Abstract
Background: Nephrolepis exaltata (sword fern) possesses a considerable
amount of phytochemicals and different biological activities. The
current study investigates the anti-biofilm potential of greenly
synthesized bimetallic nanoparticles of Nephrolepis exaltata leaf
methanol extract (NEME-MnO[2]-MgO BNPs). Methods: The NEME was
subjected to UPLC/MS analysis, followed by characterization of its NPs
by size, zeta potential, FTIR, entrapment efficiency, and release.
Then, antioxidant, antimicrobial and antibiofilm assays were employed,
followed by in silico studies. Results: The UPLC/MS analysis of NEME
led to the tentative identification of 27 metabolites, mostly
phenolics. The MnO[2]-MgO BNPs presented a uniform size and
distribution and exhibited IC[50] values of 350 and 215.6 μg/mL, in the
DPPH and ABTS assays, respectively. Moreover, the NPs exhibited
antimicrobial and anti-biofilm efficacies against Pseudomonas
aeruginosa, Klebsiella pneumonia (ATCC-9633), Staphylococcus aureus
(ATCC-6538), Escherichia coli, Bacillus cereus, and C. albicans, with
MIC values of 250–500 μg/mL. The MnO[2]-MgO BNPs inhibited Candida
albicans biofilms with a % inhibition of 66.83 ± 2.45% at 1/2 MIC. The
network pharmacology highlighted epigallocatechin and hyperoside to be
the major compounds responsible for the anti-biofilm potential. The
ASKCOS facilitated the prediction of the redox transformations that
occurred in the green synthesis, while the docking analysis revealed
enhanced binding affinities of the oxidized forms of both compounds
towards the outer membrane porin OprD of P. aeruginosa, with binding
scores of −4.6547 and −5.7701 kcal/mol., respectively. Conclusions: The
greenly synthesized Nephrolepis exaltata bimetallic nanoparticles may
provide a promising, eco-friendly, and sustainable source for
antimicrobial agents of natural origin with potential biofilm
inhibition.
Keywords: eco-friendly, Nephrolepis exaltata, UPLC-ESI/LC/MS,
bimetallic nanoparticles, anti-biofilm, network pharmacology
1. Introduction
Ferns are crucial to the preservation of moisture in forests because
their roots absorb water and progressively disperse it throughout the
soil and atmosphere. This encourages the growth of microflora and
substrate microfauna, both of which are critical to maintaining the
ecological balance of the ecosystem. They directly impact the
microclimate in many places since they have been used as ornaments,
tools for religious rites and entertainment, tools for maintaining the
fauna in various locations, and food, as well as refuge for a variety
of species [[34]1]. In addition to their aesthetic appeal, ferns are
crucial for nutrition and economy. Because they endanger biodiversity,
certain fern species are viewed as intruders and handled like diseases.
Some species, mostly arborescent ones, are excellent examples of how
ferns interact with other organisms because their rachises may be
surrounded by a variety of other plant species, including bryophytes,
pteridophytes, and orchidaceous ones, as well as small animals like
ants and microscopic and macroscopic fungi [[35]1].
Thirty taxa of ferns make up the genus Nephrolepis (Nephrolepidaceae),
which is extensively dispersed, primarily in tropical regions of Asia,
Africa, and South America. One of the common decorative fern species,
Nephrolepis exaltata (L.) Schott, grows well in cool and humid
environments and reproduces quickly. This plant is sold as “sword fern,
Boston Fern, or Bostoniensis” and is mostly grown for horticulture
[[36]2]. Nephrolepis exaltata is the least researched of the 30 species
in the genus Nephrolepis that are therapeutically beneficial. The
division Tracheophyta includes the genus Nephrolepis (Nephros, kidney;
lepis, the indusium kidney-shaped and scale-like), which is further
divided into the subdivision Polypodiophytina, class Polypodiopsida,
and order Polypodiales.
Nephrolepis exaltata, commonly known as the sword fern, is an
ornamental plant in most of India and the world. N. exaltata contains
alkaloids, flavonoids, carbohydrates, saponins, phenols, and sterols
[[37]3]. The volatile components identified from N. exaltata have
exhibited potent antimicrobial activities against a number of selected
microorganisms, with some promising cytotoxicity potential on lung,
breast, and colon carcinoma cells [[38]4].
Biofilms, established by some microorganisms, are complex communities
that are capped with exopolysaccharide (EPS) layers [[39]5]. These
bacterial communities can interact with one another and stick to
surfaces, becoming stronger and more effective in navigating the harsh
environment in which they develop [[40]6]. It is important to remember
that once a biofilm forms, the bacteria are shielded from immune
defense mechanisms and physical or chemical therapeutic strategies and
become more violently resistant. As more resistant microbial strains
have emerged during the past 20 years, numerous determinants of
resistance have been identified [[41]7].
Nanotechnology has gained global attention due to the unique
characteristics of nanoparticles (NPs), including variant shapes, small
sizes, and high surface areas, making NPs suitable for a wide range of
medical applications [[42]8]. Conventional synthesizing approaches for
NPs are generally time-consuming, expensive, need specific precursors
and definite temperatures, and create significant chemical waste
[[43]9]. In contrast, green synthesis utilizes renewable organic
extracts which eliminate the need for toxic chemicals and gives rise to
waste production. By employing natural products rich with secondary
metabolites, the green approach provides a sustainable alternative for
NP production, aligning with recent sustainability concerns [[44]10].
To the best of our knowledge, Nephrolepis exaltata has been rarely
investigated in combination with nanotechnology. Greenly synthesized
iron oxide NPs of N. exaltata have been previously investigated for
antiplasmodial and cytotoxic effects [[45]11]. Additionally, greenly
synthesized zinc oxide NPs of N. exaltata have been previously studied
for antiplatelet and cytotoxic potential [[46]12]. Hence, the current
study is considered unique and comprehensive, employing green
approaches in manufacturing bimetallic NPs of N. exaltata, offering an
eco-friendly, sustainable, and highly potent formulation attaining
antioxidant and antimicrobial potential.
Collectively, our study aims to define the phytochemical profile of the
methanol extract of Nephrolepis exaltata leaves via UPLC/MS techniques,
as well as evaluate its antioxidant, antimicrobial, and biofilm
potential using greenly synthesized MnO[2]-MgO biometallic
nanoparticles ([47]Figure 1).
Figure 1.
[48]Figure 1
[49]Open in a new tab
Graphical representation of the phytochemical and antimicrobial studies
on Nephrolepis exaltata.
2. Results and Discussion
2.1. UPLC/MS Analysis for the Methanol Leaves Extract of Nephrolepis exaltata
Twenty-seven metabolites were detected and tentatively identified from
the methanol extract of N. exaltata leaves, expressed in both positive
and negative modes ([50]Figure 2A,B). The tentatively identified
metabolites are listed in [51]Table 1 according to their retention
time, and their m/z values, together with molecular formula, chemical
class, and area %, are also included. The most abundant classes were
the flavonoids, phenolic acids, tannins, and triterpenes, in addition
to other phytoconstituents, viz. anthocyanins, iridoids, and fatty
acids ([52]Figure 2C). The identification was based on comparison of
the m/z values with the relevant literature. The identified classes of
phytoconstituents are summarized in [53]Figure 3.
Figure 2.
[54]Figure 2
[55]Open in a new tab
(A) UPLC-ESI/LC/MS positive mode chromatogram. (B) UPLC-ESI/LC/MS
negative mode chromatogram of Nephrolepis exaltata methanol extract.
(C) Pie chart showing the % of components identified via UPLC-ESI/LC/MS
analysis.
Table 1.
The tentatively identified components from Nephrolepis exaltata (Fujar)
through UPLC/MS.
No. Component Molecular Formula Chemical Class R[t] (min.) [M − H]^−
m/z [M + H]^+
m/z Area % Ref.
