Abstract
This study probed the ameliorative effects of naringenin in a D.
melanogaster model of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine
(MPTP)-induced parkinsonism, incorporating computational analysis.
Initially, flies were treated with naringenin (100–500 µM) and MPTP
(250–750 µM) for 14 days in two separate studies to determine the
optimum concentrations for the treatments. Following this, optimum
naringenin concentrations (100 and 300 µM) were administered to MPTP
(500 µM)-exposed flies in a 4-day study. Motor function, survival rate,
and neurotoxicity biomarkers were assessed alongside biological network
analysis and molecular docking simulation. Results indicate that
naringenin exhibits hormetic behavior, with 100–300 µM providing
optimal neuroprotection. The treatments significantly improved negative
geotaxis and acetylcholinesterase activity, and reduced MPTP-induced
oxidative stress as indicated by reduced nitric oxide, hydrogen
peroxide, and protein carbonyl levels. Furthermore, naringenin restored
thiol contents, and enhanced catalase and glutathione-S-transferase
activities. Network analysis helped to identify key targets, including
DRD4, DRD2, NFKB1, MAOB, MAPK14, and CYP2A6, which function in
dopaminergic signaling and oxido-inflammatory pathways. Molecular
docking analysis revealed strong binding interactions of naringenin
with DRD2, MAO, MAPK, and NF-κB protein targets, primarily through
hydrogen bonding and hydrophobic interactions. Overall, these findings
suggest that naringenin mitigates MPTP-induced neurotoxicity by
enhancing dopaminergic neurotransmission and suppressing oxidative
stress and inflammation. This study further supports the
neuroprotective potential of naringenin and could be suggested as a
promising nutraceutical/drug candidate for Parkinson’s disease.
Keywords: Parkinson's disease, Toxicity, Flavonoids, Drosophila
melanogaster, Network pharmacology, Molecular docking
1. Introduction
Parkinson’s disease (PD), once considered a rare neurodegenerative
disorder, is now considered the fastest growing neurological disorder
which poses serious health, societal and economic threats to the low-
and middle-income nations [29][1], [30][2]. It resulted in 5.8 million
disability-adjusted life years (DALYs) and 329,000 deaths in 2019
[31][3]. The number of people affected is projected to reach 12.9
million by 2040 due to aging within populations [32][4]. Environmental
factors including pesticides, chemicals, air pollution, and increased
smoking are expected to further drive the number to a higher level, as
the incidence of the disease is disproportionately increasing in
emerging industrialized zones and outpacing the rate of aging [33][5],
[34][6]. It is predicted that as low- and middle-income nations develop
and life expectancy rises, the majority of the PD burden will arise
from these countries, posing serious health and economic threats in
these regions [35][2], [36][4]. Indeed, PD is a multifactorial disorder
where genetic predisposition, environmental triggers, and aging combine
to induce the degeneration of dopaminergic neurons in the substantia
nigra causing motor symptoms including tremors, rigidity, bradykinesia
(slowness of movement), and postural instability and non-motor
symptoms, including cognitive decline, mood disorders, and autonomic
dysfunction [37][7], [38][8]. By the time motor symptoms appear, around
60–80 % of these neurons are lost [39][9]. Although the hallmark
feature of PD is the progressive loss of dopaminergic neurons in the
substantia nigra pars compacta region of the brain which is responsible
for producing dopamine, other mechanisms central to the pathogenesis of
PD include alpha-synuclein aggregation, mitochondrial dysfunction,
oxidative stress, and neuroinflammation [40][10], [41][11]. Levodopa
(L-DOPA), the current gold standard for advanced-stage symptomatic
relief and other therapeutic interventions for PD are limited and do
not impede disease progression. Besides, long-term administration of
L-DOPA may cause levodopa-induced dyskinesias, prompting physicians to
start treatment with other dopamine agonists or monoamine oxidase
inhibitors, which often fail to impede disease progression.
Consequently, research is ongoing to develop new therapeutic
alternatives to stop or delay PD development while protecting
dopaminergic nerve cells to support proper motor function.
The 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a well-known
environmental neurotoxin that is widely used in scientific research to
induce PD-like symptoms in animal models [42][12]. Its discovery and
use has been instrumental to advancing our understanding of
environmental factors that contribute to the pathogenesis of PD. The
MPTP-induced PD models allow researchers to investigate the molecular
mechanisms of dopaminergic neuron death [43][13], [44][14], [45][15],
[46][16]. Furthermore, the models are used to test the efficacy of
neuroprotective agents, including antioxidants, anti-inflammatory
compounds, and mitochondrial stabilizers as the model replicates both
motor and non-motor symptoms of PD; and thereby provides a
comprehensive tool for evaluating potential PD treatments [47][15],
[48][16]. Mechanistically, MPTP enters the brain and taken up by
astrocytes and then metabolized by the enzyme monoamine oxidase-B
(MAO-B) into its toxic metabolite [49][17], [50][18]. The
MPP+ (1-methyl-4-phenylpyridinium) is then released into the
extracellular space and taken up selectively by dopaminergic neurons
via the dopamine transporter (DAT), which makes dopaminergic neurons
especially vulnerable to MPTP toxicity [51][19]. Once inside the
dopaminergic neurons, MPP+ is transported into mitochondria, where it
inhibits complex I of the electron transport chain [52][18]. This
inhibition disrupts oxidative phosphorylation, leading to decreased ATP
production and a subsequent increase in the generation of reactive
oxygen species (ROS). The oxidative stress generated by MPP+ causes
mitochondrial dysfunction, ultimately leading to energy failure, loss
of membrane potential, and the activation of cell death pathways in
dopaminergic neurons. Dopaminergic neurons are particularly susceptible
to oxidative stress due to their high metabolic activity and the
presence of dopamine, which can undergo oxidation to form toxic
quinones. The resulting oxidative stress further contributes to
mitochondrial dysfunction and neuronal death. MPTP-induced
neurodegeneration is accompanied by activation of microglia, the
resident immune cells of the brain. Microglia release pro-inflammatory
cytokines, such as tumor necrosis factor-alpha (TNF-α) and
interleukin-1 beta (IL-1β), which exacerbate neuroinflammation and
contribute to further neuronal damage [53][20]. This neuroinflammatory
response plays a critical role in the progression of MPTP-induced
neurotoxicity and mirrors the chronic inflammation observed in human
PD. The D. melanogaster model provides a robust and versatile platform
for preclinical drug screening due to its low or absent ethical
limitations, genetic tractability, short life cycle, high fecundity and
low cost of maintenance. The D. melanogaster MPTP model is a powerful
tool for studying the molecular mechanisms underlying PD and for
testing potential neuroprotective treatments as many of the core
processes involved in PD pathogenesis, such as mitochondrial
dysfunction, protein aggregation, and neurodegeneration, are
well-conserved in D. melanogaster [54][16], [55][21]. Chronic
administration of MPTP to flies has been shown to cause selective
degeneration of dopaminergic neurons, neuroinflammation and locomotor
abnormality, mimicking the symptoms of parkinsonism [56][22].
