaves of MO. Transmission electron microscopy (TEM) and x‐ray diffraction analysis showed that MnO₂ NPs were spherical and crystalline, averaging ∼8.3 nm in size. Antioxidant activity, assessed by 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) and 2,2′‐azino‐bis (3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS) assays, revealed high potency (IC₅₀ = 9.08 ± 0.11 and 6.62 ± 0.12 µg/mL). Cell viability assays indicated relative non‐toxicity, with IC₅₀ values greater than 20 µg/mL for human embryonic kidney (HEK 293) and liver (HEPG2) cells. The antidiabetic effects were evaluated against α‐amylase and α‐glucosidase enzymes, showing IC₅₀ values of 36.58 ± 0.74 and 55.03 ± 1.68 µg/mL, respectively, compared to FDA‐approved acarbose. Docking studies yielded scores of −6.10 and −7.32 kcal/mol. Overall, these results highlight that the MO‐synthesized MnO₂ NPs can be explored as potential antioxidant, cytoprotective, and antidiabetic agents for therapeutic uses.

Manganese oxide (MnO NPs), synthesis of Moringa oleifera leaf extract nanoparticles, are spherical and crystalline with a size of 8.3 nm. They exhibit strong antioxidant activity in DPPH and ABTS assays, with IC₅₀ values of 9.08 and 6.62 µg/mL, respectively, and demonstrate low toxicity to kidney and liver cells. MnO NPs also show significant antidiabetic effects against α‐amylase and α‐glucosidase, suggesting their potential as antioxidants, cytoprotective, and antidiabetic agents.

1. Introduction

Hyperglycemia and physiological imbalance are hallmarks of diabetes mellitus (DM). DM is defined as a deficiency in insulin generation or the deterioration of insulin produced. Types 1 and 2 are the most common types of DM among the well‐known varieties that currently exist [1]. Insulin infusion is necessary for the treatment of Type 1 diabetes, but food restriction, exercise, and the use of synthetic antidiabetic medications are necessary for the treatment of Type 2 diabetes. Current treatment of diabetes involves insulin injection for Type 1 diabetes and the use of an oral class of blood glucose‐lowering drugs. The first and most popular class is the biguanides, with the popular medication metformin falling under this class; other classes are sulfonylurea, meglitinides, DPP‐4 inhibitors, thiazolidinedione, SGLT 2 inhibitors, α‐amylase inhibitors, and α‐glucosidase inhibitors [2]. The treatment of diabetes is approached through monotherapy with metformin as the first option; sometimes this drug is combined with another oral antihyperglycemic drug, creating a combination therapy, and like all medications, has side effects [3]. The side effects of continuous use of metformin may result in renal and liver failure. Sulphonylurea loses efficacy in 6–12 months of use, and DPP‐4 inhibitors cause acute pancreatitis [4]. One promising approach to treat diabetes is to target and inhibit the initial breakdown of glucose using acarbose, voglibose, and miglitol [5]. Acarbose is the preferred α‐amylase and α‐glucosidase inhibitor, as it is the most widely used. However, its constant use results in severe side effects, such as belching, abdominal pain, and diarrhea. With time, the dosage of acarbose increases, leading to further gastrointestinal complications, which eventually lead to patients removing acarbose; therefore, an alternative without side effects is required [6].

Recently, the use of medicinal plants with natural compounds has attracted interest due to their fascinating pharmacological properties and reduced or no side effects [7]. Medicinal plants form the basis for primary health care in developing countries, especially in most African countries, and have been used in the treatment and management of various diseases, such as viral and bacterial infections, diabetes management, hypertension, inflammation, pain, cancer, and male and female infertility [8, 9]. In particular, the extracts from medicinal plants possess many bioactive phytochemicals with potent pharmacological properties, which are attributed to their therapeutic use in traditional medicines [10]. Bioactive compounds, such as alkaloids, glycosides, flavonoids, saponins, and terpenoids, with proven oxidative stress‐mitigating potential, are among the most important phytochemicals found in the extracts of medicinal plants. Oxidative stress plays a crucial role in DM, as it causes a reduction in glucose absorption; therefore, the treatment technologies targeting the initial breakdown of glucose have been suggested as an alternative approach to managing diabetes [11].

Among the most widely used medicinal plants is Moringa oleifera (MO), originally found in India but also cultivated in the rest of Asia, Africa, the Caribbean islands, North America, and South America [12]. Historically, all its parts have been utilized to treat a wide range of diseases. The leaves are the most used part of the tree, owing to their rich content of compounds with diverse chemical structures and physiological properties, including antimicrobial, anticancer, antidiabetic, anti‐inflammatory, cholesterol‐lowering activity, antispasmodic, and antidiuretic activities [13, 14]. Further, the methanolic extract of MO was shown to exhibit antiepileptic, anticonvulsant, antidiabetic, cardiovascular, anti‐inflammatory, anti‐hypertensive, anthelmintic activity, and central nervous system (CNS) activity properties. In contrast, the ethanolic extracts from the seeds and leaves showed hepatoprotective, anticancer, and anti‐inflammatory activity [15]. Another study revealed the radical scavenging and anti‐inflammatory properties of the roots’ aqueous and alcoholic extracts [16].