1 Tetrahydroxy trimethoxy dihydroxyflavone C[19]H[18]O[10] Flavonoid
0.81 377 381 12.03
(18.13) [[56]13,[57]14]
2 Kaempferol-di-hexoside C[42]H[45]O[22] Flavonoid 6.04 609 - 4.75
[[58]15]
3 Kaempferol-hexoside C[21]H[20]O[11] Flavonoid 6.64 447 - 2.82
[[59]15]
4 Afzelin * C[21]H[20]O[10] Flavonoid 7.08 431 - 2.23 [[60]2]
5 Quercetin-hexoside C[21]H[20]O[12] Flavonoid 7.65 463 - 8.15 [[61]15]
6 Kaempferol-hexuronoide C[27]H[30]O[16] Flavonoid 8.05 459 - 0.58
[[62]15]
7 Unidentified - - 8.61 - 162 or 194 or 217 6.17 -
8 Ethyl palmitate C[18]H[36]O[2] Fatty acid 11.52 - 285 2.04 [[63]16]
9 Unidentified - - 14.35 - 277 or 353 or 393 0.75 -
10 9-oxo-Octadecadienoic acid C[18]H[32]O[3] Fatty acid 14.41 293 -
20.80 [[64]17,[65]18]
11 Myricetin C[15]H[10]O[8] Flavonoid 15.48 - 319 0.69 [[66]16]
12 Myricetin-pentosyl pentoside C[27]H[30]O[16] Flavonoid 15.96 609 611
7.69
(1.49) [[67]16]
13 Chlorogenic acid C[16]H[18]O[9] Phenolic acid 16.44 353 355 5.49
(6.40) [[68]13,[69]14,[70]19]
14 Trihydroxy germacrenolide - Sesquiterpene lactone 16.94 - 285 2.75
[[71]16]
15 p-Coumaroyl-hexoside C[15]H[14]N[2]O[3] Phenolic acid 17.36 325 -
11.43 [[72]16]
16 Caffeic acid hexoside C[9]H[8]O[4] Phenolic acid 19.13 341 347 6.22
(2.75) [[73]14,[74]20]
17 Carnosic acid C[20]H[28]O[4] Phenolic acid 19.99 - 333 2.49
[[75]14,[76]21]
18 Trigalloyl hexoside C[27]H[24]O[18] Tannin 20.99 - 637 1.10 [[77]22]
19 Malvidin C[17]H[15]O[7]^+ Anthocyanin 21.24 - 331 0.61 [[78]23]
20 Glycitein-hexouronide C[22]H[20]O[11] Flavonoid 22.73 459 461 0.29
(17.92) [[79]24,[80]25]
21 Benzoyl caffeic acid rutinoside - Phenolic acid 26.00 591 - 0.29
[[81]18]
22 Unidentified - - 27.62 - 613 2.61 -
23 Unidentified - - 27.84 - 647 or 613 2.41 -
24 Lutein (hydroxycarotenoid) C[40]H[56]O[2] Carotenoid 28.05 - 568
2.84 [[82]23]
25 Hyperoside C[21]H[20]O[12] Flavonoid 28.28 - 465 3.67 [[83]19]
26 Syringaresinol−acetyl hexose C[30]H[37]O[14] Iridoid 28.41 621 757
1.60
(2.85) [[84]26]
27 Unidentified - - 28.89 - 445 4.48 -
28 Galloyl-HHDP C[35]H[16]O[21] Tannin 29.28 481 - 0.56 [[85]27]
29 Methoxy ursolic acid C[31]H[51]O[4] Triterpene 29.54 - 487 2.83
[[86]28]
30 Oleanolic acid * C[30]H[48]O[3] Triterpene 29.71 457 - 2.78 [[87]29]
31 Methoxy benzoic acid (p-Anisic acid) C[8]H[8]O[3] Phenolic acid
30.07 313 315 1.05
(2.28) [[88]16]
32 Caffeoyl quinic acid dimer C[32]H[36]O[18] Phenolic acid 30.72 707 -
2.41 [[89]30]
33 Unidentified - - 31.11 265 - 6.04
-
34 Epigallocatechin * C[15]H[14]O[7] Tannin 31.34 305 307 0.76
(2.41) [[90]2]
% identification
−ve mode 91.93%
+ve mode 55.12%
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* For compounds previously reported from the genus Nephrolepis. Area %
between brackets is for the compounds in ESI positive mode.
Figure 3.
[92]Figure 3
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Structures of some metabolites identified by UPLC-ESI/LC/MS.
Flavonoids represented the most predominant class of identified
components, with nine tentatively identified compounds, where
kaempferol and myricetin were the common aglycones. Compound 1
presented a deprotonated peak at m/z 377 (12.03%) and at m/z 381
(18.13%), and it appeared to be the flavone named tetrahydroxy
trimethoxy dihydroxyflavone [[94]13,[95]14]. Compounds 2, 3, and 6 were
detected at m/z 609, 447, and 459, respectively, and they were
tentatively defined as kaempferol-di-hexoside [[96]15],
kaempferol-hexoside [[97]15], and kaempferol-hexuronoide [[98]15]
([99]Table 1). Similarly, myricetin aglycone (m/z 319, +ve mode)
[[100]16] and its glycoside, myricetin-pentosyl pentoside [m/z
609(611)], [[101]16] were tentatively identified. A famous flavonoid,
previously reported from genus Nephrolepis, appeared in the ESI
negative ion mode at m/z 431 and was then defined as afzelin [[102]2].
In addition to that, one major peak was detected at m/z 463 with an
area % of 8.15% which was tentatively defined as quercetin-hexoside
[[103]15]. A deprotonated molecular ion peak was detected at [M − H]^−
m/z 459 and at [M + H]^+ m/z 461 and it was tentatively assigned to
glycitein-hexouronide [[104]24,[105]25].
Phenolic acids represented the second most abundant class of
phytoconstituents, where seven components were tentatively identified.
One major peak was detected at m/z 353 in ESI negative mode (5.49%) and
at m/z 355 in ESI positive mode (6.40%) which was defined as caffeoyl
quinic acid or chlorogenic acid [[106]13,[107]14,[108]19,[109]31].
Further, a chlorogenic acid dimer presented a deprotonated peak at m/z
707 (2.41%), which was defined as caffeoyl quinic acid dimer
[[110]30,[111]32]. Other caffeic acid derivatives were also traced,
viz. caffeic acid hexoside at [M − H]^− m/z 341 (6.22%) and at [M +
H]^+ m/z 347 (2.75%) [[112]14,[113]20]. Moreover, a deprotonated peak
was traced at m/z 591 in ESI negative ion mode which was tentatively
assigned to benzoyl caffeic acid rutinoside [[114]18]. Compound 15 was
detected at m/z 325 (11.43%) and was identified as p-coumaroyl-hexoside
[[115]16,[116]33]. Two simple phenolic acids presented their peaks at
m/z 333 (positive mode) and at m/z 313 (315), which were tentatively
named as carnosic acid [[117]14,[118]21] and methoxy benzoic acid
(p-anisic acid) [[119]16], respectively.
Two fatty acid peaks were defined from the plant extract. An abundant
peak (20.80%) appeared at m/z 293 in ESI negative mode which was
identified as 9-oxo-octadecadienoic acid [[120]17,[121]18]. Moreover, a
deprotonated peak was detected at [M + H]^+ m/z 285 and it belonged to
the fatty acid ester, ethyl palmitate (2.04%) [[122]16].
Interestingly, three tannins were tentatively identified, where one
tannin peak was traced at m/z 637 (+ve mode), which was defined as
trigalloyl hexoside [[123]22]. Compound 28 presented a deprotonated
peak at m/z 481 (1.10%), which was identified as galloyl-HHDP
[[124]27]. In addition, compound 34 had a deprotonated molecular ion
peak at [M − H]^− m/z 305 and [M + H]^+ m/z 307, which lead to its
identification as epigallocatechin, which was also documented before
from the genus Nephrolepis. Oleanolic acid, the famous triterpene which
was reported from the genus Nephrolepis, showed a deprotonated peak at
m/z 457, C[30]H[48]O[3] [[125]29]. Further, another peak was traced at
m/z 487 for methoxy ursolic acid ([126]Table 1) [[127]28].