Computational biology tools and data integration techniques including
algorithms, simulations, and molecular docking techniques for
predicting how drugs interact with biological targets continue to
evolve towards revolutionizing drug discovery. Network pharmacology
focuses on understanding how drugs/toxins interact with multiple
targets within biological networks, rather than the traditional
single-target drug development model. This multi-dimensional approach
integrates computational biology, bioinformatics, and pharmacology to
study the interactions between drugs, targets, and biological systems
on a network level. By focusing on multi-target interactions, system
robustness, and network modularity, network pharmacology offers a more
integrative and holistic approach to understanding how drugs work
within the broader context of human health and disease. This shift
enables the development of more effective therapies for complex
diseases, reduces adverse effects, and supports the emerging field of
personalized medicine [57][23]. Several studies have reported
identification of multitargeting phytochemicals against parkinsonism
through network pharmacology [58][24], [59][25], [60][26]. While
network pharmacology is a powerful tool for identifying potential drug
targets, molecular docking and other molecular modelling tools can help
to clarify the interaction of the drug with these multiple targets.
Molecular docking integrated with molecular dynamics simulation has
been used to suggest various natural products that interacts with
important targets in neurodegenerative diseases [61][27], [62][28].
Integration of network pharmacology with molecular docking ensures that
drugs can modulate different nodes within a network; and thereby
enables the discovery of multi-target drugs and the development of more
effective therapies for complex diseases such as neurodegenerative
diseases. Combining in vivo studies with computational modeling offers
a powerful approach to understanding biological processes and
developing therapeutic interventions. This integrative approach is
particularly valuable in fields like neurodegenerative diseases,
pharmacology, and toxicology, where both animal models and
computational tools can provide complementary insights.
Dietary polyphenols are natural compounds found in food plants that
have gained attention for their potential as promising therapeutic
agents. These compounds, which include flavonoids, phenolic acids,
lignans, and stilbenes, are abundant in fruits, vegetables, tea, wine,
and cocoa. Due to their wide range of biological activities,
polyphenols are being explored as drugs for various chronic diseases,
particularly because of their safety and multifunctional properties
[63][29], [64][30], [65][31]. Our previous studies have revealed the
protective role of some flavonoids including of resveratrol, hesperetin
and curcumin in D. melanogaster models [66][32], [67][33], [68][34].
Naringenin, a flavonoid found predominantly in citrus fruits, has
demonstrated significant neuroprotective properties through its
antioxidant, anti-inflammatory, and anti-apoptotic activities, as well
as its ability to protect mitochondria and enhance neurogenesis and
synaptic plasticity. These mechanisms collectively make naringenin a
promising therapeutic agent for neurodegenerative diseases. The
neuroprotective mechanism of naringenin is not fully understood in D.
melanogaster, a versatile model for current and future preclinical
studies of this compound which can further elucidate its potential as a
neuroprotective agent in human health. Therefore, this study focused on
exploring the beneficial effects of naringenin in D. melanogaster model
of MPTP-induced parkinsonism combined with network pharmacology and
molecular docking.
2. Materials and methods
2.1. Chemicals and D. melanogaster culture
All chemicals used were commercial products of analytical grade. The
1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) at a percentage
purity of 95 % and naringenin were procured from A K Scientific, 30023
Aherm Ave, Union City, CA 94587, United States of America. The
5′,5′-dithiobis(2- nitrobenzoic acid) (DTNB), and reduced glutathione
(GSH) were purchased from Sigma Aldrich (St. Louis, MO, USA).
2.2. Culture of D.melanogaster culture
The D. melanogaster (wild type, Oregon strains) flies (1–3 days old)
from the National Species Stock Centre, Bowling Green, Oklahoma, USA
were used for this study. They were obtained from the Department of
Biochemistry and Molecular Biology, Federal University of Santa Maria,
Brazil. The flies were maintained and reared on cornmeal medium mixed
with brewer's yeast (1 % w/v), agar-agar (1 % w/v), and nipagin
(preservative, 0.08 % v/w) at constant temperature (23 ± 2 °C) under
12 h dark/light cycle in the Drosophila Laboratory, Department of
Biochemistry, University of Ibadan, Oyo-State, Nigeria.
2.3. MPTP exposure and naringenin treatment
To determine the appropriate doses and duration of naringenin treatment
and MPTP exposure a 14-day survival study was carried out on two
separate sets of both D. melanogaster genders (1–3 days old) as
previously described earlier [69][35]. Briefly, different groups
containing 50 flies/vial (n = 5) were orally exposed to naringenin
(100, 200, 300, 400, and 500 µM) for 14 days. Daily mortality was
enumerated and used to estimate the percentage of surviving flies in
each vial. Also, the oxidative stress markers and antioxidant status of
the flies were determined. Similarly, flies were exposed to MPTP (250,
500, and 750 µM) for 14 days and percentage of surviving flies were
estimated. Based on the data obtained, 100 and 300 µM of naringenin as
well as 500 µM of MPTP were selected and exposed to flies for 4 days.
Thereafter, indices of survival, neurotoxicity, inflammation, oxidative
stress and antioxidant status were estimated. Locomotor performance of
naringenin- and MPTP-treated flies was investigated using the negative
geotaxis assay method [70][36] as described in a previous study
[71][37].
2.4. Biochemical analyses
Following the treatments, the flies were anaesthetized using carbon
(iv) oxide, weighed, and homogenized in 0.1 M phosphate buffer, pH 7.0
(ratio of 1 mg:10 mL). Centrifugation of the homogenates was performed
at 4000 g for 10 mins at 4°C in a Thermo Scientific Sorval Micro 17 R
refrigerated centrifuge. Supernatants were separated into labeled
conical tubes, stored at −20°C and aliquots used for the determination
of biochemical parameters carried out in duplicates for each of the
five replicates of MPTP and naringenin concentrations. Estimation of
protein was carried out using Lowry’s method [72][38]. Determination of
Total thiol level was achieved using Ellman’s method [73][39]. The
enzyme activity of Glutathione-S-transferase was assayed following the
method of Habig and Jakoby [74][40]. Catalase activity was assayed
according to the method described by Aebi [75][41]. The procedure of
Ellman, et al. [76][42] was used for evaluating the activity of
acetylcholinesterase (AChE). The H[2]O[2] content was estimated using
the method of Jiang, et al. [77][43]. The nitrite level in the aliquots
was determined using the Griess reaction method [78][44].
2.5. Gene mining, target prediction and network construction
The SMILES notation and the 2D chemical structure of naringenin were
used on the Swiss Target Prediction database
([79]http://www.swisstargetprediction.ch) [80][45] and PharmMapper
([81]http://www.lilab-ecust.cn/pharmmapper/) [82][46] to predict target
genes. The predicted target genes were imported into the UniProt
database ([83]https://www.uniprot.org/) [84][47] to retrieve the
standard gene names, while duplicate entries were removed. The
GeneCards database ([85]https://www.genecards.org/) [86][48] and Online
Mendelian Inheritance in Man (OMIM, [87]http://omim.org/) [88][49] were
used to predict potential MPTP- induced targets. The related targets
were collected using the keywords “1-methyl-4-phenyl-1, 2, 3,
6-tetrahydropyridine-induced parkinson’s disease” and “parkinsonism”
along with the Homo sapiens species. In order to identify the
intersection genes as potential targets, a Venn diagram was created by
using Draw Venn Diagram tool ([89]https://bioinformat
ics.psb.ugent.be/webtools/Venn/) accessed on 11 September, 2024. The
UniProt database was utilized to retrieve the standard gene names, and
after merging the predicted targets for the three keywords from both
databases, duplicate entries were removed. Protein–protein interaction
(PPI) networks were constructed using the STRING
([90]https://cn.string-db.org/cgi/input.pl) [91][50]. The PPI networks
were imported into Cytoscape 3.10.2 [92][51] software to obtain the hub
genes. The cytoHubba plugin [93][52] was utilized to compute the top 10
hub nodes using the degree (k). The Analyze Network tool was used for
topological analyses of the network, including Maximal Clique
Centrality (MCC) method, degree (k), betweenness centrality (BC),
clustering coefficient, closeness centrality (CC), and average shortest
pathway (ASPL). The overlapping genes were further explored through
Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)
enrichment analyses using the Shiny GO 0.77 tool
([94]http://bioinformatics.sdstate.edu/go/ [95][53], with an FDR of
<0.05 and p of <0.05 as cut-off values, displaying the top ten results.