With the emergence of nanomedicine, trace elements, such as iron, magnesium, manganese, copper, selenium, and zinc, present in the human body, have been utilized in the synthesis of metal nanoparticles [17]. Due to their distinct plasmonic and optoelectronic properties, these nanomaterials are regarded as alternative candidates. Most importantly, manganese nanoparticles continue to be explored in various applications, such as catalysis, drug delivery, antibacterial/antifungal, and tumor therapy [18, 19, 20, 21]. As an essential nutrient, manganese is a trace mineral present at minute levels in the body. Primarily present in the pancreas, liver, kidneys, and bones, manganese assists in the formation of bones, blood clotting factors, sex hormones, and connective tissues, as well as reduces inflammation in the body [22]. Previous research has linked manganese to Type 2 diabetes, as manganese is involved in blood sugar management, a major indicator in diabetic patients. Manganese activates many enzymes in the metabolism of carbohydrates, glucose, cholesterol, and proteins and is involved in many chemical processes in the body [23]. Additionally, manganese deficiency can result in decreased pancreatic insulin synthesis and glucose intolerance; therefore, manganese supplements have been found to stimulate and increase insulin secretory efficiency [24]. Consequently, the use of a manganese source in nanoparticle synthesis could be advantageous in the treatment and management of Type 2 diabetes.

In the last few decades, the green approach to nanoparticle synthesis has become popular. A myriad of studies have reported the formation of different types of nanoparticles with different structural architectures using bioactive compounds from plant extracts [25, 26, 27]. The use of extracts from plants to synthesize manganese nanoparticles has numerous benefits. First, the extract‐based bioactive compounds have proved efficient in converting different Mn precursors to individual atoms, as shown in Table 1. Second, when Mn is transformed into Mn NPs or its oxide (MnO), the effectiveness of the nanoparticles can be enhanced, thus enabling their utilization for various biological applications [28, 29, 30]. Moreover, the integration of medicinal plant extracts containing bioactive functional groups into the nanoparticle surface during synthesis could accelerate ion bioavailability and improve the rate of absorption, therefore improving treatment efficiency [31].

TABLE 1.

Synthesis of extract‐capped nanoparticles from various Mn sources.

Plant extracts	Mn precursors	Morphology	Applications	References
Kalopanax pictus	KMnO4	Spherical	Degradation of dye	[32]
Saraca asoca	Mn(NO3)2	Stacked cubes	In vitro anticancer activity	[33]
Green tea	MnSO4	Nano algae‐like	Antibacterial activity	[34]
Olives	MnSO4·H2O	Spherical	Antioxidant and anticancer activity	[35]
Plectranthus amboinicus	KMnO4	Spherical	Antioxidant and antimicrobial activity	[36]
Gardenia resinifera	Mn(CH3COO)2·H2O	Spherical	Antibacterial activity	[37]

In this study, the focus will be on the gas chromatography–mass spectrometry (GC–MS) analysis and green synthesis of manganese dioxide nanoparticles using MO leaf extract, their physicochemical characterization, and the evaluation of their inhibitory effects on α‐amylase and α‐glucosidase enzymes in the management of diabetes.

2. Materials and Methods

2.1. Cells and Reagents

DPPH (2,2‐diphenyl‐1‐picrylhydrazyl), ABTS (2,2′‐azino‐bis (3‐ethylbenzothiazoline‐6‐sulfonic acid)), MTT (3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide), DMSO (dimethyl sulfoxide), potassium peroxydisulfate (K₂S₂O₈), ascorbic acid, and methanol were purchased from Sigma Aldrich Chemicals Co. (St. Louis, Missouri, USA). Human liver cancer (HepG2, ATCC HB8065) and human embryonic kidney (HEK 293, CRL‐1573) cells were purchased from CELLONEX (Separation Scientific SA (Pty) Ltd., Johannesburg, South Africa), whereas Dulbecco's modified Eagle's medium, fetal bovine serum (FBS), and penicillin‐streptomycin were purchased from Celtic Molecular Diagnostics SA (Pty) Ltd. (Cape Town, South Africa).

2.2. Plant Collection and Extraction

MO leaves were collected in the wild in March 2022, around Madombidzha, Louis Trichardt, Limpopo province (Latitude: 23°7′27″ S and Longitude: 29°48′ 53″ E) and kept at the CERE herbarium, University of South Africa, Gauteng Province, South Africa. The plant components, along with a voucher specimen of air‐dried leaves, were deposited and identified. To prepare the MO extract, freshly ground MO leaves (1 g) were mixed with distilled water (100 mL). The mixture was gently heated using a magnetic stirrer at 60°C for 1 h. After this, the solution was allowed to cool and filtered using the Whatman No. 1 filter paper, and the obtained extract was kept at 4°C.

2.3. GC–HRTOF‐MS Analysis

A small amount (12 mg) of the dry raw material was extracted using 0.9 mL of methanol, which was thoroughly vortexed and then filtered with a 0.5‐µm filter syringe. After the sample was transferred to an autosampler vial and analyzed. A gas chromatography–high‐resolution time‐of‐flight (GC–HRTOF‐MS) instrument (LECO Corporation, St. Joseph, MI, USA) was used for the analysis and calibrated before use. Subsequent samples were analyzed using a Pegasus GC–HRTOF‐MS instrument (LECO Corporation, St. Joseph, MI, USA), equipped with an Agilent 8890A gas chromatography (Agilent Technology Inc., Wilmington, DE, USA), operating in high resolution with a Gerstel MPS multipurpose auto‐sampler (Gerstel Inc., Germany). The column mode was at constant flow, and the characteristics were 30 m × 0.25 mm ID  ×  0.25 µL Rxi‐5 ms column (Pennsylvania, USA). The carrier gas used was helium at a flow rate of 1 mL/min. Samples were injected in a splitless mode, and the injection volume was 1 µL for each sample. The inlet and transfer line temperatures were set at 250°C. The oven temperature was set initially to 70°C and maintained at this temperature for 1 min. This was then increased to 120°C, at 10°C/min, held for 2 min, and then raised to 300°C at 10°C/min for 3 min. The detector voltage was set at 70 eV for electronic ionization. The recommended MS data acquisition rate of 13 spectra/s m/z was used, with a range of 30–700.