In our current study, the NEME was phytochemically analyzed through
UPLC/MS, which lead to the tentative identification and quantification
of 27 metabolites, most of which are flavonoids, phenolic acids,
tannins, triterpenes, and other classes. Upon reviewing literature on
genus Nephrolepis, trace reports were detected regarding the
phytochemical analysis and isolation of phytoconstituents, and they
were summarized as follows. Different phytoconstituents were isolated
from the leaves of Nephrolepis exaltata, including phloretic acid,
dehydrovomifoliol, dehydrololiolide, quercitrin, kaempferol, afzelin,
quercetin, luteolin, 3-O-methylquercetin, demethoxymatteucinol,
methoxygaertneroside, (2S)-5,7,3′,5′-tetrahydroxyflavanone,
epigallocatechin, lanicepside A, pinoresinol 4′-O-β-D-glucopyranoside,
and glochidiobioside [[128]2]. Moreover, zinc oxide nanoparticles
(ZnO-NPs) synthesized from an aqueous extract of Nephrolepis exaltata
demonstrated potential antiplatelet activity by inhibiting the platelet
aggregation induced by platelet activation factor (PAF) and arachidonic
acid (AA). The results showed that synthesized ZnO-NPs were more
effective in inhibiting platelet aggregation induced by AA with IC50
(56% and 10 μg/mL) and PAF (63% and 10 μg/mL), respectively. The
cytotoxicity of synthesized nanoparticles revealed that cell viability
decreased and the IC50 was found to be 46.7% at a concentration of 75
μg/mL [[129]12]. In another study, the aerial parts of Nephrolepis
biserrata and Nephrolepis cordifolia were fractionated in different
solvents. These fractions were concentrated to obtain a powder and were
tested against nine bacterial and three fungal strains according to the
disc diffusion method. The water and methanol fractions were active
against most of the tested bacterial and fungal strains, and some of
these were more effective than the controls tested [[130]34].
The fresh leaves of NEME revealed the presence of alkaloids,
flavonoids, tannins, saponins, phlobatanins, steroids, anthraquinone,
and cyanogenic gylcosides. The proximate composition showed a
considerable amount of crude fiber, crude protein, ash content,
carbohydrate, and energy content. The results of the mineral element
content revealed that the fern contained a high quantity of potassium,
phosphorus, calcium, magnesium, and iron and a moderate amount of
manganese and zinc. Anti-nutrient analysis showed low concentrations of
cyanide (0.06 ± 0.01 mg/100 g), phytate (0.25 ± 0.01 mg/100 g), and
oxalate (0.69 ± 0.01 g/100 g) [[131]35].
2.2. MnO[2]-MgO BNPs Biosynthesis Using NEME
In the current study, NEME was utilized to create MnO[2]-MgO BNPs from
Mn acetate tetra hydrate and Mg nitrate hexahydrate, all stabilized in
a colloidal condition, with the solution’s color changed to black
[[132]36]. The phytochemical composition of NEME plays a critical role
in the biosynthesis of the NPs, due to presence of active constituents
which contribute to metal ion reduction. This process occurs through
tautomeric shifts, where enol forms transition into keto forms,
releasing reactive hydrogen atoms that aid in nanoparticle formation
[[133]11,[134]37]. This is consistent with a previous study which
reported the successful formulation of zinc oxide nanoparticles using
the aqueous extract of Nephrolepis exaltata as both a reducing and
capping agent, via using zinc acetate dihydrate
(Zn(CH[3]CO[2])[2]·2H[2]O) as the zinc precursor [[135]12].
Additionally, The iron oxide nanoparticles (FeO NPs) from NEME were
also formed and showed potent antiplasmodial activity with an MIC of 62
± 1.3 at 25 µg/mL against Plasmodium parasites [[136]11].
2.3. Characterization of the Biosynthesized MnO[2]-MgO BNPs
The potential of NEME to biosynthesize MnO[2]-MgO BNPs was visually
assessed via the color change from yellow to black. This color change
indicated the activation of SPR in the biogenic MnO[2]-MgO BNPs,
producing a black color that was recognized as the characteristic
spectroscopic signature for their successful formation. Based on UV-Vis
investigations, the experimental peak conducting the OD (1.3; diluted
twice) of the MnO[2]-MgO BNPs was observed at 350 nm ([137]Figure 4).
On the other hand, the peak of the NEE disappeared from the UV-Vis
spectrum, which further confirms the optimal BNP formation.
Figure 4.
[138]Figure 4
[139]Open in a new tab
UV-Vis spectroscopy of MnO[2]-MgO BNPs and NEME.
Generally, the structure, dielectric characteristics, morphological
surfaces, intensity, and size of any generated nanoparticles are
frequently critical factors that greatly affect the SPR. The obtained
results were matched with the reported ones about the absorption peaks
of MnO[2] nanoparticles, which generally appear at 350–400 nm,
corresponding to charge transfer transitions between Mn^3+ and Mn^4+
states [[140]38]. Alwin David and Ram Kumar [[141]39] reported that the
UV–visible spectrum of biosynthesized MnO[2] nanoparticles exhibited an
absorption maximum at 371 nm, confirming the characteristic surface
plasmon resonance of MnO[2] NPs. Farhan and Mohammed [[142]40] reported
that the UV–visible spectrum of MnO[2] nanoparticles exhibited a broad
absorption band with two characteristic peaks at approximately 320 nm,
indicating the successful formation of MnO[2] NPs.
Additionally, Faisal et al. [[143]41] investigated the green synthesis
of MnO[2] nanoparticles using Fagonia cretica and reported a distinct
absorption peak at 410 nm with an absorbance of 2.25 a.u., confirming
the successful formation of the nanoparticles.
Similarly, MgO nanoparticles exhibit a strong absorption band appeared
in the 200–300 nm range, which is usually associated with excitonic
transitions and oxygen vacancies [[144]42]. Hassan et al. [[145]43]
reported that magnesium oxide nanoparticles synthesized via Rhizopus
oryzae-mediated green synthesis exhibited a surface plasmon resonance
(SPR) peak at 282 nm, confirming the formation of MgO NPs. Abdallah et
al. [[146]44] and Nguyen et al. [[147]45] reported that the maximum
absorption peaks of MgO nanoparticles synthesized using Rosmarinus
officinalis L. and Tecoma stans (L.) appeared at 250 nm and 281 nm,
respectively. The presence of both characteristic peaks in the
UV–visible spectra confirms the formation of MnO[2]-MgO bimetallic
nanoparticles. Additionally, the peak shifts appearing as broadening in
the UV spectrum indicate NP interactions and stabilization by plant
bioactive constituents during the synthesis [[148]46].
The TEM image presents the morphology of the MnO[2]-MgO BNPs, where the
nanoparticles exhibited a heterogeneous distribution with varying
shapes, including quasi-spherical and irregular shapes, with the
presence of a notable agglomeration, likely due to interparticle
interactions. The scale bar of 100 nm confirms the nanoscale nature of
the synthesized material, with sizes varying between 20 and 80 nm, as
depicted in the TEM image ([149]Figure 5A). These variations in shape
are often attributed to differences in nucleation and growth kinetics
during the synthesis, which are affected by the plant extract’s
bioactive constituents and reaction conditions. The presence of
agglomeration suggests that while the plant-derived reducing and
stabilizing constituents helped in the NP formation, their capping
force might not have been sufficient to completely prevent
interparticle interactions [[150]47]. In the MnO[2]-MgO BNPs
biosynthesized by the NEE, the particle size distribution characterized
by the DLS approach was found to be between 50 and 90 nm, with an
average size of 70 nm as determined on a log-scale intensity plot
([151]Figure 5B). Differences between TEM and DLS are frequently
reported due to their respective measurement principles, where DLS
reflects hydrodynamic diameter and is often larger than the physical
size observed by TEM [[152]48]. Since PDI values exceeding 0.7 express
polydispersity particle diffusion, our results showed a PDI value of
0.571 [[153]49]. Collectively, the results confirm that the
biosynthesized MnO[2]-MgO BNPs exhibit a uniform and homogeneous size
distribution.
Figure 5.
[154]Figure 5
[155]Open in a new tab
Investigation of (A) TEM and (B) DLS images of MnO[2]-MgO BNPs.
The FTIR spectrum of MnO[2]-MgO BNPs of NEME ([156]Figure 6A) reveals
distinct absorption bands which confirm the presence of functional
groups derived from the extract, all of which play a crucial role in
the metal oxide formation. The broad absorption band is attributed to
O-H and N-H stretching vibrations, signifying the presence of OH and NH
from the plant bioactive constituents. These functional groups suggest
the involvement of flavonoids, tannins, and proteins in reducing and
stabilizing MnO[2]-MgO BNPs [[157]50]. The FTIR results and previous
studies highlight the effectiveness of plant-mediated (green) synthesis
in producing stable and functional metal oxide NPs with potential
applications in agriculture and biomedicine [[158]51,[159]52].
Figure 6.
[160]Figure 6
[161]Open in a new tab
(A) FTIR of MnO[2]-MgO BNPs synthesized from Nephrolepis exaltata
extract; and (B) XRD of MnO[2]-MgO BNPs.