2.6. Molecular docking
The 3-D crystallographic structures of selected key target proteins
were retrieved from Protein Database ([96]http://www.rcsb.org). These
include DRD2 (PDBID: 8IRS) complexed with agonist rotigotine, MAOB
(PDBID: 2V60) in complex with inhibitor
7-[(3-Chlorobenzyl)oxy]-2-Oxo-2h-Chromene-4-Carbaldehyde (safinamide),
MAPK/JNK3 (PDBID: 7S1N) cocrystalized with inhibitor
4-[5-(2-chloro-6-fluoroanilino)-6-methyl-1H-pyrazolo[3,4-b]pyridin-1-yl
]-N-(oxetan-3-yl)thiophene-2-carboxamide (DA-74674) and NF-kB (PDBID:
2O61). All the co-crystallised/reference compounds and water molecules
were deleted and missing hydrogen atoms were added using MGL-AutoDock
Tools (ADT, v1.5.6) as demonstrated earlier [97][54]. The Kollamn
charges were added as the partial atomic charge [98][55]. The 3D
structures of naringenin and reference compounds were downloaded from
the PubChem compound database ([99]www.pubchem.ncbi.nlm.nih.gov) as
Structure data format (SDF) files. The SDF files of the ligands were
then converted to mol2 chemical format using Open babel [100][56]. The
Gasteiger-type polar hydrogen charges were assigned to the atoms in the
structures, while the non-polar hydrogen atoms were merged with the
carbons. The internal degrees of freedom and torsions were set to zero
as demonstrated earlier [101][30]. Finally, the structure files were
converted to the PDBQT format dockable in AutoDock Tools. The
structures of the hub targets were retrieved from the Protein Data Bank
([102]https://www.rcsb.org). The structures of naringenin and the
native compounds were imported into AutoDock Vina incorporated in PyRx
0.8. The structures were then minimized through Open Babel using the
Universal Force Field (UFF) as the energy minimization parameter and
conjugate gradient descent as the optimization algorithm. The small
molecule compounds were then docked against the binding/active sites of
the proteins. The binding/active sites were each defined by the grid
boxes covering the active site residues as demonstrated earlier
[103][57], [104][58]. The docking was performed with other parameters
kept as default. Subsequently, visual inspection was performed on the
various docked posed using Discovery Studio Visualizer version 16.
2.7. Statistical analyses
Data were expressed as mean ± standard error of mean. Comparison of
data was carried out by one-way ANOVA. Statistical significance was set
at P < 0.05.
3. Results
3.1. Naringenin alone improves longevity and antioxidant status in D.
melanogaster
[105]Fig. 1 shows the effects of naringenin supplementation on survival
and oxidative/antioxidant markers in D. melanogaster. For the survival
test, a representation of mortality over a period of 14 days in treated
and untreated flies is presented in [106]Fig. 1A. The survival rates
show a downward trend over time, with some differences based on
concentration ([107]Fig. 1A). Upon a 14-day incubation of flies with
normal diet, the percentage of surviving flies was observed as 89.37 %
([108]Fig. 1B). However, this value was observed as 90.22 % (P < 0.05),
86.18 % (P < 0.05), 89.73 % (P < 0.05), 88.89 % (P < 0.05) and 80.67 %
in flies fed with diets supplemented with concentrations of 100, 200,
300, 400 and 500 µM respectively indicating that, survival is quite
high in the lower concentrations (100 and 300 µM) ([109]Fig. 1B).
Higher concentrations of naringenin (400 and 500 µM) seem to have a
negative impact on survival compared to lower concentrations or
control, indicating that, higher doses of naringenin might induce
toxicity, whereas lower doses appear less harmful or neutral with
respect to survival. Figures C-H show the results of the effects of
naringenin on the levels of various biochemical markers related to
oxidative stress and antioxidative defense. Antioxidants like SOD, CAT
are elevated at lower concentrations of naringenin but may decrease at
higher concentrations. Similar to the survival test, naringenin might
have a hormetic effect on the biochemical indices, where lower
concentrations enhance antioxidant defenses and higher concentrations
may overwhelm the system and lead to oxidative damage.
Fig. 1.
[110]Fig. 1
[111]Open in a new tab
Effects of different concentrations of naringenin treatments on the
survival and biochemical indices in D. melanogaster. (A) Survival
curves of D. melanogaster under various concentrations of naringenin
(100, 200, 300, and 500 μM) over a 14-day period. (B) Bar graph
representing the percentage survival of D. melanogaster on day 14
across the different naringenin concentrations. (C-H)
oxido-inflammation markers viz: Nitric oxide (NO), H2O2 (H[2]O[2]),
Total thiol, non-protein thiol, catalase (CAT) enzyme activities and
Glutathion S- transferase activity (GST). Each bar in the bar graphs
represents the mean ± SEM for each group, with statistical significance
marked for differences compared to the control (P < 0.05).
3.2. Naringenin reduces toxicity in MPTP‑treated D. melanogaster
[112]Fig. 2A depicts the effects of different concentrations of MPTP
(250 µM, 500 mM, 750 mM) on D. melanogaster survival over time,
compared to a control group. The data show that higher concentrations
of MPTP result in more rapid declines in survival. Specifically, after
14 days incubation period, survival rates decreased to 46.53 %, 53.90 %
and 65.78 % in flies exposed to diets supplemented with 250 µM, 500 µM,
and 750 µM of MPTP respectively ([113]Fig. 2B). [114]Fig. 2 also shows
the results of the effects of different concentrations of naringenin
combined with MPTP treatment on neurotoxicity. Assessment of the motor
function using the flies' ability to climb (negative geotaxis) revealed
that, MPTP impairs climbing ability, consistent with neurodegenerative
damage ([115]Fig. 2C). Naringenin helped restore motor function
impaired by MPTP, with the most effective improvement seen at moderate
doses. Higher doses do not seem to provide additional benefits. The
basal AChE enzyme activity in flies fed with a normal diet was
0.96 ± 0.16 nmol/min/mg protein. The addition of MPTP to the diet
reduced this rate by 20.8 % to 0.76 ± 0.09 (P < 0.05) ([116]Fig. 2D).
In the presence of naringenin alone, AChE activities was significantly
increased to 1.31 ± 0.004 (P < 0.05) at concentrations of 100 µM.
However, the flavonoid restored MPTP-induced inhibition of AChE to
1.06 ± 0.08 and 0.96 ± 0.08 (P < 0.05) at concentrations of 100 µM and
300 µM respectively ([117]Fig. 2D). The results show marked improvement
compared to the MPTP-only group, while suggesting again that high
naringenin doses may not be as effective or might even reduce AChE
activity. Naringenin appears to counteract the MPTP-induced reduction
in AChE activity, with moderate doses having the best effect. Higher
doses are less beneficial or potentially harmful.
Fig. 2.