2.4. Collection and Identification of Compounds

The data collected from the GC–HRTOF–MS were formatted and processed on the LECO Chroma TOF‐HRT software. Peaks and mass spectra were compared with NIST, Mainlib, and Replib metabolomics libraries. Each identified metabolite was assigned a name when the similarity value (SV) was >800 over 1000, which is 80%.

2.5. Synthesis of MnO₂ Using MO

To synthesize MnO₂ nanoparticles, a flask containing the extract of MO (25 mL) was mixed with 3 g/100 mL of MnCl₂·4H₂O (ACS Reagent, ≥98%, Merck, Johannesburg, South Africa) solution and stirred at 60°C for 1 h. The formation of the nanoparticles was indicated by the initial solution pH of 5.23, which changed to 4.44 at the end of the reaction. Subsequently, repeated centrifugation of the solution to remove any unreacted extracts and precursors was done at 4400 rpm for 30 min. The pellets obtained were dried overnight in an oven at 50°C and then calcined at 200°C for 2 h to obtain black‐colored pellets.

2.6. Characterization

Fourier‐transform infrared (FTIR) spectroscopy (PerkinElmer Frontier, USA) analysis of the functional groups present in the MnO₂ NPs and dried extract was done in the range 4000–500 cm⁻¹ with an ATR detector. Transmission electron microscopy (TEM JEOL JEM 2100, Japan) was used to examine the morphology of the nanoparticles. A TEM micrograph was obtained at a 200 kV voltage, and an energy‐dispersive x‐ray (EDX) analyzer fitted to the TEM instrument was used to ascertain the elemental composition. The surface charge of the colloidal dispersion of nanoparticles was measured using Nano‐ZS (Malvern, UK). The structural property of the dried nanoparticles was determined using an x‐ray diffractometer (RIGAKU SmartLab, Tokyo, Japan) with Cu Kɑ (1.54 Å) radiation. Moreover, a ThermoScientific EVOLUTION One Plus UV–vis spectrophotometer was used to measure the absorption spectra of the nanoparticle dispersion.

2.7. Antioxidant Activity

2.7.1. DPPH Radical Scavenging Activity

The radical scavenging activity (DPPH) of the MnO NPs was carried out with slight modification [24]. In summary, MnO₂ NPs were introduced into a 0.1‐mM methanol solution of DPPH at different concentrations, and the range of ascorbic acid and MnO₂ NPs concentrations investigated was 5.0–1000 µg/mL. Methanol and ascorbic acid were employed as blank and positive control, respectively. After 30 min incubation, absorbance was measured at 517 nm. Data were calculated as the percentage of inhibition of three independent experiments using the following formula. Utilizing the inhibitory percentages, the IC₅₀ values were calculated, and the antioxidant activity was determined:

$$\mathrm{Inhibitory}\mathrm{activity}\%=1-\frac{\mathrm{Abs}\mathrm{of}\mathrm{sample}}{\mathrm{Abs}\mathrm{of}\mathrm{control}}\times 100$$

where Abs is the absorbance in the presence or absence of samples.

2.7.2. ABTS Radical Scavenging Activity

The radical scavenging activity (ABTS) of MnO₂ NPs was measured as described [25]. To create the ABTS cation radical, 7 mM ABTS powder and 2.45 mM potassium peroxydisulfate (K₂S₂O₈) were combined in distilled water, and the combination was left for 16 h in the dark. The cation combination was quantified using methanol, resulting in an absorbance at 734 nm of 0.70 (±0.02). Ascorbic acid, the positive control, was added to the MnO₂ NPs in the same quantities. The DPPH activity (2.4.1) was followed to perform the ABTS activity by measuring the absorbance at 734 nm using a Varioskan‐Flash microplate reader (ThermoFisher Scientific, Vantaa, Finland). The formula mentioned in Section 2.4.1 was used to calculate the ABTS activity.

2.8. Cytotoxicity Activity

The cell viability assay was used to assess the cytotoxic potential of MnO₂ NPs using a protocol described [26]. Human liver cancer (HepG2) and HEK 293 cells were cultured in Dulbecco's Minimal Essential Medium (DMEM, Gibco) supplemented with 10% FBS and 1% penicillin‐streptomycin solution. A number of 1 × 10⁴ cells/mL were seeded in 96‐well plates at 100 µL/well and incubated for 24 h at 37°C in a humidified 5% CO₂ incubator. Thereafter, cells were exposed to different MnO₂ NPs doses, ranging from 5.0 to 1000 µg/mL. Doxorubicin and untreated cells were used as positive and negative controls, respectively. After 24 h of exposure, 20 µL of MTT solution (20 mg/mL) prepared in PBS was added to each well, and the plates were incubated for an additional 4 h before absorbance measurements were taken.

$$\mathrm{Cell}\mathrm{viability}\%=\frac{\mathrm{Abs}\mathrm{of}\mathrm{treated}}{\mathrm{Abs}\mathrm{of}\mathrm{untreated}}\times 100$$

where Abs is absorbance in the presence or absence of samples.

2.9. Inhibitory Effects of α‐Amylase and α‐Glucosidase

2.9.1. α‐Amylase Inhibitory Activity

Using a slightly modified technique [38], the inhibitory effect of α‐amylase was determined. In summary, 20 µL of MnO₂ NPs, 50 µL of phosphate buffer, and 10 µL of α‐amylase (2 U/mL) were mixed in a 96‐well reaction plate and incubated for 20 min at 37°C. Then, a 1% soluble potato starch substrate (100 mM phosphate buffer, pH 6.8) was added to the mixture, followed by incubation for 30 min. Both MnO₂ NPs and acarbose, the positive drug control ranges from 0.125 to 2 mg/mL concentration. We used phosphate buffer (100 mM, pH = 6.8) as a negative control. Following the incubation period, 100 µL of DNS was added and heated for 10 min. An ELISA microplate reader (VarioSkan Flash, Thermo Fisher Scientific, Vantaa, Finland) was utilized to quantify the absorbance.

$$\mathrm{Inhibitory}\mathrm{activity}\%=1-\frac{\mathrm{Abs}\mathrm{of}\mathrm{sample}}{\mathrm{Abs}\mathrm{of}\mathrm{control}}\times 100$$

where Abs represents the absorbance in the presence and absence of samples.