The XRD diffractograms of the synthesized MnO[2]-MgO BNPs confirm their
crystalline nature through distinct diffraction peaks corresponding to
various lattice planes ([162]Figure 6B). The observed diffraction peaks
at 2θ values of 28.9°, 37.9°, 42.5°, 43.3°, 49.9°, 56.5°, 64.99°,
74.5°, and 78.3° are indexed to the respective lattice planes (310),
(111), (301), (220), (411), (600), (220), (311), and (222). These
reflections are aligned with the standard crystallographic data for MgO
and MnO[2], indicating the successful formation of the BNPs. The peaks
at 37.9°, 43.3°, 64.99°, 74.5°, and 78.3° correspond to the Bragg’s
reflection planes (111), (220), (220), (311), and (222), which are
characteristic for the FCC lattice structure of MgO, suggesting a
well-defined crystalline phase [[163]53]. The combination of structural
confirmation through XRD and the FTIR results, reinforces the potential
of MnO[2]-MgO BNPs as functional nanomaterials characterized by
enhanced stability and reactivity. The diffraction peaks at 28.9° and
42.5° can be specifically attributed to MnO[2], which aligns with the
tetragonal and orthorhombic phases of manganese dioxide, confirming its
presence within the synthesized BNPs [[164]54].
The SEM image ([165]Figure 7A) of the MnO[2]–MgO BNPs shows a
heterogeneous morphology characterized by agglomerated structures. The
BNPs appear as irregularly shaped clusters, with certain areas
exhibiting well-defined, plate-like crystalline formations. These
aggregated structures are likely the result of nanoparticle clustering
during the drying and preparation process for SEM analysis. On the
other hand, the EDX analysis ([166]Figure 7B) confirms the elemental
composition of the NEE-synthesized nanostructures. The spectrum
displays characteristic peaks corresponding to Mn, Mg, O, and C, which
reveals the successful formation of MnO[2]-MgO BNPs. The weight %
analysis shows that Mn (46.7 wt. %) and Mg (23.5 wt. %) are the
predominant elements. The observed morphology aligns with the reported
data on the biosynthesized metal oxide NPs, where plant extracts
influence NPs’ shape and stabilization. The presence of both aggregated
and structured NPs indicates that while the synthesis approach
effectively produces BNPs, further optimization such as surfactant
assisted synthesis and/or ultrasonication could enhance dispersion and
diminish particle agglomeration [[167]55].
Figure 7.
[168]Figure 7
[169]Open in a new tab
(A) SEM micrograph (scale bar = 4 µm, magnification = 40,000×) and (B)
EDX spectrum showing the elemental composition of MnO–MgO BNPs
biosynthesized using Nephrolepis exaltata extract.
2.4. The In Vitro Antimicrobial Assay
[170]Table 2 summarizes the diameter of inhibition zones (in mm) for
various microbial strains when exposed to Nephrolepis exaltata extract,
magnesium nanoparticles, manganese nanoparticles, and MnO[2]-MgO BNPs,
with the results compared to standard antimicrobials
(chloramphenicol/clotrimazole). This agar well diffusion assay, a
widely accepted method, measures antimicrobial potency based on the
size of the clear zone where microbial growth is inhibited around the
tested substance. The MnO[2]-MgO BNPs were active against both
Gram-positive and Gram-negative bacteria, as well as against C.
albicans with different inhibition zone diameters, as mentioned in
[171]Table 2 and [172]Figure 8.
Table 2.
Antimicrobial activity of Nephrolepis exaltata extract, Mn
nanoparticles, Mg nanoparticles, and MnO[2]-MgO BNPs.
Microbial Strain Diameter of Inhibition Zone (mm)
Nephrolepis exaltata
Extract Magnesium Nanoparticle Manganese Nanoparticle MnO[2]-MgO BNPs
Chloramphenicol/
Clotrimazole
Pseudomonas aeruginosa 16 ± 0.5 11.8 ± 0.4 12 ± 0.5 26 ± 0.5 15.3 ± 0.3
Klebsiella pneumonia (ATCC-9633) 15 ± 0.5 17.1 ± 0.4 16 ± 0.5 22.6 ±
0.3 24.5 ± 0.2
Staphylococcus aureus (ATCC-6538) 15.3 ± 0.3 16 ± 0.5 14.6 ± 0.3 19.3 ±
0.8 19 ± 0.5
Escherichia coli 0 14.6 ± 0.3 12.1 ± 0.4 17 ± 0.5 21.3 ± 0.6
Bacillus cereus 21 ± 0.5 17.5 ± 0.2 22.6 ± 0.3 16 ± 0.5 25.6 ± 0.3
Candida albicans (ATCC-10231) 0 12.6 ± 0.3 0 13.3 ± 0.3 20 ± 0.5
[173]Open in a new tab
Figure 8.
[174]Figure 8
[175]Open in a new tab
Antimicrobial activity of E, NEME; Mg, Mg nanoparticles; Mn, Mn
nanoparticles; and C, MnO[2]-MgO BNPs against Pseudomonas aeruginosa,
Klebsiella pneumonia (ATCC-9633), Staphylococcus aureus (ATCC-6538),
Escherichia coli, Bacillus cereus, and Candida albicans (ATCC-10231).
2.5. Determination of MIC
[176]Table 3 shows the MIC values of MnO[2]-MgO BNPs against the tested
strains. The MIC values indicate that the lowest concentration required
of the MnO[2]-MgO BNPs to inhibit the microbial growth ranged between
250 to 500 μg/mL, as shown in [177]Table 3 and [178]Figure 9.
Table 3.
MIC values of MnO[2]-MgO BNPs against the different tested strains.
Microbial Strain MIC Values of MnO[2]-MgO BNPs (µg/mL)
Pseudomonas aeruginosa 250 μg/mL
Klebsiella pneumonia (ATCC-9633) 500 μg/mL
Staphylococcus aureus (ATCC-6538) 500 μg/mL
Escherichia coli 500 μg/mL
Bacillus cereus 500 μg/mL
Candida albicans (ATCC-10231) 250 μg/mL
[179]Open in a new tab
Figure 9.
[180]Figure 9
[181]Open in a new tab
MIC of MnO[2]-MgO BNPs against Pseudomonas aeruginosa, Klebsiella
pneumoniae (ATCC-9633), Staphylococcus aureus (ATCC-6538), Escherichia
coli, Bacillus cereus, and Candida albicans (ATCC-10231). The yellow
arrows refer to the MIC values of the lowest concentrations required
for microbial growth inhibition.
2.6. The Antioxidant Activity
In the current study, the antioxidant activity of MnO[2]-MgO BNPs at
different concentrations (1000–7.81 μg/mL) was evaluated using the DPPH
and ABTS assays, as illustrated in [182]Figure 10A,B, respectively. The
results demonstrated that MnO[2]-MgO BNPs exhibited an IC[50] value of
350 μg/mL in the DPPH assay, while in the ABTS assay they gave an
IC[50]value of 215.6 μg/mL. These findings highlight the potent
antioxidant efficacy of MnO[2]-MgO BNPs, which reveals their power to
reduce oxidative stress related to excessive ROS generation. It is
known that the antioxidants play a crucial role in neutralizing ROS,
which are by-products of biological reactions implicated in numerous
pathological conditions, including inflammation, cancer, and
neurodegenerative diseases [[183]56].
Figure 10.
[184]Figure 10
[185]Open in a new tab
Antioxidant activity of MnO[2]-MgO BNPs at different concentrations,
measured using (A) DPPH and (B) ABTS methods.
2.7. The Anti-Biofilm Activity
Biofilm formation is a crucial survival strategy for both fungi and
bacteria that enables them to survive in diverse environments, resist
harsh conditions, and escape host immune responses [[186]57]. The in
vitro anti-biofilm activity of MnO[2]-MgO BNPs against all the tested
pathogens ([187]Figure 11) revealed a concentration-dependent reduction
in their biofilm formation. Candida albicans exhibited the highest
biofilm inhibition, with a reduction ranging from 66.83 ± 2.45% at 1/2
MIC to 15.53 ± 3.03% at 1/8 MIC. In contrast, Escherichia coli showed
the lowest biofilm inhibition, with percentages ranging from 25.35 ±
2.04% at 1/2 MIC to 8.51 ± 1.41% at 1/8 MIC. The ability of MnO[2]-MgO
BNPs to impair the integrity of biofilms suggests their potential use
in medical applications, such as in coating medical devices or
resisting biofilm-related infections [[188]58]. The significant
reduction in the formation of Candida albicans biofilm indicates that
fungal biofilms may be more susceptible to the action of MnO[2]-MgO
BNPs compared to bacterial biofilms. This could be attributed to
structural differences between fungal and bacterial biofilms, as the
formers often rely on an extensive extracellular matrix that may be
more susceptible to nanoparticle-mediated disruption [[189]59].