[118]Fig. 2
[119]Open in a new tab
Effects of MPTP and naringenin on survival, locomotor function, and
acetylcholine esterase activity in D. melanogaster. (A) Survival curves
of D. melanogaster treated with different concentrations of MPTP
compared to control flies. MPTP treatments lead to a significant
reduction in survival over the course of 14 days, indicating its
neurotoxic effects. The survival rate in MPTP-treated flies declines
sharply compared to the control group. (B) The survival rate of the
flies on the 12th day. (C) Bar graph representing the beneficial
effects of 300 and 500 μM naringenin on the negative geotaxis behavior
of MPTP-treated flies. Naringenin treatment shows a dose-dependent
improvement in climbing ability, with higher concentrations restoring
motor function more effectively compared to the MPTP-only group. (D)
Acetylcholinesterase (AChE) activity levels in MPTP-treated flies with
and without naringenin. MPTP causes a significant reduction in AChE
activity, indicating its neurodegenerative impact. Naringenin
supplementation shows a protective effect by increasing AChE activity,
particularly at higher concentrations, mitigating the neurotoxic
effects of MPTP. Each bar represents the mean ± SEM for each group,
with statistical significance denoted for comparisons with the control
and MPTP-treated groups (P < 0.05).
3.3. Role of naringenin in oxido-inflammatory modulation in MPTP‑induced
toxicity
In this study, the effects of naringenin on MPTP-induced oxidative
stress are evaluated, specifically focusing on three markers: NO,
H[2]O[2], and protein carbonyls in D. melanogaster as depicted in
[120]Fig. 3. The basal concentration of NO in flies fed with normal
diet was observed as 1.83 ± 0.13 mmol/mg protein. Diet supplementation
with MPTP (500 µM) significantly increased this value by 1.3-fold to
2.45 ± 0.27 mmol/mg protein (P < 0.05, [121]Fig. 3A). Naringenin alone
affected the rate of NO production in fruit flies at concentrations of
100 µM (1.62 ± 0.12 mmol/mg protein) and 300 µM (1.35 ± 0.13 mmol/mg
protein) (P < 0.05). Also, naringenin inhibited the elevation of NO
production caused by MPTP (500 µM) ([122]Fig. 3A). The basal
concentration of H[2]O[2] flies fed with unsupplemented diets was
observed as 15.11 ± 2.46 µmol/mg protein. The addition of MPTP (500 µM)
to the diet increased this value by 1.3-fold to 19.80 ± 1.21 µmol/mg
protein (P < 0.05) ([123]Fig. 3B). No significant change was observed
in the levels of H[2]O[2] in flies treated with naringenin alone.
However, naringenin at concentrations of 100 µM (15.30 ± 0.61 µmol/mg
protein) and 300 µM (13.28 ± 1.16 µmol/mg protein) inhibited the
elevation of H[2]O[2] in flies receiving both the flavonoid and MPTP
diet supplementation ([124]Fig. 3B). For protein carbonyl production,
basal levels in flies fed with normal diet was observed as
1.32 ± 0.14 mmol/mg protein. Diet supplementation with MPTP (500 µM)
significantly increased this value by 1.3-fold to 1.77 ± 0.20 mmol/mg
protein (P < 0.05, [125]Fig. 3C). Naringenin alone affected the rate of
protein carbonyl production in fruit flies at concentrations of 100 µM
(1.08 ± 0.06 mmol/mg protein) and 300 µM (0.81 ± 0.06 mmol/mg protein)
(P < 0.05). Also, naringenin restored the elevated protein carbonyl
production caused by MPTP (500 µM) by 23.7 %. to 1.36 ± 0.05 mmol/mg
protein (P < 0.05) and 1.15 ± 0.18 mmol/mg protein (P < 0.05) at
concentrations of 100 µM and 300 µM respectively ([126]Fig. 3C).
Fig. 3.
[127]Fig. 3
[128]Open in a new tab
Beneficial effects of naringenin on oxidative stress markers in D.
melanogaster exposed to MPTP-induced toxicity. (A) The levels of nitric
oxide (NO) in control, MPTP-treated, and naringenin-treated flies. MPTP
exposure significantly elevates NO levels compared to the control
group. Naringenin treatment at different concentrations shows a
dose-dependent reduction in NO levels, indicating a protective effect
against MPTP-induced oxidative stress. (B) The levels of H₂O₂ in the
various experimental groups. MPTP-treated flies exhibit a marked
increase in H₂O₂ levels, reflecting oxidative damage. Naringenin
supplementation significantly decreases H₂O₂ levels, with higher
concentrations providing better protection, as seen by the reduced
levels compared to the MPTP-only group. (C) Protein carbonyl levels in
control, MPTP, and naringenin-treated flies. MPTP treatment leads to a
notable increase in protein carbonylation, indicative of protein
oxidative damage. Naringenin administration reduces protein carbonyl
levels in a concentration-dependent manner, suggesting naringenin’s
potential in mitigating MPTP-induced protein damage. Each bar
represents the mean ± SEM for each group, with statistical significance
marked for comparisons to the control and MPTP-treated groups
(P < 0.05).
Total thiol, non-protein thiol, as well as catalase (CAT) and
glutathione-S-transferase (GST) enzyme activities were used as markers
of anti-oxidant status in this study. [129]Fig. 4 shows that,
naringenin ameliorates the MPTP-induced decrease levels of total thiol
and non-protein thiol as well as CAT and GST enzyme activities in D.
melanogaster. The basal total thiol levels in flies fed with
unsupplemented diets was observed as 1.39
[MATH: ± :MATH]
0.36 µmol/mg protein. The addition of MPTP (500 µM) to the diet
depleted total thiol concentration by 44.6 % to 0.77
[MATH: ± :MATH]
0.34 µmol/mg protein (P < 0.05) ([130]Fig. 4 A). No significant
depletion of total thiol was observed in flies treated with naringenin
only. However, naringenin at 100 µM inhibited the reduction in total
thiol levels in flies receiving both the flavonoid and MPTP diet
supplementation ([131]Fig. 4A). With respect to non-protein thiol
levels, basal concentration in flies fed with normal diet was observed
as 0.85
[MATH: ± :MATH]
0.07 µmol/mg protein. Diet supplementation with MPTP (500 µM) decreased
this value by 29.4 % to 0.60
[MATH: ± :MATH]
0.11 µmol/mg protein (P < 0.05, [132]Fig. 4B). Naringenin at
concentrations 100 µM and 300 µM were found to significantly increase
the levels of non-protein thiol when compared with unsupplemented diet.
However, naringenin restored the depletion of non-protein thiol caused
by MPTP to 1.07
[MATH: ± :MATH]
0.05 µmol/mg protein and 0.78
[MATH: ± :MATH]
0.08 µmol/mg protein at concentrations of 100 µM and 300 µM
respectively ([133]Fig. 4B). For the GST activities, basal enzyme
activities in flies fed with normal diet was 0.57
[MATH: ± :MATH]
0.05 µmol/min/mgprotein. The addition of MPTP to the diet reduced this
rate by 42.1 % to 0.33
[MATH: ± :MATH]
0.05 µmol/min/mgprotein (P < 0.05) ([134]Fig. 4 C). In the presence of
naringenin alone, GST activities were significantly increased to 0.70
[MATH: ± :MATH]
0.08 µmol/min/mgprotein and 0.84
[MATH: ± :MATH]
0.04 µmol/min/mgprotein (P < 0.05) at concentrations of 100 µM and
300 µM respectively. Moreover, the flavonoid restored GST inhibition
observed in MPTP treated flies to 0.57
[MATH: ± :MATH]
0.06 µmol/min/mgprotein and 0.61
[MATH: ± :MATH]
0.08 µmol/min/mgprotein (P < 0.05) at concentrations of 100 µM and
300 µM respectively ([135]Fig. 4 C). Similarly, the basal CAT enzyme
activities in flies fed with normal diet was 0.80
[MATH: ± :MATH]
0.09 mmol of H[2]O[2] consumed/min/mg protein. The addition of MPTP to
the diet reduced this rate by 35 % to 0.52
[MATH: ± :MATH]
0.04 mmol of H[2]O[2] consumed/min/mg protein (P < 0.05) ([136]Fig.