2.9.2. α‐Glucosidase Inhibitory Activity

The α‐glucosidase inhibitory enzyme activity of MnO₂ NPs was determined as reported [38]. Briefly, 20 µL of different concentrations of MnO₂ NPs, 50 µL of phosphate buffer, and 10 µL of α‐glucosidase (1 U/mL) were incubated in a 96‐well plate for 15 min at 37°C. Thereafter, 5 mM P‐NPG substrate was added to 20 µL of the mixture and incubated for 20 min at 37°C. To stop the reaction, 50 µL of 0.1 M Na₂CO₃ was added to the mixture. The MnO₂ NPs and acarbose concentrations range from 0.125 to 2 mg/mL, whereas phosphate buffer (100 mM, pH = 6.8) was used as the negative control. The p‐nitrophenol was quantified using an ELISA microplate reader (VarioSkan Flash, Thermo Fisher Scientific, Vantaa, Finland) at an absorbance of 405 nm. The percentage inhibition was calculated using the formula in Section 2.6.1.

2.10. Molecular Docking Studies

To acquire more insights and validate the observed biological activities, we investigated the activity of MnO₂ nanoparticles using molecular docking simulations following a method described by Joseph and colleagues [39]. The RCSB Protein Data Bank was used to download anti‐diabetic receptors human pancreatic α‐amylase (PDB ID: 1B2Y) and human lysosomal acid‐α‐glucosidase (PDB ID: 5NN8). The protein structures were prepared for molecular docking by eliminating non‐essential ligands and water molecules, followed by the incorporation of polar hydrogen atoms and Kollman charges. For the docking process, the binding sites of the co‐crystalized ligands were selected, and a sphere was created around the proteins 1B2Y (x: 11.621; y: 5.607; z: 46.146) and 5NN8 (x: −10.909; y: −45.921; z: 93.68). The Mn₃O₄ crystal and acarbose were, respectively, subjected to energy minimization using the General Atomic and Molecular Electronic Structure System (GAMESS, US). Docking simulations were conducted using AutoDock 4.2, with parameters set to 100 genetic algorithm runs, a population size of 300, and 25 million energy evaluations. To ensure the reliability of the docking outcomes, re‐docking was performed to assess the root‐mean‐square deviation (RMSD) and spatial superposition of the predicted binding pose. The interaction of protein–ligand conformations and hydrogen bonds was visualized by using Discovery Studio 2024 Client.

2.11. Statistical Analysis

Data are expressed as the mean ± SD of triplicate experiments. GraphPad Prism 8.2 (GraphPad Prism 8 Software, CA, USA) and Origin Pro 2024 (OriginPro Corporation, New York, NY, USA) software were used for data analysis.

3. Results and Discussion

3.1. GC–MS Analysis

The GC–MS analysis of the methanol extract of MO revealed a total of 21 identified compounds with seven major constituents, which are: benzoic acid, methyl ester, n‐hexadecanoic acid, cyclohexane, 1,3,5‐triphenyl‐, cholesta‐4,6‐dien‐3‐ol, cholesta‐3,5‐diene, stigmasta‐3,5‐diene, and cholesterol. The corresponding chromatogram is presented in Figure 1, and detailed information on the identified chemical constituents, including their names, retention times (RT), molecular formulas, and similarity indices, is summarized in Table 2.

FIGURE 1.

GC–MS chromatogram of methanol extracts of Moringa oleifera leaves (MO).

TABLE 2.

Bioactive compounds found in methanol extracts of Moringa oleifera (MO).

No.	Name	R.T. (min)	Formula	Similarity
1	Decane	4.75243	C10H22	949
2	Benzoic acid, methyl ester	6.09694	C8H8O2	888
3	Benzoic acid, 4‐methyl‐, methyl ester	8.16468	C9H10O2	933
4	Neophytadiene	17.2029	C20H38	916
5	Hexadecanoic acid, methyl ester	17.6942	C17H34O2	917
6	n‐Hexadecanoic acid	18.4465	C16H32O2	919
7	Phytol	19.9239	C20H40O	806
8	Methyl stearate	19.9731	C19H38O2	915
9	Dodecanamide	20.4978	C12H25NO	829
10	Nonadecane	20.705	C19H40	854
11	Cyclohexane, 1,3,5‐triphenyl‐	22.8842	C24H24	879
12	Tetracosane	23.2482	C24H50	881
13	Heptacosane	24.7672	C27H56	768
14	4‐Methyl‐1‐phenylpentan‐3‐ol	25.0409	C12H18O	755
15	Cholesta‐4,6‐dien‐3‐ol, (3)‐	26.1794	C27H44O	882
16	Cholesta‐3,5‐diene	26.3375	C27H44	921
17	1,1′:3′,1″‐Terphenyl, 5′‐phenyl‐	26.6487	C24H18	882
18	Stigmasta‐5,22‐dien‐3‐ol, acetate, (3,22Z)‐	27.3872	C31H50O2	832
19	Stigmasta‐3,5‐diene	27.931	C29H48	847
20	α‐Tocopherol	28.1332	C29H50O2	858
21	Cholesterol	28.1858	C27H46O	860