Figure 11.
[190]Figure 11
[191]Open in a new tab
Anti-biofilm activity of MnO[2]-MgO BNPs against tested microorganisms.
2.8. In Silico Biological Activity Predictions
The integration of in silico approaches with experimental methodologies
has significantly advanced the understanding of complex chemical and
biological processes. This synergistic strategy has proven particularly
effective in identifying molecular targets and elucidating the
mechanisms of action of bioactive compounds [[192]60,[193]61]. In the
present study, computational techniques were employed to analyze the
major constituents of Nephrolepis exaltata extract, aiming to elucidate
the components responsible for its observed antimicrobial activity
against Pseudomonas species, as confirmed by biological assay data.
Furthermore, predictive modeling was conducted to explore the potential
mechanisms underlying this activity. The identified bioactive compounds
underwent statistical screening for antimicrobial potential and were
further evaluated using the PASS Online platform to predict their
antibacterial efficacy, particularly against Pseudomonas spp., as
detailed in [194]Supplementary Table S2. The results demonstrated a
high probability of antibacterial activity (Pa > 0.5) for the majority
of the tested compounds. However, the compounds with CIDs 10155076,
157010309, and 90477731 (caffeoylquinic acid, p-Coumaroyl-hexoside, and
methoxy ursolic acid, respectively) were predicted to lack
antibacterial potential (Pa < 0.5). Notably, the compounds with CIDs
72277 (epigallocatechin) and 5281643 (hyperoside) exhibited promising
antibacterial activity against Pseudomonas sp., with Pa values of 0.7
and 0.5, respectively.
2.9. Prediction of the Potential Targets
2.9.1. Prediction of the Potential E. coli Targets of the Annotated Compounds
Given the importance of identifying therapeutic targets through which
phytochemicals exert antimicrobial activity, the PharmMapper server was
utilized to predict potential protein targets using a pharmacophore
mapping approach. PharmMapper was employed to identify targets for the
compounds with PubChem CIDs 72277 and 5281643. Each compound yielded
298 predicted protein targets ([195]Supplementary Materials, Tables S3
and S4), among which 80 targets were identified as bacterial proteins
for CID 72277 and 77 for CID 5281643 ([196]Supplementary Materials,
Tables S5 and S6). Upon further analysis using the STRING database,
only two protein targets related to P. aeruginosa were identified for
CID 72277, while one P. aeruginosa-associated target was found for CID
5281643 ([197]Table 4).
Table 4.
Predicted refined results of PharmMapper for compounds CID 72277 and
CID 5281643.
Compound Pubchem CID Pseudomonas aeruginosa Related Proteins Uniprot ID
72277
(epigallocatechin) Polypeptide deformylase [198]Q9I7A8
Quinolone signal response protein (pqsE) [199]P20581
5281643
(hyperoside) 3′-phosphoadenosine-5′-phosphosulfate reductase (PAPS
reductase) [200]O05927
[201]Open in a new tab
2.9.2. Protein–Protein Interaction (PPI) Network Analysis
To further explore the biological relevance of the three identified P.
aeruginosa protein targets ([202]Table 4), protein–protein interaction
(PPI) networks were constructed using the STRING database. In the
resulting networks, each node represents a protein target, while each
edge denotes a predicted or known interaction between proteins. The
generated PPI networks highlighted the central role of these targets,
suggesting that they function as key regulatory hubs—or “maestro”
regulators—interacting with multiple other proteins within the P.
aeruginosa proteome. This emphasizes their potential significance as
therapeutic targets against P. aeruginosa ([203]Figure 12, [204]Figure
13 and [205]Figure 14).
Figure 12.
[206]Figure 12
[207]Open in a new tab
The PPI network of correlated Pseudomonas aeruginosa protein targets
for the polypeptide deformylase [208]Q9I7A8 [[209]62].
Figure 13.
[210]Figure 13
[211]Open in a new tab
The PPI network of correlated Pseudomonas aeruginosa protein targets
for the quinolone signal response protein [212]P20581 (pqsE).
Figure 14.
[213]Figure 14
[214]Open in a new tab
The PPI network of correlated Pseudomonas aeruginosa protein targets
for the 3′-phosphoadenosine-5′-phosphosulfate reductase [215]O05927
(cysH).
The three Pseudomonas aeruginosa-related proteins targets ([216]Table
4) of compounds CID 72277 and CID 5281643 underwent enrichment analysis
to understand their biological functions and possible pathways.
Enrichment analyses were performed through Gene Ontology (GO) and the
Kyoto Encyclopedia of Genes and Genomes (KEGG).
2.10. Gene Ontology (GO) Enrichment Analysis
GO enrichment analysis is a method for interpreting gene or protein
sets by associating them with known biological functions, including
biological processes [[217]63], cellular components (CCs), and
molecular functions (MFs) [[218]60,[219]64]. The results, illustrated
by the histogram, show that the candidate targets are primarily
involved in biological processes such as translation, ribosome
assembly, and cellular response to sulfate starvation. In terms of
molecular functions, the targets are associated with structural
constituents of the ribosome, ATP binding activity, and sulfate
reductase activity. Cellular component analysis indicates enrichment in
the cytosol, NADPH-related structures, and ribosomal subunits
([220]Figure 15).
Figure 15.
[221]Figure 15
[222]Open in a new tab
GO enrichment analysis, including biological process, cellular
components, and molecular function for three Pseudomonas
aeruginosa-related protein targets ([223]Q9I7A8, [224]P20581, and
[225]O05927) of compounds CID 72277 and CID 5281643.
2.11. KEGG Pathway Enrichment Analysis
KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis is
used to map protein targets to relevant molecular pathways [[226]60].
The analysis was performed to identify potential biological pathways
associated with the predicted protein targets of the selected
phytochemicals. The top 10 enriched pathways were selected based on
enrichment scores and are visualized in [227]Figure 16. The KEGG
analysis revealed that the protein targets related to CID 72277 and CID
5281643 are predominantly associated with pathways involving
polypeptide deformylase and phosphoadenosine phosphosulfate reductase,
which represent the most significantly enriched functions.
Figure 16.
[228]Figure 16
[229]Open in a new tab
KEGG pathway enrichment analysis for three Pseudomonas
aeruginosa-related protein targets ([230]Q9I7A8, [231]P20581, and
[232]O05927) of compounds CID 72277 and CID 5281643.
2.12. Molecular Docking
In order to further verify the active ingredients, their potential
targets, and their mechanistic role against P. aeruginosa, the most
significant core targets (polypeptide deformylase and phosphoadenosine
phosphosulfate reductase) based on KEGG pathways and other
aforementioned results were selected for virtual screening docking
simulation studies against the emerged two active metabolites of
Nephrolepis exaltata extract (CID 72277 and CID 5281643) using MOE
software.
The findings demonstrated that both active metabolites interacted with
the primary target, peptide deformylase (PDB ID: 6JFF). Among them,
compound CID 72277 exhibited the strongest binding affinity, with a
docking score of −6.0270 kcal/mol. Its binding mode involved two
hydrogen bonds and two hydrophobic interactions with critical amino
acid residues Trp100, Glu146, Gly102, and Val142 ([233]Table 5 and
[234]Figure 17) [[235]9]. Conversely, compound CID 5281643 displayed a
moderate binding affinity, characterized by a docking score of −5.0920
kcal/mol and interactions including hydrogen bonds and hydrophobic
contacts with residues Trp100, Glu146, and His145 ([236]Table 5).
Table 5.
Docking results of compounds CID 72277 and CID 5281643 against target
proteins peptide deformylase (PDB ID: 6JFF) and adenosine
5′-phosphosulfate reductase (PDB ID: 2GOY).