4D). In the presence of naringenin alone, catalase activities were
significantly increased to 0.92
[MATH: ± :MATH]
0.06 mmol of H[2]O[2] consumed/min/mg protein and 1.12
[MATH: ± :MATH]
0.06 mmol of H[2]O[2] consumed/min/mg protein (P < 0.05) at
concentrations of 100 µM and 300 µM respectively. Moreover, the
flavonoid restored catalase inhibition observed in MPTP treated flies
to 0.79
[MATH: ± :MATH]
0.06 mmol of H[2]O[2] consumed/min/mg protein and 0.97
[MATH: ± :MATH]
0.03 mmol of H[2]O[2] consumed/min/mg protein (P < 0.05) at
concentrations of 100 µM and 300 µM respectively ([137]Fig. 4D).
Fig. 4.
[138]Fig. 4
[139]Open in a new tab
The MPTP and Naringenin on antioxidant status in D. melanogaster
exposed to MPTP-induced toxicity (A) The level of Total protein thiol
oxide in control, MPTP-treated, and naringenin-treated flies. (B)
Non-protein thiol level (C) Catalase activity in control, MPTP-treated,
and naringenin-treated flies and (D) Glutathione-S-transferase enzyme
activity. Values are expressed as mean ± standard deviation (n = 5).
Each bar represents the mean ± SEM for each group, with statistical
significance marked for comparisons to the control and MPTP-treated
groups (P < 0.05).
3.4. Targets network and protein-protein interactions
Hub genes that may drive the ameliorative potential of naringenin in
MPTP-induced parkinsonism were identified through gene mining, target
prediction and network construction as depicted in [140]Fig. 5. The
Venn diagram shows targets relevant to MPTP-induced toxicity (MIT) and
the target genes in naringenin-induced protection (NIP) in
Parkinsonism. The MIT targets contain 267 genes that are specifically
targeted in MPTP-induced Parkinsonism but are not targeted by
naringenin. The NIP targets includes 1595 genes targeted by naringenin,
which are not directly involved in the MPTP-induced Parkinsonism model.
The overlap between the two target sets contains 54 genes that are
common to both MPTP-induced Parkinsonism and naringenin amelioration.
Evaluation of the Protein-Protein Interaction (PPI) network of the
common target genes revealed 54 nodes and 186 edges, where nodes
represent proteins and edges represent interactions between them. The
interconnected nature of the network suggests a complex web of
interactions among the common target genes. The network shows a variety
of interaction types, indicated by the different colors of the edges,
which represent various forms of interaction data, such as physical
binding, co-expression, or pathways. Specific proteins are central and
highly connected within the network, acting as hubs. These hub proteins
may play critical roles in the overall function and stability of the
network. Proteins including DRD4, DRD2, NFKB1, MAOB, MAPK14, and CYP2A6
are prominently connected, suggesting that they may be central to the
shared pathways between Parkinsonism and naringenin's ameliorative
effects.
Fig. 5.
[141]Fig. 5
[142]Open in a new tab
Protein-Protein Interaction (PPI) Network of Genes and Identification
of Hub Genes in of MPTP-induced toxicity (MIT) and Naringenin-induced
protection (NIP) in parkinsonism model. The Venn diagram illustrate the
common genes. The interaction network (middle section) visualizes the
relationships among these proteins, with edges representing
interactions. The inset on the right zooms into the hub genes, which
are identified based on their high degree of connectivity in the
network.
Identification, visualization and ranking of the hub genes based on
Maximal Clique Centrality (MCC) algorithm using cytoHubba, with Maximal
Clique Centrality (MCC) algorithm revealed the hub targets as shown in
[143]Fig. 5. The hub genes are represented as nodes with different
sizes and colors, indicating their importance in the network. In
addition to MCC, more topological metrics were computed using various
algorithms as presented in [144]Table 1.
Table 1.
Topological metrics of the extracted hub genes.
Nodes Protein names MCC k CC EPC BottleNeck EcCentricity BC
DRD2/D2R Dopamine Receptor D2 2185 12 27.25 22.30 4 0.309 141
MAOB Monoamine Oxidase B 2184 11 26.91 20.90 7 0.231 105
SLC6A4 Serotonin Transporter 2180 12 28.08 20.92 1 0.309 184
SLC6A3/DAT Dopamine Transporter 2168 10 23.83 18.77 1 0.231 26
DRD4/D4R Dopamine Receptor D4 2162 9 22.17 13.53 1 0.231 9
CHRNA4 Cholinergic Receptor Nicotinic Alpha 4 Subunit 1446 8 22.42
18.06 1 0.231 7
DRD3/D3R Dopamine Receptor D3 1440 7 21.50 16.55 1 0.231 0.3
SLC18A2/ VMAT2 Vesicular Monoamine Transporter 2 720 14 21.00 21.82 1
0.231 0
CHRM2 Muscarinic Acetylcholine Receptor M2 720 6 21.00 15.92 1 0.231 0
MMP9 Matrix Metallopeptidase 9 682 21 33.50 25.68 9 0.308 259
NFKB Nuclear Factor Kappa B 554 19 32.83 25.14 2 0.308 264
CSTB Cystatin B 388 12 27.92 22.68 3 0.231 82
ACE Angiotensin-Converting Enzyme 383 16 19.58 24.95 10 0.231 1
MMP2 Matrix Metallopeptidase 2 306 14 29.83 24.33 1 0.308 77
MMP1 Matrix Metallopeptidase 1 246 4 25.50 19.79 2 0.308 10
[145]Open in a new tab
NB: MCC (Maximal Clique Centrality), k (Degree Centrality), CC
(Closeness Centrality), EPC (Edge Percolation Centrality), BC
(Betweenness Centrality)
The results of the topology analysis of the hub genes provide valuable
insights into the structure and importance of these genes within the
network related to MPTP-induced toxicity and naringenin-induced
amelioration. The DRD2/D2R, the topmost protein based on the MCC value
(2185), indicate a very high maximal clique centrality; and thereby act
as a key connector in the network. Its Degree (k) value (12) reflects
its number of direct interactions with other genes. A high EPC value
(22.30) of this protein suggests its significant role in maintaining
network connectivity. The relatively high EcCentricity value (0.309)
implies that its distance to the farthest node in the network is
moderate, while its Betweenness value (141) indicates a significant
control over the flow of information within the network. The MAOB
ranked second after DRD2 based on the MCC value (2184). Although this
value is slightly lower, the BottleNeck value (7) shows a more
prominent role in controlling flow compared to DRD2. The MCC value of
SLC6A4 (2180) closely follows DRD2 and MAOB, while the EcCentricity
(0.309) is similar to DRD2. The MCC value of SLC6A3 (2168) is slightly
lower but still significant. MMP9 exhibited the highest Closeness value
(33.5). DRD4 also maintains maintaining high centrality (MCC = 2162).