The analysis uncovered several bioactive and pharmacologically significant compounds from the leaves of MO [40, 41]. The major volatile constituents included alcohols, alkanes, alkenes, amides, saturated fatty acids, and terpenoid compounds. Among the compounds, neophytadiene is recognized for its antioxidant, anti‐diabetic [42], and anti‐inflammatory properties [43]. n‐Hexadecanoic acid (palmitic acid) was identified for its antioxidant activity [44], whereas phytol is notable for its well‐documented antioxidant, anticancer [45], and diuretic effects [46]. Additionally, heptacosane has been reported to exhibit anti‐corrosive and antioxidant activities [47], whereas tetracosane has been associated with enhanced antioxidant and cytotoxic capacities [48]. Cholesta‐3,5‐diene demonstrated cytotoxic effects in primary human oral keratinocytes [49]. Likewise, stigmasta‐3,5‐diene exhibits both antioxidant and potential anti‐diabetic activities [50]. Finally, α‐tocopherol, a well‐known form of vitamin E, was identified for its potent antioxidant properties and chemopreventive role against cancer. Notably, it has also been shown to compromise the cytotoxic and cytostatic actions of various protein kinase inhibitors (PKIs) [51]. Among the main compounds, two compounds have shown potential as reducing or capping agents during nanoparticle formation. For example, benzoic acid can act as a reductant and surface stabilizer during the synthesis of Au nanoparticles [52], whereas hexadecanoic acid has been used as a complex to build lamellar nanostructures due to its retention in the nanoparticles’ cores [53].

3.2. Synthesis and Characterization of MnO₂ Nanoparticles

Previous studies on the phytochemical screening of the extracts of MO revealed an abundance of bioactive compounds, such as alkaloids, amino acids, fats, flavonoids, saponins, and oils [54, 55]. These compounds possess ionizable functional groups efficient in the reduction of metal ions to their atoms, thus presenting effective capping, stabilizing, and reducing agents. For the preparation of MnO NPs, aqueous‐derived extract of MO was used as a cost‐effective, safe, and environmentally benign method for nanoparticle synthesis. A change in the solution's pH was used to track the phyto‐reduction of manganese ions in the presence of oxygen to generate manganese dioxide (MnO₂) using the aqueous extract. After the reaction was completed, a final pH of 4.44 was noticed, from an initial pH of 5.23, which indicated the formation of MnO₂ NPs.

3.2.1. TEM and Selected Area Electron Diffraction (SAED)

In Figure 2a, the TEM image of the extract‐synthesized MnO₂ NPs showed small (average diameter ∼8.3 nm) spherical nanoparticles. In addition, the nanoparticles display aggregation, a common feature of many metallic nanoparticles with magnetic properties. The observed aggregation could be due to the high surface energy, electrostatic attraction, and the smaller size of the nanoparticles formed [56]. The micrograph showed that there is secondary material surrounding the nanoparticles, which is associated with the bioorganic molecules responsible for synthesizing and stabilizing the spherical MnO₂ NPs. The surface of nanoparticles can adsorb phytochemicals derived from plant extracts because these phytochemicals possess potent chelating properties, which significantly speed up the electron transport between the substrate and the active metal center [31]. In Figure 2b, the SAED pattern of the MnO₂ nanoparticles showed discrete bright spots in coaxial rings, further illustrating the crystalline nature of the formed nanoparticles.

FIGURE 2.

(a) TEM image, (b) SAED pattern, (c) EDX spectrum, and (d) zeta‐potential (inset: stability) of the synthesized MnO₂ nanoparticles. MO, Moringa oleifera.

3.2.2. EDX and Zeta Potential

By utilizing the EDX spectroscopic technique, the elements present in the nanoparticles were determined (Figure 2c). The spectrum displayed both Mn and O reduction peaks, whereas the Cu and C peaks were likely due to the carbon‐coated copper grid. Besides, the surface charge analysis of the MnO₂ nanoparticles (Figure 2d) indicated a lower positive zeta potential of 5.6 mV, as the MO leaf extract induces a net positive charge. Generally, a high surface charge arising from electrostatic repulsion between nanoparticles is crucial for stabilizing and preventing nanoparticle aggregation. In this instance, the low positive surface charge from the MnO₂ NPs could be attributed to the high protein content from the MO extract [57]. Hence, the reason for the possible aggregation that was noticed from the TEM analysis. Additionally, the stability of the purified nanoparticles dispersed in water was assessed for 7 days using the dynamic light scattering (DLS) method (Inset). The zeta‐potential values of the nanoparticles hardly changed significantly during this period. During calcination at 200°C, control over the final shape and size could be mediated by the strong adsorption of bioactive functional groups; in this case, the likely high protein content from the leaf extract could be the reason behind the positive values observed. The observed positive charge could impart greater stability in the surface charge during the incubation period.

3.2.3. FTIR Spectroscopy

FTIR analysis was used to identify the functional groups in the MO extract that participate in the reduction and stabilization of the MnO₂ nanoparticles. The spectra of the MO extract and the resulting MnO₂ NPs were found to have identical vibrational peaks, indicating the presence of the same functional groups of phytochemicals. The functional groups were recognized by comparing the observed bands with predicted values. By comparing the observed absorption peak values with standard values from data in the literature, the most notable functional groups were found. As illustrated in Figure 3, there was a coincidence of absorption peaks at 3225 cm⁻¹ for MnO₂ NPs and 3226 cm⁻¹ for the MO extract alone. This peak corresponds to the vibration of the OH group in alcohol/phenolic compounds. A peak at 2929 cm⁻¹ in the extract and 2927 cm⁻¹ in the MnO₂ NPs spectra indicates the aliphatic ─C─H stretching, whereas the appearance of strong bands at 1558, 1404, and 1081 cm⁻¹ in the extract, which reduced significantly to 1553, 1402, and 1049 cm⁻¹ in the MnO₂ NPs, was observed. These peaks indicate the ─COO (carboxylic group), ─C─N (amide group), and ─C─O─C (anhydride group), respectively, which are components of the amide bonds found in proteins [58], and hence demonstrate the high protein content in the plant extract. Furthermore, a noticeable peak in the MnO₂ NPs appeared at 591 cm^−1, which suggests Mn─O bending vibration. These bands in the FTIR spectra indicate that the compounds from the MO extract contributed to the formation of a layer that covered the MnO₂ nanoparticles [59].