Active Metabolites
PubChem Id (CID) Target Protein
(Isozyme) Binding Score
kcal/mol Key Amino Acid Residues Type of Binding 2D Representation
CID 72277 PDB IDs: 6JFF −6.0270 Trp100, Glu146, Gly102, Val142 H-Bond
H-Bond Hydrophobic
Hydrophobic graphic file with name pharmaceuticals-18-01262-i001.jpg
CID 5281643 PDB IDs: 6JFF −5.0920 Trp100
Glu146, His145 H-Bond
H-Bond
Hydrophobic graphic file with name pharmaceuticals-18-01262-i002.jpg
CID 72277 PDB IDs: 2GOY −5.6139 Arg242, Gly161 H-Bond
H-Bond graphic file with name pharmaceuticals-18-01262-i003.jpg
CID 5281643 PDB IDs: 2GOY −7.1013 Gly161, Thr160, Ser60, Glu162, Leu85,
Ser62, Arg242, Arg145 H-Bond
H-Bond
2x H-Bond
H-Bond Hydrophobic
Hydrophobic
Ionic
Ionic graphic file with name pharmaceuticals-18-01262-i004.jpg
[237]Open in a new tab
Figure 17.
[238]Figure 17
[239]Open in a new tab
3D-representation of (CID 72277) against peptide deformylase, PDB IDs:
6JFF.
Regarding adenosine 5′-phosphosulfate reductase (PDB ID: 2GOY), CID
5281643 emerged as the more potent ligand, achieving a binding score of
−7.1013 kcal/mol. Its interaction profile included hydrogen bonding,
hydrophobic, and ionic interactions with key residues Gly161, Thr160,
Ser60, Glu162, Leu85, Ser62, Arg242, and Arg145 ([240]Table 5 and
[241]Figure 18). In contrast, CID 72277 exhibited comparatively weaker
binding to this target, with a docking score of −5.6139 kcal/mol. Its
binding was limited to residues Arg242 and Gly161 via hydrogen bonds
([242]Table 5). These molecular docking results are consistent with the
pharmacophore modeling predictions previously obtained from PharmMapper
for both compounds.
Figure 18.
[243]Figure 18
[244]Open in a new tab
3D-representation of (CID 5281643) against adenosine 5′-phosphosulfate
reductase, PDB IDs: 2GOY.
2.13. Predicting the Role of MnO[2]-MgO BNPs in Antipseudomonal Bacterial
Effect of Nephrolepis exaltata Extract
2.13.1. ASKCOS Prediction
In this study, the ASKCOS platform (Automated Synthesis Knowledge
Construction and Optimization System) was employed to predict the redox
reaction products involved in the preparation of the nano-formulation
derived from the interaction between MnO[2]-MgO BNPs and the selected
bioactive compounds (CID 72277 and CID 5281643) ([245]Table 6). ASKCOS
([246]https://askcos.mit.edu/forward?tab=forward, accessed on 6 July
2025) is an open-source, machine learning-based software suite widely
used in computer-aided synthesis planning (CASP). It is frequently
cited in the fields of drug discovery, cheminformatics, and synthetic
route design due to its ability to utilize extensive reaction datasets
as well as predictive algorithms to propose feasible synthetic pathways
[[247]65]. In this context, ASKCOS facilitated the prediction of the
likely redox transformations, providing essential insight into the
chemical nature of the expected products, which were subsequently
subjected to further computational evaluation and molecular docking
studies.
Table 6.
ASKCOS prediction of redox transformations of compounds CID 72277 and
CID 5281643.
CID 72277 Oxidized Form CID 5281643 Oxidized Form
graphic file with name pharmaceuticals-18-01262-i005.jpg graphic file
with name pharmaceuticals-18-01262-i006.jpg
[248]Open in a new tab
2.13.2. Molecular Docking Simulation
With respect to the outer membrane porin OprD of P. aeruginosa (PDB ID:
3SY7), the oxidized forms of CID 72277 and CID 5281643 exhibited
enhanced binding affinities, suggesting efficient interaction with the
porin channel. This implies the potential for successful intracellular
delivery of the compounds via the MnO[2]-MgO-based nano-formulation,
facilitating their penetration into the bacterial cell. Once
internalized, the oxidized compounds are anticipated to be reduced back
to their native bioactive forms by intracellular redox systems of P.
aeruginosa, including NADH, glutathione, and phenazine-mediated
pathways [[249]66]. This mechanistic insight correlates with the
observed enhancement in antibacterial activity, as demonstrated in the
biological assays following nano-formulation of the NEME.
Molecular docking analysis revealed that compounds CID 72277 and CID
5281643 achieved binding scores of −4.6547 and −5.7701 kcal/mol.,
respectively. Their binding interactions involved key residues within
the OprD binding pocket: CID 72277 formed hydrogen bonds and
hydrophobic contacts with Ala199, Gly189, Gly188, Leu201, and Leu152,
while CID 5281643 interacted with Ile187, Leu152, Gly189, and Leu201
([250]Table 7).
Table 7.
Docking results of compounds CID 72277 and CID 5281643 against
Pseudomonas aeruginosa outer membrane protein OprD (PDB ID: 3SY7).
Active Metabolites
PubChem Id (CID) Target Protein
(Isozyme) Binding Score
kcal/mol Key Amino Acid Residues Type of Binding 2D Representation
CID 72277 PDB IDs: 3SY7 −4.6547 Ala199
Gly189, Gly188, Leu201
Leu152 H-Bond
H-Bond
H-Bond
H-Bond
Hydrophobic graphic file with name pharmaceuticals-18-01262-i007.jpg
CID 5281643 PDB IDs: 3SY7 −5.7701 Ile187
Leu152
Gly189, Leu201 2x H-Bond
H-Bond
H-Bond
2x Hydrophobic graphic file with name pharmaceuticals-18-01262-i008.jpg
[251]Open in a new tab
Collectively, the integration of the in silico approaches has provided
crucial insights into the antimicrobial potential of N. exaltata
extract, particularly against Pseudomonas aeruginosa. The computational
screening via PASS Online revealed that several bioactives, especially
epigallocatechin and hyperoside, possess strong antibacterial activity
(Pa ≥ 0.5), supporting findings of the biological measures.
Pharmacophore-based target prediction using PharmMapper identified
bacterial protein targets specific to P. aeruginosa, including
polypeptide deformylase, pqsE, and PAPS reductase. These proteins were
further validated as central nodes in protein–protein interaction
networks, indicating their potential role as key regulatory elements in
bacterial viability. GO and KEGG enrichment analyses highlighted their
involvement in critical biological functions such as translation and
sulfate metabolism. Subsequent molecular docking confirmed strong
interactions between these compounds and their predicted targets, with
epigallocatechin displaying the highest affinity towards peptide
deformylase, while hyperoside showed superior binding to PAPS
reductase. Interestingly, formulating these compounds into
MnO[2]–MgO-based nanoformulations further enhanced their binding to the
outer membrane porin OprD, suggesting improved cellular uptake. The
redox-responsive nature of the formulation allows intracellular
reduction of the compounds to their active forms, thus amplifying their
antibacterial potential.
3. Material and Methods
3.1. Chemicals and Reagents
Fresh leaves of Nephrolepis exaltata were purchased in September, 2024
from El-Minia garden. The plant was kindly identified by Dr. Kholoud
Nagy, the assistant professor of botany, Faculty of Sciences, Minia
University. Manganese acetate tetra hydrate (Mn(CH[3]COO)[2]·4H[2]O)
and )Mg(NO[3])[2]·6H[2]O), as sources of metal ions as well as NaOH,
were purchased from Sigma-Aldrich^®, Cairo, Egypt.
3.2. Preparation of Nephrolepis exaltata Methanol Extract (NEME)
Fresh leaves of N. exaltata were thoroughly rinsed twice with distilled
water, dried with a towel, cut, and left to dry in shade for about 1
week. After complete dryness, the leaves (500 g) were powdered,
macerated with 95% methanol, and concentrated using a Rotavap
(Heidolph, Schwabach, Germany), which gave a crude extract (100 g) that
was stored in the refrigerator at 4 °C [[252]67].
3.3. UPLC/MS Analysis of Nephrolepis exaltata Extract
The UPLC/MS analysis for the N. exaltata extract was executed using a
XEVO TQD triple quadruple instrument, Waters Corporation, Milford, MA,
USA, with ESI-MS positive and negative ion acquisition modes using an
ACQUITY UPLC—BEH C18 column (1.7 mm − 2.1 mm × 50 mm) with a flow rate
of 0.2 mL/min, applying a gradient of water containing 0.1% formic acid
and acetonitrile containing 0.1% formic acid
[[253]13,[254]20,[255]68,[256]69,[257]70].