3.5. Functional and pathway enrichment of hub targets
It is important to understand the biological and biochemical relevance
of the hub proteins. Therefore, the Gene Ontology (GO) enrichment and
pathway analyses were performed. The Biological Process enrichment
analysis shown in [146]Fig. 6A highlights several processes that are
significantly enriched among the hub genes. Response to abiotic
stimulus has the highest level of enrichment. Response to
Oxygen-Containing Compound is also highly enriched. High enrichment in
regulation of transport suggests the involvement of hub genes in
regulating the transport of molecules across cell membranes. The
Cellular Component enrichment analysis of the hub genes, as shown in
[147]Fig. 6B reveals key cellular locations where these genes are most
active. Among the cellular components, Synaptic Membrane has the
highest enrichment, indicating a strong association of the hub genes
with synaptic membranes. In a similar manner, postsynapse is highly
enriched, showing the importance of the hub genes in the postsynaptic
region. A general enrichment within the synapse as a whole was
observed. Strong enrichment of Cytoplasmic Vesicle and Intracellular
Vesicle was observed. [148]Fig. 6C illustrates the fold enrichment of
various molecular functions. The Postsynaptic Neurotransmitter Receptor
Activity is the most enriched. This term involves the function of
proteins that act as receptors for neurotransmitters in the
postsynaptic membrane, particularly in neurotransmission.
Metalloendopeptidase Activity was also highly enriched. Besides the
MMPs, other proteolytic enzymes like ACE and MAOB fall under this
category, playing roles in blood pressure regulation and dopamine
metabolism, respectively. Pathway enrichment of overlapping genes
depicted in [149]Fig. 6D highlights several biological processes and
biochemical pathways that are enriched in the hub genes studied. The
KEGG signaling pathways depicted in [150]Fig. 9 focuses on cocaine
addiction (7 A) and dopaminergic synapse (7B). Several important hub
genes involved in the cocaine addiction and dopaminergic synapse are
highlighted in red. The genes including MAPK, DAT, D2R, VMAT, MAO, and
NF-kB are critical hubs that mediate both the acute effects of cocaine
and the long-term adaptations that lead to addiction.
Fig. 6.
[151]Fig. 6
[152]Open in a new tab
Functional Enrichment Analysis of Naringenin-Targeted Genes in PD. The
figure presents the gene ontology (GO) and pathway enrichment analysis
of genes targeted by naringenin in the context of PD, emphasizing their
biological processes (A), cellular components (B), molecular functions
(C), and KEGG pathways (D). The fold enrichment and false discovery
rate (FDR) significance are color-coded, with red shades representing
the highest significance in all panels.
Fig. 9.
[153]Fig. 9
[154]Open in a new tab
Molecular docking interactions of naringenin and safinamide (reference
drug) with the monoamine oxidase B (MAO-B) enzyme. The center shows the
3D structure of MAO-B (ribbon representation), with the ligands bound
in the active site. Naringenin binds to MAO-B with a binding affinity
of −9.3 kcal/mol, interacting with key residues such as TYR398, LEU171,
and ILE199. Safinamide also exhibits a binding affinity of
−9.3 kcal/mol, engaging residues like LEU171, ILE199, and GLN206. The
lower inset provides a close-up surface view of the binding pocket,
showing both ligands in the active site of MAO-B.
3.6. Docking and interactions of naringenin with dopaminergic and
oxido-inflammatory targets
[155]Fig. 8 compares the molecular docking interactions of Dopamine
Receptor D2 (DRD2) with naringenin and rotigotine, the reference DRD2
agonist. Naringenin had binding score of −8.3 kcal/mol with key
interactions with important amino acid residues including GLU95, LEU94,
LEU183, THR412, VAL91 and PRO405. Rotigotine (9.4 kcal/mol) shows a
higher binding affinity compared to naringenin conducting interactions
with ILE183, VAL91, LEU94, ASP114, PHE389, PHE390 and TYR416. [156]Fig.
9 shows the docking scores and interactions between naringenin and
safinamide (reference drug) with Monoamine Oxidase B (MAO-B). Both
compounds have an identical docking score of −9.3 kcal/mol, indicating
comparable binding affinity. Naringenin conduct non-covalent bonds with
several active site residues including TYR57, TYR398, LEU171 and LEU199
while safinamide made contact points through LEU164, GLY205, GLN206,
ILE316, LEU171 and LEU199. [157]Fig. 10 shows the docking interactions
of MAPK with naringenin and DA-74674. The DA-74674 has a stronger
binding affinity for MAPK than naringenin, as indicated by its lower
docking score. However, the score of −9.3 kcal/mol for naringenin still
shows significant interaction with MAPK, suggesting that it could
modulate the pathway effectively. [158]Fig. 11 depicts the molecular
docking results for the interaction between NF-κB (a transcription
factor) and the two ligands (naringenin and curcumin). Naringenin had a
binding energy of −5.7 kcal/mol and exhibit interactions with ASP206,
HIS141, ALA242, TYR57. The lower binding energy suggests a strong
interaction between naringenin and NF-κB, possibly inhibiting NF-κB
activation. The interactions with amino acids such as ASP206 and HIS141
indicate that naringenin likely engages in hydrogen bonding or other
polar interactions, stabilizing its binding within the active site of
NF-κB. Curcumin, the reference compound had −5.5 kcal/mol interacting
with key amino acid residues including TYR223, ASN244, SER208, VAL219.
Curcumin also demonstrates a significant interaction with NF-κB, though
with a slightly higher binding energy compared to naringenin. Curcumin
forms interactions with residues like TYR223 and ASN244, which could
contribute to its known anti-inflammatory effects through the
inhibition of NF-κB.
Fig. 7.
[159]Fig. 7
[160]Open in a new tab
KEGG pathway mapping of naringenin-targeted genes in dopaminergic
neurotransmission pathway. The figure illustrates the mapping of
naringenin-targeted genes onto KEGG pathways related to cocaine
addiction (A) and dopaminergic synapse (B). Red boxes highlight the
genes impacted by naringenin in these pathways.
Fig. 8.
[161]Fig. 8
[162]Open in a new tab
Molecular docking interactions of naringenin and rotigotin (reference
drug) with the dopamine D2 receptor (DRD2). The center displays the 3D
structure of DRD2 (ribbon representation), with bound ligands shown in
stick representations. Naringenin binds at the active site with a
binding affinity of −8.3 kcal/mol, interacting with key residues such
as GLU95, VAL91, and THR412, forming hydrogen bonds and hydrophobic
contacts. Rotigotin binds with a binding affinity of −9.4 kcal/mol,
engaging residues like ASP114, PHE390, and ILE183. The bottom inset
provides a close-up surface view of the binding pocket with the ligands
docked inside.
Fig. 10.
[163]Fig. 10
[164]Open in a new tab
Molecular docking interactions of naringenin and DA-74674 (reference
drug) with MAPK (Mitogen-Activated Protein Kinase). The central
structure represents the 3D conformation of MAPK (ribbon
representation) with ligands bound to the active site. Naringenin binds
with a docking score of −9.3 kcal/mol, interacting with residues such
as LYS93, ALA91, and MET146 through hydrogen bonds and hydrophobic
contacts. DA-74674 shows a stronger binding affinity of −10.5 kcal/mol,
forming interactions with key residues like LYS93, GLN155, and MET146.
The lower inset provides a detailed surface view of the MAPK binding
pocket, highlighting the positioning of both ligands.
Fig. 11.
[165]Fig. 11
[166]Open in a new tab
Molecular docking interactions of naringenin and curcumin (reference
compound) with the NF-KB. The center shows the 3D structure of NF-KB
(ribbon representation), with the ligands bound in the active site. The
lower inset provides a close-up surface view of the binding pocket,
showing both ligands in the active site of NF-KB.