FIGURE 3.

FTIR spectral analysis of MO extract and MnO₂ NPs. MO, Moringa oleifera.

3.2.4. UV–Vis Spectroscopy

Furthermore, the formation of the MnO₂ nanoparticles from the MO extract was studied using a UV–vis spectrophotometer. The UV–vis absorption spectrum of an aqueous solution of MnCl₂·4H₂O showed a single broad absorption band at 265 nm (Figure S1). However, the MnO₂ NPs showed two broad absorption peaks at 271 and 312 nm (Figure 4a), characteristic of their electronic excitation (usually around 250–380 nm). Due to its semiconductor nature, the two absorptions in the UV region have been attributed to the electronic transition from the valence band to the conduction band of the MnO₂ [60]. Unlike most metallic nanoparticles that display strong plasmonic absorption, MnO₂ NPs typically display an intrinsic absorption peak with no strong localized surface plasmon resonance. These broad peaks confirm the formation of MnO₂ NPs from the MO extract.

FIGURE 4.

(a) UV absorption and (b) XRD analysis of the MO‐synthesized MnO₂ NPs.

3.2.5. X‐Ray Diffraction

The structural characteristics and phase purity of the MnO₂ nanoparticles were investigated using XRD analysis. In Figure 4b, the diffraction pattern of MnO₂ NPs showed four dominant, well‐defined peaks with high intensities at 16.12°, 20.68°, 32.47°, and 37.54°, which were indexed to the (1 1 0), (2 0 0), (3 1 0), and (2 1 1) planes, respectively. These peaks possibly indicate a preferential growth of α‐MnO₂ nanoparticles corresponding to the standard JCPDS database (Card No.: 44‐0141) [61]. A careful comparison of the diffraction peaks showed that some peaks are relatively higher than others. The varying degrees of crystallinity observed in the diffraction pattern, with relatively smaller diffraction peaks and well‐indexed reflections, suggest highly pure nanoparticles devoid of impurities. Using the Debye–Scherrer equation at the most intense peak (1 1 0), the crystallite size was calculated to be 16.77 nm. The XRD pattern obtained is consistent with previous reports on the formation of MnO₂ nanoflowers [62] and nanowires [63] with tetragonal structural orientation. Thus, the high degree of crystallization demonstrated the formation of MnO₂ NPs from the MO extract.

3.3. Antioxidant Activity

DPPH and ABTS radical scavenging assays were used to evaluate the antioxidant activity of MnO₂ NPs. As shown in Table 3, the radical inhibitory properties of MnO₂ NPs against DPPH and ABTS demonstrated an IC₅₀ value of 9.08 ± 0.11 and 6.62 ± 0.12 µg/mL, respectively. However, when compared to the DPPH radical, the MnO₂ NPs were more effective at suppressing the ABTS radical. By comparing Vitamin C, a recognized free radical inhibitor, to the latter results, the IC₅₀ values of the latter were double that of the MnO₂ NPs at 4.11 ± 0.82 and 3.92 ± 0.25 µg/mL. It has been established that the physicochemical properties of nanoparticles, such as size and surface properties, can influence their radical scavenging activities [26]. With a smaller size, the surface area to volume ratio increases, which increases the surface area of nanoparticles. A large surface area resulting from the relatively small size of the MnO₂ NPs indicates that more active sites are available to interact with free radicals, thus leading and enhanced activity and greater antioxidant capacity. This result is consistent with earlier studies on manganese dioxide and cerium oxide nanoparticles, which demonstrated the capacity of nanoparticles to scavenge free radicals and protect the cellular system from oxidative damage [64, 65].

TABLE 3.

Inhibitory effects (IC₅₀) of Moringa oleifera extract‐synthesized MnO₂ NPs on 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH), 2,2′‐azino‐bis (3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS), human embryonic kidney (HEK 293), HepG2 cells, α‐amylase, and α‐glucosidase.

	IC50 ± SD (µg/mL)
Samples	DPPH	ABTS	HEK 293	HepG2	α‐Amylase	α‐Glucosidase
MnO2 NPs	9.08 ± 0.11	6.62 ± 0.12	68.22 ± 1.73	51.78 ± 2.05	36.58 ± 0.74	55.03 ± 1.68
Acarbose	ND	ND	ND	ND	24.54 ± 1.55	6.54 ± 0.27
Ascorbic acid	4.11 ± 0.82	3.92 ± 0.25	ND	ND	ND	ND
Doxorubicin	ND	ND	2.71 ± 0.31	8.60 ± 0.59	ND	ND

Note: Values represent the mean of three replicates given as mean ± SD.

Abbreviation: ND, not determined.