3.4. Biosynthesis of MnO[2]-MgO BNPs of Nephrolepis exaltata Extract
The MnO[2]-MgO BNPs were prepared using different concentrations of
salts compared to bimetallic biosynthesis [[258]71]. A 10 mL (0.05 M)
sample of Mn (CH[3]COO)[2]·4H[2]O and 10 mL (0.2 M) of Mg
(NO[3])[2]·6H[2]O) were mixed and then agitated for 20 min. Then, 80 mL
of the formulated Nephrolepis exaltata extract was added and finally
the PH was adjusted to 9.0. For optimizing the synthesis of MnO[2]-MgO
BNPs, the reaction was conducted in a shaking incubator at 35 °C with
continuous agitation at 150 rpm for approximately 24 h, resulting in a
color change to black which suggests the successful bioformation of
MnO[2]-MgO BNPs [[259]36]. To ensure purity of the bimetallic
nanoparticles, 5 washings with distilled water were employed to remove
any loosely bound organic residues. This was followed by centrifugation
at 10,000 rpm for 10 min. The precipitate was then oven-dried at 70 °C
for 48 h.
3.5. Characterization of the Formed MnO[2]-MgO BNPs
The initial formation of MnO[2]-MgO BNPs was detected by the color
change of the NEE from yellow to black. UV–visible spectroscopy (JENWAY
6305, Keison Products, Staffordshire, UK) was employed to measure the
absorbance of the synthesized NP solution at wavelengths ranging from
200 to 700 nm to determine the maximum SPR. FTIR analysis (Cary-660
model, Agilent Technologies, Santa Clara, CA, USA) was conducted using
the KBr pellet method at the wavenumber range of 400 to 4000 cm^−1 to
identify the chemical functional groups formed between the MnO[2]-MgO
BNPs [[260]72]. TEM with a JEM-2100 Plus, Jeol, Tokyo, Japan apparatus
was employed to estimate the average dimensions and morphologies of the
formed MnO[2]-MgO BNPs. DLS, using a Nano Zetasizer instrument from
Malvern Panalytical, Malvern, England, was employed to measure the mean
particle size distribution of the synthesized MnO[2]-MgO BNPs. An
XRD-6000, Shimadzu, Kyoto, Japan was harnessed to estimate the crystal
size and crystallinity of the bimetallic MnO[2]-MGO BNPs [[261]8].
Scanning electron microscopy (SEM, ZEISS, EVO-MA10, Oberkochen,
Germany) was used to examine the surface structure, while
energy-dispersive X-ray spectroscopy (EDX, Bruker, Bremen, Germany)
confirmed the elemental composition, purity, and distribution of the
synthesized MnO[2]-MgO BNPs.
3.6. Evaluation of the Antimicrobial and Anti-Biofilm Activity
3.6.1. Selection of the Isolates
The bacterial isolates and standard strains used in this study were
obtained from the Bacteriology laboratory at the Botany and
Microbiology Department, Faculty of Science, Al-Azhar University. These
microorganisms included gram-negative species such as Escherichia coli
and Pseudomonas aeruginosa, as well as the gram-positive species
Bacillus cereus. The identification and antibiotic susceptibility
testing were previously conducted using the VITEK2 system
(BioMérieux^®, Inc., Durham, NC, USA) [[262]73]. In addition to these
bacterial strains, standard strains of Staphylococcus aureus
(ATCC-6538), Klebsiella pneumoniae (ATCC-9633), and Candida albicans
(ATCC-10231) were employed for testing the antimicrobial activity and
biofilm inhibition potency of MnO[2]-MgO BNPs.
3.6.2. The Antimicrobial Activity
The antimicrobial activity of Nephrolepis exaltata extract, MnO[2],
MgO, and MnO[2]-MgO BNPs was assessed using Mueller Hinton Agar
(Ministry of Home Affairs, New Delhi, India) for bacterial strains and
Potato Dextrose Agar for Candida albicans [[263]74]. Fresh 24 h
cultures of tested microorganisms were inoculated onto the surface of
the prepared MHA and PDA plates for bacterial and fungal testing,
respectively. Wells of 6 mm diameter were made using a sterile cork
borer and 100 µL of each test compound was carefully dispensed into
separate wells. The plates were then left at 4 °C for 2 h to allow
diffusion. The inoculated plates were subsequently incubated for 24 h
at 37 °C for all bacterial strains and 48 h at 28 °C for Candida
albicans. After the incubation period, inhibition zones were measured
and recorded to evaluate the antimicrobial efficacy of each of the
tested formulations [[264]75].
3.6.3. Determination of the MIC
The MIC values of MnO[2]-MgO BNPs were determined via the broth
microdilution assay method reported by El-Didamony et al. [[265]73].
Various concentrations of MnO[2]-MgO BNPs were prepared, and 100 µL of
the tested preparations was added to sterile microtiter plate wells
containing 100 µL of double-strength Mueller Hinton (MH) broth, all of
which resulted in final concentrations of 1000, 500, 250, 125, 62.5,
and 31.25 µg/mL. A microbial cell suspension (50 µL) adjusted to an OD
equivalent to the 0.5 McFarland standard was introduced into all wells,
except for the negative control. The positive control wells contained
MH broth and bacterial suspension to assure the ability of the broth to
support bacterial growth, while the other wells included MH broth to
ensure sterility. The plates were incubated at 37 °C for 24 h. To
detect bacterial growth, 30 µL of resazurin solution (0.02% wt./v) was
inoculated, followed by overnight incubation. A color change indicated
the microbial growth, whereas the absence of color change in sterile
control wells confirmed the absence of contamination. The experiment
was conducted in triplicate and the mean values were calculated
[[266]76].
3.6.4. The Anti-Biofilm Assay
The anti-biofilm activity of MnO[2]-MgO BNPs was assessed using 96-well
microtiter plates (flat-bottom, polystyrene) following the method
reported by Sharaf, MH [[267]77]. Each well was filled with 100 μL of
MHB, inoculated with 10 μL of an overnight microbial culture
suspension, then adjusted to an OD[620] of 0.05 ± 0.02. To this
mixture, 100 μL of the MnO[2]-MgO BNPs of NEE was added at different
concentrations corresponding to ½ × MIC, ¼ × MIC, and 1/8 × MIC. The
plates were then incubated at 37 °C for 48 h and the biofilms were
fixed using absolute alcohol and stained with 0.1% (w/v) crystal violet
solution for 30 min. Finally, the wells were air-dried, where 200 μL of
33% CH3COOH was added to dissolve the stained biofilm, followed by
measuring the OD at 630 nm. The percentage inhibition of biofilm
formation was calculated using the following equation:
[MATH: Biofilm inhibition%=1−OD630 of cells treated with different concentration of MnO2−MgOBNPs extractOD630 of non treated control×100 :MATH]
(1)
3.7. Antioxidant Assays (DPPH and APTS Scavenging Activities)
The free radical-scavenging potential of MnO[2]-MgO BNPs was determined
via the DPPH reagent assay [[268]78]. The DPPH reagent was prepared by
dissolving 8 mg of DPPH in 100 mL of methanol to give a concentration
of 80 µg/mL. To determine the scavenging activity, 100 µL of the DPPH
reagent was combined with 100 µL of the test sample in a 96-well
microplate and incubated at room temperature for 30 min, and then the
absorbance was recorded at 490 nm using an ELISA reader (TECAN, Grödig,
Austria), with 100% methanol as the control. The DPPH scavenging
activity was calculated using the following formula:
[MATH: DPPH scavenging activity=control absorbance−MnO2−MgOBNPs absorbancecontrol absorbance×100 :MATH]
(2)
To evaluate the DPPH radical scavenging activity, different
concentrations of MnO[2]-MgO BNPs (1000, 500, 250, 125, 62.5, 31.25,
15.62, and 7.81 µg/mL) were tested. The antioxidant activity of both
the standard and MnO[2]-MgO BNPs was expressed as DPPH scavenging
activity (%). The half-maximal inhibitory concentration (IC[50]) was
determined to assess the effectiveness of the NPs as antioxidants.