4. Discussion
Our findings revealed the ameliorative role of naringenin in MPTP-
induced parkinsonism using D. melanogaster experimental model,
biological network exploration and molecular docking simulation. The
beneficial effects of naringenin administration may involve several
mechanisms including suppression of oxido-inflammation and modulation
of dopaminergic signaling pathways in MPTP-induced PD. The hormetic
response observed upon administration of naringenin alone highlights
the optimal dosing range of naringenin in D. melanogaster.
Low-to-moderate doses of naringenin (100 µM to 300 µM) seem to maintain
or improve the survival of the flies. At these concentrations,
naringenin’s effects may have reached an optimum to effectively reduce
the levels of ROS such as NO and H[2]O[2], and boost antioxidant
defense system involving CAT and GST without overwhelming the system or
producing off-target effects. Naringenin is widely reported for its
potent antioxidant properties, which help in scavenging free radicals
and reducing oxidative stress [167][59], [168][60], [169][61], a major
factor in neurodegeneration caused by MPTP. Emran and Islam [170][61]
found that lower doses of naringenin improved cognitive performance and
reduced oxidative stress markers in rodent models of neurodegeneration
whereas very high doses may have diminishing returns or off-target
effects. Increased oxidative stress markers reported at high doses of
narigenin as observed in this study suggests that, it may induce
oxidative damage, which could account for the reduced survival. At
these concentrations, naringenin may interact with multiple cellular
pathways, leading to potential toxicity or reduced effectiveness due to
off-target effects. This study also corroborates the review by Skibola
and Smith [171][62] who noted that, excessive flavonoid supplementation
can lead to imbalanced antioxidant activities and disruption of normal
cellular functions.
This study demonstrates that, while MPTP treatments significantly
reduced survival, motor function (negative geotaxis), and AChE activity
in D. melanogaster, modeling neurodegenerative damage similar to PD,
naringenin improves the motor function, and AChE activity, with lower
doses showing the most pronounced benefits. This suggests that
naringenin can mitigate the neurotoxic effects of MPTP by supporting
neurotransmission (AChE) and motor function, likely through its
antioxidant properties. Co-administration of MPTP and naringenin
further suggests that, naringenin may lose its neuroprotective
potential at higher concentrations, indicating a potential threshold
beyond which it could be ineffective or even harmful. The ameliorative
potential of naringenin through modulation of oxido-inflammatory
pathways and dopaminergic signal pathways is widely reported in other
animal models. Lou, et al. [172][63] reported that, administration of
naringenin in mice prevented PD associated with
6-hydroxydopamine-induced nigrostriatal dopaminergic degeneration and
oxidative stress through mechanism involving nuclear factor E2-related
factor 2/antioxidant response element (Nrf2/ARE). Another study
performed in adult Sprague–Dawley male rats also revealed that,
naringenin ameliorated 6-hydroxydopamine model of PD by protecting the
tyrosine hydroxylase (TH)-positive cells and increasing the level of
dopamine [173][64]. Our study established the involvement of oxidative
damage in D. melanogaster MPTP-induced PD model as indicated by the
levels of NO, H[2]O[2], and protein carbonyls in D. melanogaster.
Elevated NO contributes to nitrosative stress and neuroinflammation
[174][65], [175][66], [176][67] and is associated with protein
nitration, mitochondrial dysfunction, and neuronal damage [177][67],
[178][68]. By lowering NO levels, naringenin may reduce neuronal damage
and inflammation as it is widely reported to modulate neuroinflammatory
pathways by targeting several signal molecules such as
mitogen-activated protein kinase (MAPK) [179][69], suppressor of
cytokine signaling 3 (SOCS-3) [180][70], the signal transducer and
activator of transcription-1 (STAT-1) [181][71] and Nuclear factor
kappa B (NF-κB) [182][72]. Naringenin is known to induce a significant
reduction in P65 (a subunit of NFκB) phosphorylation and nuclear
translocation [183][71]. That is, naringenin can prevent IκB-α
phosphorylation and degradation causing decreased expression and
suppression of NFκB in neuroinflammation as reported by Santa-Cecília,
et al. [184][73].
Furthermore, naringenin ameliorates the MPTP-induced decrease in key
antioxidant markers such as total thiol, non-protein thiol as well as
CAT and GST enzyme activities in D. melanogaster. This suggests that
naringenin helps replenish the thiol pool and counters the oxidative
damage caused by MPTP. Naringenin significantly ameliorates the loss of
non-protein thiols, with higher concentrations showing greater
restorative effects. This indicates that naringenin helps maintain
intracellular GSH levels, which are crucial for detoxification and
antioxidant defense. Earlier studies using experimental rat models,
revealed that, administration of naringenin caused decreased oxidative
stress markers including H[2]O[2], protein carbonyls, 4-hydroxynonenal
(4-HNE) and malondialdehyde (MDA) [185][74], and an increased level of
glutathione (GSH), glutathione peroxidase (GPx), GR, GST, SOD, CAT and
choline acetyltransferase enzyme activity [186][75], [187][76]. In
addition, naringenin was reported ameliorate neurotoxicity in
experimental rats by significantly reducing the activities of
mitochondrial complex I–V enzymes as well as mitochondrial membrane
potential [188][77]. Taken together, the study has demonstrated that,
naringenin may exhibit its neuroprotective action through reduced
neurotoxicity, inflammation and oxidative stress as well as increased
antioxidant status in MPTP-induced Parkinsonism in D. melanogaster.
Computational analyses was performed to predict the possible biological
processes, biochemical pathways, and molecular signaling involved in
the ameliorative potential of naringenin. Targets network and
protein-protein interactions analyses, which was focused on exploring
the intricate interactions of naringenin with the MPTP inducible genes
and PD targets within biological networks, revealed 54 common genes and
highlights the complexity of gene interactions and shared molecular
mechanisms that are crucial for both the pathophysiology of PD and the
therapeutic effect of naringenin. The analysis reveals the network’s
diversity of interactions (physical, co-expression, genetic
interactions, etc.) indicating a multi-faceted approach to regulation
and impact of naringenin. The network revealed the interconnectedness
of dopaminergic signaling, neurotransmitter transport systems and
oxido-inflammatory pathways as key areas influenced by naringenin,
potentially offering therapeutic avenues. The hub genes identified are
DRD2/D2R, MAOB, SLC6A4, SLC6A3/DAT, DRD4/D4R, CHRNA4, DRD3/D3R,
SLC18A2, CHRM2, MMP9, NFKB, CSTB, ACE, MMP2, and MMP1. The topology
metrics of these hub genes in the PPI network provided valuable
insights into the structure and importance of these genes within the
network. Few hub genes identified, particularly DRD2, MAOB, SLC6A4, and
MMP9, exhibit significant centrality and connectivity within the
network, indicating their critical roles in the mechanism. These genes
are not only highly interconnected but also strategically positioned to
control the flow and stability of information within the network,
making them potential key targets for therapeutic strategies in
Parkinsonism. The DRD2 which was highlighted as a major hub, plays a
critical role in dopaminergic signaling and is crucial in PD pathology
[189][78]. The DRD4 similar to DRD2, is involved in dopaminergic
signaling. The MAOB, another significant hub gene, is involved in the
breakdown of dopamine and is often implicated in PD [190][79]. The
SLC6A3 (Dopamine Transporter, DAT) gene encodes the dopamine
transporter and is crucial in dopamine reuptake and clearance from
synaptic spaces. Its regulation is essential for maintaining dopamine
levels, making it a critical player in Parkinsonism. Other Hub Genes
including SLC6A2 and SLC6A4 are part of the solute carrier family,
involved in neurotransmitter transport [191][80], indicating that
naringenin might influence a broad range of neurotransmitter systems
beyond dopamine.