3.4. Cytotoxicity Activity

The selection of the liver hepatocellular carcinoma (HepG2) and HEK 293 cell lines for evaluating cytotoxicity is influenced by their importance in assessing the safety profiles of prospective antidiabetic agents. HepG2 cells, originating from human hepatocellular carcinoma, are well‐established as an in vitro model for examining liver metabolism, glucose regulation, and insulin signaling. As the liver is essential for glucose homeostasis and drug metabolism, assessing cytotoxicity in HepG2 cells provides crucial information regarding a compound's possible hepatic toxicity and its compatibility with metabolism in antidiabetic therapies [66]. Conversely, HEK 293 cells, which come from human kidney tissue, are representative of non‐cancerous, normal human cells often used to evaluate general cytotoxicity. Testing on HEK 293 cells helps differentiate between selective toxicity that might impact metabolically active liver cells and non‐selective toxicity that could affect other normal cell types [67]. Consequently, both HepG2 and HEK 293 cells were utilized in the cytotoxicity evaluations of the MnO₂ NPs. This will guarantee a thorough assessment of the toxicity, ensuring their safety, biocompatibility, and potential selectivity for diabetic target tissues while reducing negative effects on normal cell lines. In contrast to doxorubicin (positive control), which had IC₅₀ values of 2.71 ± 0.31 and 8.60 ± 0.59 µg/mL against HEK 293 and HepG2 cells, respectively, the MnO₂ NPs were less toxic to both HEK 293 and HepG2 cells, with IC₅₀ values of 68.22 ± 1.73 and 51.78 ± 2.05 µg/mL, as indicated in Table 3. A previous study revealed that Terminalia chebula fruit extract‐synthesized MnO₂ NPs possess anticancer properties toward breast cancer cells at IC₅₀ values of MDA‐MB‐231 (IC₅₀ = 8 µg/mL) and MCF‐7 (IC₅₀ = 10 µg/mL) [68]. Moreover, the expression of genes linked to possible neurotoxicity was altered by the 24 h treatment of neuronal (PC‐12) cells with 10 µg/mL Mn NPs [69]. Furthermore, a 9‐h exposure of N27 cells to Mn NPs led to increased ROS levels and a time–dose‐related decline in viability, demonstrating the possible anticancer mechanism of the Mn NPs [70]. However, in our investigation, after 24 h exposure, MnO₂ NPs were less toxic to HEK 293 and HepG2. This could result from the non‐toxic nature of the metal oxide MnO₂, which is essential for maintaining cellular redox equilibrium as a coenzyme component [71]. On the contrary, MO has been demonstrated in numerous studies to promote cell proliferation, particularly normal cell survival, with strong antioxidant properties [72].

3.5. Inhibition of α‑Amylase and α‑Glucosidase Enzymes

The synthesized MnO₂ NPs were evaluated for their inhibitory effects on α‐amylase and α‐glucosidase. From Table 3, the MnO₂ NPs were an effective α‐amylase inhibitor, with an IC₅₀ value of 36.58 ± 0.74 µg/mL for α‐amylase and 55.03 ± 1.68 µg/mL for α‐glucosidase. When acarbose, the standard reference drug, was used to compare the activity of MnO₂ NPs, it showed remarkable inhibition against both α‐amylase (24.54 ± 1.55 µg/mL) and α‐glucosidase (6.54 ± 0.27 µg/mL). From these findings, the MnO₂ NPs appear to be better candidates for effective α‐amylase and α‐glucosidase inhibition. Several metal–oxide nanoparticles synthesized from plant extracts have been investigated for the inhibition of α‐amylase and α‐glucosidase. For example, nickel oxide nanoparticles synthesized using the leaf extract of Lagerstroemia speciosa were found to inhibit α‐amylase enzyme at an IC₅₀ value of 21.03 µg/mL [73]. Similarly, cobalt oxide and magnesium oxide nanoparticles synthesized from aqueous leaf extract of Hibiscus rosa sinensis were reported to show considerable α‐amylase and α‐glucosidase enzyme inhibition properties [74]. At their highest concentration, cobalt oxide nanoparticles inhibited α‐amylase and α‐glucosidase enzymes by IC₅₀ values of 298 and 357 µg/mL, whereas magnesium oxide inhibited α‐amylase and α‐glucosidase enzymes by IC₅₀ values of 327 mg/mL and >400 µg/mL, respectively. These results create opportunities for advanced research into the use of medicinal plants to reduce glucose absorption. To our knowledge, no study has investigated how MnO₂ NPs modulate α‐amylase and α‐glucosidase enzymes; thus, this work is the first to document this activity.

3.6. Molecular Docking Study

Additionally, molecular docking was utilized to uncover the possible mechanisms behind the antidiabetic effects by forecasting how the bioactive compounds in the extract interact with nanoparticles (NPs) in relation to crucial diabetic target enzymes like α‐amylase and α‐glucosidase. Table 4 presents the predicted binding affinities and inhibition constants (K _i) from molecular docking studies for acarbose, glucomoringin, and MnO₂ NPs against α‐amylase and α‐glucosidase. For α‐amylase, MnO₂ NPs exhibit the strongest binding affinity (−6.10 kcal/mol) and lowest K _i (33.78 µM), suggesting the highest inhibitory potential, followed by glucomoringin (−4.94 kcal/mol, 0.24 mM) and then acarbose (−4.30 kcal/mol, 0.70 mM). Against α‐glucosidase, MnO₂ NPs also show the strongest affinity (−7.32 kcal/mol) and lowest K _i (4.31 µM). In contrast, glucomoringin displays a weak affinity (−1.67 kcal/mol) and a high Ki (59.69 mM) for α‐glucosidase, whereas acarbose shows a moderate affinity (−3.03 kcal/mol) and a K _i (6.01 mM). Overall, MnO₂ NPs demonstrate the most promising inhibitory activity against both enzymes in these in silico analyses. In silico molecular docking studies screening for α‐glucosidase and α‐amylase inhibitors among natural compounds have revealed that certain bioactive molecules, such as curcumin, exhibit superior inhibitory activity compared to the conventional drug acarbose [75].

TABLE 4.

Binding affinities and inhibition constants (K _i) from AutoDock for acarbose, glucomoringin, and MnO₂ NPs.