Additionally, the antioxidant activity of MnO[2]-MgO BNPs was further
evaluated using the ABTS
(2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid)) assay. This
method followed the protocol established by Lee [[269]79] with minor
modifications:
[MATH: APTS scavenging activity=control absorbance−MnO2−MgOBNPs extract absorbancecontrol absorbance×100 :MATH]
(3)
3.8. In Silico Biological Activity Predictions
The Way2Drug platform offers a suite of computational tools designed to
assist researchers in predicting various pharmacological and
toxicological properties of chemical compounds, including biological
activity spectra, cytotoxicity, adverse drug reactions, mechanisms of
action, and interactions with metabolic enzymes [[270]80]. Among these
tools is PASS Online (Prediction of Activity Spectra for Substances),
which predicts the biological activity profiles of compounds based on
structure–activity relationships derived from a database of over one
million biologically characterized molecules. PASS provides a
probabilistic assessment of biological activity, expressed as the
probability of activity (Pa) and inactivity (Pi), achieving an average
predictive accuracy of approximately 95% [[271]81]. The chemical
structures of compounds 1–20 were retrieved along with their PubChem
IDs and SMILES ([272]Supplementary Table S1) using the PubChem^®
database ([273]https://pubchem.ncbi.nlm.nih.gov/, accessed on 6 July
2025), then submitted to PASS Online in the SMILES format, and their
predicted activities were recorded. Compounds with Pa values ≥ 0.5 were
considered potentially active and selected for further evaluation, with
particular interest given to those with 0.7 > Pa > 0.5, indicating
moderate confidence in activity ([274]Table S2). Additionally,
AntiBac-Pred ([275]http://www.way2drug.com/antibac/, accessed on 6 July
2025), an extension of the PASS platform, was employed to predict the
antimicrobial spectrum of the compounds against a panel of 353
bacterial strains. The output is provided as a confidence ratio, where
higher values correspond to a greater likelihood of antibacterial
activity against specific microbial species.
3.9. Prediction of the Potential Protein Targets of the Annotated Compounds
The potential molecular targets of the annotated compounds were
predicted using the PharmMapper server, an advanced pharmacophore-based
web tool that utilizes reverse molecular docking to identify potential
targets [[276]82,[277]83]. The compounds were uploaded in SDF format,
where default parameters were applied. Specifically, conformer
generation was enabled with a maximum of 300 conformations per
compound, energy minimization was activated, and the target set used
for pharmacophore mapping was the “Druggable Pharmacophore Models”
database (version 2017, containing 16,159 models). For compounds
predicted to exhibit antibacterial activity, targets associated with
Pseudomonas species were selectively retrieved for further analysis.
Subsequent target validation and interaction analysis were performed
using STRING database version 11.5 ([278]https://string-db.org/,
accessed on 6 July 2025), which compiles and integrates known and
predicted protein–protein interactions [[279]60]. The list of predicted
targets from PharmMapper was input into STRING, specifying Pseudomonas
aeruginosa as the organism of interest. A medium confidence threshold
(interaction score ≥ 0.4) was applied.
3.10. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)
Enrichment Analysis
To gain deeper insights into the biological functions and associated
pathways of the identified protein targets, functional enrichment
analyses were conducted using Gene Ontology (GO) and the Kyoto
Encyclopedia of Genes and Genomes (KEGG) databases. GO analysis
categorizes gene functions into three domains: biological process
[[280]63], cellular component (CC), and molecular function (MF),
providing a comprehensive understanding of gene roles. KEGG pathway
analysis elucidates the biological pathways in which the target genes
are involved. GO enrichment analysis was performed and visualized using
STRING database, applying a false discovery rate (FDR) threshold of <
0.05 to ensure statistical significance. KEGG pathway enrichment was
performed and visualized using the ShinyGO (version 0.76.3;
[281]http://bioinformatics.sdstate.edu/go/, accessed on 6 July 2025)
and SRplot tools ([282]https://www.bioinformatics.com.cn/en, accessed
on 6 July 2025), facilitating the interpretation of key pathways
associated with the predicted targets [[283]60,[284]64,[285]84].
3.11. Molecular Docking
Molecular docking was performed between compounds CID 72277
(epigallocatechin) and CID 5281643 (hyperoside) and the core targets
peptide deformylase and adenosine 5′-phosphosulfate reductase. The
Molecular Operating Environment (MOE) 2019.0102 software was used for
molecular docking simulation for the studying of binding affinity N.
exaltata metabolites against target enzymes. The database of the active
metabolites was drawn and prepared via energy minimization, hydrogen
addition, and calculation of the partial charges. Finally, this
prepared database was saved in the form of mdb extension. The target
enzymes were retrieved from Protein Data Bank ([286]www.rcsb.org) with
PDB IDs: 6JFF and 2GOY. They were prepared and checked through
automatic quick prepare order of MOE. The docking simulation was
implemented via Amber10 Forcefield. Evaluation of ligand–protein
complex interactions was afforded through visualization of poses and
scoring function. Validation of docking studies was examined by the
Root Mean Square Deviation (RMSD) values for co-crystalized ligand
protein iso-zymes, (peptide deformylase, PDB IDs: 6JFF, RMSD:1.6367)
and (adenosine 5′-phosphosulfate reductase, PDB IDs: 2GOY,
RMSD:1.0805).
3.12. Predicting the Role of MnO[2]-MgO BNPs in Antipseudomonal Bacterial
Effect of Nephrolepis exaltata Extract
The potential reaction products formed between the MnO[2]–MgO
composites and the top-ranked bioactive constituents of the extract
(CID 72277 and CID 5281643) were predicted using the ASKCOS online tool
([287]https://askcos.mit.edu/, accessed on 6 July 2025). Subsequently,
the resulting products were subjected to molecular docking studies
against the high-resolution crystal structure of the Pseudomonas
aeruginosa outer membrane protein OprD (PDB ID: 3SY7), a critical porin
that regulates the transport of small molecules into and out of the
bacterial cell. This protein is known to contribute to antibiotic
resistance mechanisms, and structural insights into OprD can facilitate
the development of therapeutic strategies to counter such resistance.
Molecular docking simulations were carried out using the Molecular
Operating Environment (MOE) software. The active metabolites were
sketched, energetically minimized, and structurally optimized by adding
hydrogen atoms and calculating partial atomic charges. The processed
ligands were stored in MOE’s proprietary database format (mdb). The
OprD protein structure was retrieved from the Protein Data Bank (PDB
ID: 3SY7) and prepared using MOE’s QuickPrep protocol. Docking
procedures were executed using the Amber10 force field. Ligand–protein
interactions were evaluated based on binding poses and scoring
functions. The reliability of the docking protocol was confirmed by
calculating the Root Mean Square Deviation (RMSD) between the docked
and co-crystallized ligand poses, yielding an RMSD value of 1.3874 Å,
which indicates acceptable accuracy.
3.13. Statistical Analysis
The statistical analysis of the obtained data was visualized by
GraphPad Prism version (8.0.2). To make comparison of the differences
between groups, an independent t-test was employed. The analysis was
conducted using the Sorensen (Bray–Curtis) method for group linkage,
which enabled the clustering of similar groups based on their
characteristics. ANOVA (Analysis of Variance) and Tukey’s post hoc test
were applied for multiple comparisons.
4. Conclusions
The current study investigated the antimicrobial and anti-biofilm
activities of greenly synthesized MnO[2]-MgO BNPs against several
tested pathogens, where the results revealed a concentration-dependent
reduction in their biofilm formation. Accordingly, Nephrolepis exaltata
nanoparticles may act as a natural source for new antimicrobial drugs
with potent biofilm inhibition activity. Future research is encouraged
in order to isolate the main components responsible for the observed
activities. The progressive challenge of antibiotic resistance
necessitates the evolution of standby strategies to ensure good health,
safety, and improved quality of life. This study successfully
synthesized and characterized MnO[2]-MgO bimetallic nanoparticles using
Nephrolepis exaltata as a sustainable reducing agent, which correlates
to green chemistry principles. Such a cost-effective and eco-friendly
approach underscores the potential of MnO[2]-MgO BNPs in combating
Psudomonas aeruginosa strains, which are a major public health threat
associated with blood and lung infections, while aligning with global
sustainability goals.
The greenly synthesized MnO[2]-MgO BNPs exhibited superior purity and
distinctive morphologies, with a dose-dependent anti-biofilm inhibition
of P. aeruginosa strains. The findings highlight the efficiency of
eco-friendly MnO[2]-MgO BNPs as potent antibacterial agents, presenting
a foundation for future research to elucidate their mechanisms and
explore their broader applicability across multidisciplinary domains,
potentially improving public health and sustainable practices.
Acknowledgments