	α‐Amylase (1B2Y)		α‐Glucosidase (5NN8)
Ligand	Affinity (kcal/mol)	K i	Affinity (kcal/mol)	K i
Acarbose	−4.30	0.70 mM	−3.03	6.01 mM
Glucomoringin	−4.94	0.24 mM	−1.67	59.69 mM
MnO2 NPs	−6.10	33.78 µM	−7.32	4.31 µM

Acarbose exhibits distinct binding modes with α‐amylase and α‐glucosidase (Figure 5). In α‐amylase, it forms conventional hydrogen bonds with Asp197, Asp300, and His299, a carbon–hydrogen bond with Ile148, and an additional hydrogen bond with Tyr151. In α‐glucosidase, acarbose engages in hydrogen bonds with Asp282 and Leu677, alongside π‐alkyl interactions with Phe649 and Trp376, and a further hydrogen bond with Arg411. These differences in binding interactions—ranging from polar hydrogen bonds to hydrophobic π‐alkyl contacts—explain acarbose's inhibitory effects on both enzymes through tailored active‐site recognition. Glucomoringin interacts with α‐glucosidase primarily via hydrogen bonds involving Asp282 and Ala284, along with carbon‐hydrogen bonds to Arg281 and Ala555, and π‐alkyl interactions with Leu283 and Val548. With α‐amylase, it forms an extensive hydrogen bond network with Asp197, Asp300, His299, Glu233, Lys200, and Glu240, supplemented by carbon–hydrogen bonds (Ala198, Gly306) and alkyl interactions (His201, Leu162). These interactions enhance its binding affinity, demonstrating adaptability to different enzymatic environments.

FIGURE 5.

Three‐dimensional representation of the binding interactions between (a) acarbose–amylase, (b) acarbose–glucosidase, (c) glucomoringin–amylase, (d) glucomoringin–glucosidase, (e) MnO₂ NPs–amylase, and (f) MnO₂ NPs–glucosidase.

The MnO₂ NPs engage in multiple stabilizing interactions with the active sites of α‐amylase and glucosidase, primarily mediated through hydrogen bonding, metal coordination, and weak non‐covalent forces. In α‐amylase, the oxygen atoms of the MnO₂ NPs function as hydrogen bond acceptors with key residues, including Tyr151, Asn152, Lys200, and Gly308. Simultaneously, these oxygen atoms also act as hydrogen bond donors, forming interactions with Glu240, Gly306, Glu149, Asn150, Ile235, Gly238, Gly239, and Leu237. Additionally, a carbon–hydrogen (C–H) interaction is observed between the MnO₂ NPs and the α‐carbon (CA) of Asn150, whereas π‐donor hydrogen bonds further stabilize the complex through interactions with the aromatic ring of Tyr151 (twice). Notably, direct metal coordination occurs between manganese ions (Mn) in the NPs and the backbone oxygen atoms of Gly238 and Glu240, reinforcing the binding affinity. In the case of glucosidase, the interaction network is similarly dominated by hydrogen bonds, where MnO O1 atoms engage with Arg281, Ala284, Tyr292, Arg600, Trp618, and Asp616. A distinct metal–acceptor interaction is observed between an Mn ion and the carboxylate oxygen of Asp282. Furthermore, a π‐donor hydrogen bond suggests additional stabilization via the backbone amide hydrogen (HN) of Phe525, possibly facilitated by the aromatic ring's electron density.

4. Conclusions

In this study, GC–MS analysis of the volatile phytoconstituents in MO leaves provided valuable insights into the plant's potential nanoparticle formation and biological activities. Phytochemicals isolated from the MO extract, such as benzoic acid and hexadecanoic acid, likely acted as stabilizing and reducing agents during the MnO₂ NPs formation. The MO‐synthesized MnO₂ NPs were characterized using various solid‐state techniques and indicated successful synthesis. The results from radical scavenging showed that MnO₂ NPs exhibited significant antioxidant activity, as evidenced by DPPH and ABTS assays. Additionally, the MnO₂ NPs showed minimal cytotoxic effects on HepG2 and HEK 293 cells, as highlighted by their IC₅₀ dosage. Notably, moderate inhibitory activity against α‐amylase and α‐glucosidase enzymes was observed for the MnO₂ NPs when compared to the standard control drug, which are key targets in diabetes management. Docking studies indicated that the MnO₂ NPs can inhibit these enzymes by forming non‐covalent interactions, including hydrophobic contacts, π–π stacking, electrostatic interactions, and hydrogen bonds with critical amino acids in their active sites. These interactions play a role in determining the binding affinity and specificity of the compounds, thus enhancing their possible inhibitory effects and mechanisms of action related to diabetes management. This research highlights the potential of MO as a sustainable source for producing trace metal oxide nanoparticles, which could be valuable in medical applications, particularly in the treatment of diabetes and related conditions.

Author Contributions

Selokela Joseph Mahlo, Adewale Odunayo Oladipo, and Garland Kgosi More: conceptualization, methodology, software, data curation, visualization, investigation, writing – original draft preparation. Mpho Phehello Ngoepe and Yvan Anderson Ngandjui Tchangoue: methodology, software, data curation, visualization, investigation. Garland Kgosi More and Sogolo Lucky Lebelo: supervision, validation. Selokela Joseph Mahlo, Mpho Phehello Ngoepe, Yvan Anderson Ngandjui Tchangoue, Adewale Odunayo Oladipo, Titus Alfred Makudali Msagati, Garland Kgosi More, and Sogolo Lucky Lebelo: writing – reviewing and editing.

Funding

The authors have nothing to report.

Ethics Statement

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting File 1: cbdv70935‐sup‐0001‐SuppMat.docx

Data Availability Statement

No datasets were generated or analyzed during the current study.