Enrichment of the hub genes in the various biological processes
suggests that the hub genes are central to neuroprotective mechanisms,
particularly against oxidative stress, chemical toxins, and
dysregulated transport systems. Damaged mitochondria produce ROS, which
leads to oxidative stress, causing damage to cellular structures like
proteins, lipids, and DNA [192][81]. This mitochondrial impairment,
along with defective mitophagy (the process of removing damaged
mitochondria), contributes to neuronal degeneration [193][82]. In PD,
various environmental chemical toxins contribute to dopaminergic neuron
death through induction of oxidative stress, making this biological
process crucial in understanding the disease mechanism [194][83],
[195][84]. In addition, high enrichment in regulation of transport
suggests the involvement of hub genes in regulating the transport of
molecules across cell membranes. Dysregulated transport of dopamine and
other neurotransmitters is a hallmark of PD, particularly involving the
SLC6 family of transporters including SLC6A3, SLC6A4, which are key
regulators of neurotransmitter homeostasis [196][85], [197][86]. The
hub genes collectively underscore the complex interplay between
dopaminergic, serotonergic, cholinergic, antioxidant and inflammatory
pathways in MPTP-induced toxicity and naringenin-induced
neuroprotection. This further supports the widely reported antioxidant
potential of naringenin in PD and other neurodegenerative disorders
[198][87], [199][88], [200][89].
Cellular component enrichment of the hub genes indicate that they are
primarily localized and most active in synaptic regions, the plasma
membrane, and associated vesicular components. This suggests their
critical roles in synaptic transmission, neurotransmitter regulation,
and neuronal communication, all of which are essential for proper
dopaminergic function. Enrichment in the synaptic regions and membranes
is particularly significant in the context of PD, where synaptic
dysfunction, particularly in dopaminergic neurons, is a major
pathophysiological factor. Genes like SLC6A3 and SLC6A4 (dopamine and
serotonin transporters, respectively) are critical to synaptic function
[201][90]. The plasma membrane, especially in neurons, is key to
maintaining ion gradients and facilitating neurotransmitter release and
uptake. Genes involved in neurotransmitter transport (SLC6A3, SLC6A4)
and receptors (DRD2, DRD3) are central to this function. Dopamine
receptors (DRD2, DRD4) and transporters (SLC6A3, SLC18A2) are integral
components of the membrane, regulating dopamine dynamics in neurons.
Genes like SLC18A2, the gene that encodes vesicular monoamine
transporter 2 (VMAT2) are involved in packing neurotransmitters into
vesicles, essential for synaptic transmission [202][91]. Disruption of
vesicular trafficking is implicated in PD pathology, especially in
dopamine release [203][92]. Naringenin is known to enhance synaptic
plasticity, the ability of neurons to strengthen or weaken their
connections based on activity [204][87], [205][93], [206][94]. This is
vital for learning and memory, and naringenin’s positive impact on
synaptic plasticity could explain its cognitive-enhancing effects in
neurodegenerative diseases and brain injury models. Taken together, the
enrichment in synaptic components and vesicles points to their
involvement in processes like neurotransmitter release, synaptic
plasticity, and potentially in the pathogenesis of neurodegenerative
disorders like PD.
Molecular function enrichment of the hub genes revealed that they are
primarily involved in neurotransmitter receptor activity, enzyme
regulation (including metalloproteinases and neurotransmitter-degrading
enzymes), and binding functions related to cellular signaling. These
functions are crucial in the context of PD, where neurotransmitter
imbalance, oxidative stress, and neuroinflammation are prominent
[207][95], [208][96]. The postsynaptic neurotransmitter receptor
activity involves the function of proteins that act as receptors for
neurotransmitters in the postsynaptic membrane, particularly in
neurotransmission. Genes linked to dopamine (e.g., DRD2, DRD3, DRD4)
and acetylcholine receptors (e.g., CHRNA4, CHRM2) are key players here,
as they are vital for proper synaptic signaling. Neurotransmitter
Receptor Activity is a broader category that include the activity of
receptors that bind neurotransmitters such as dopamine, serotonin, and
acetylcholine, relevant to genes like SLC6A3 (dopamine transporter),
SLC6A4 (serotonin transporter), and CHRM2 (muscarinic receptor). The
pathway enrichment analysis revealed the top enriched pathways include
those related to dopaminergic neurotransmission (cocaine addiction,
dopaminergic synapse), inflammatory signaling (IL-17, T cell receptor
signaling), and metabolic processes (cytochrome P450, fluid shear
stress, atherosclerosis). Cocaine Addiction pathway map generally
involves neurotransmitter signaling, particularly dopamine. Hub genes
including DRD2, DRD3, and SLC6A3 (dopamine transporter) are likely
involved here. In PD, dopamine dysregulation plays a significant role,
and this pathway suggests that addiction-related dopamine signaling may
overlap with mechanisms affected in PD. The Cytochrome P450 enzymes are
involved in the metabolism of various drugs, and genes like MAOB and
SLC6A4 (serotonin transporter) could play roles in drug metabolism and
neurotransmitter processing. This pathway indicates that altered drug
metabolism indicated by cytochrome P450 activity might be significant
in MPTP-induced parkinsonism which can be might modulated by
naringenin, improving drug metabolism and reducing neurotoxicity.
Inflammatory responses driven by IL-17 Signaling Pathway are implicated
in the pathway analysis. Neuroinflammation plays a key role in PD
progression. Microglia, the brain's resident immune cells, become
activated in response to neuronal injury or the presence of
alpha-synuclein aggregates. While microglial activation is initially
protective, chronic activation leads to the release of pro-inflammatory
cytokines (e.g., TNF-α, IL-1β) and ROS, exacerbating neuronal damage
[209][97], [210][98]. Emerging evidence suggests that systemic immune
system dysregulation may also contribute to PD pathogenesis, as
increased levels of peripheral inflammatory markers have been detected
in patients with PD[211][99]. This could be linked to the hub NFKB
which plays a central role in inflammatory responses. In addition, T
cell signaling pathway plays a role in the immune response is
implicated which may involve genes like NFKB and MMPs central to immune
and inflammatory responses. Naringenin may modulate T cell responses,
reducing neuroinflammation and potentially protecting against disease
progression. Microglia are the immune cells of the central nervous
system and become activated during neuroinflammation, which is a
hallmark of neurodegenerative diseases. Naringenin is known to exhibit
anti-inflammatory potential by inhibiting microglial activation
[212][100]. It can inhibit overactivation of microglia and astrocytes,
thereby reducing the production of pro-inflammatory cytokines (such as
TNF-α, IL-1β, and IL-6) and nitric oxide (NO) [213][94]. This helps to
prevent chronic neuroinflammation and its associated neuronal damage.
Naringenin is also known to inhibit the NF-κB (nuclear factor kappa B)
signaling pathway, which is a key regulator of inflammation [214][101].
By blocking the nuclear translocation of NF-κB, naringenin reduces the
expression of pro-inflammatory genes, thereby attenuating inflammation
in the brain.
Dopaminergic Synapse pathway is critical in PD, as it involves dopamine
synthesis, release, and signaling. Genes such as DRD2, DRD3, DRD4,
SLC6A3, and MAOB are involved in dopaminergic synapse function.
Naringenin’s effect on this pathway could help restore dopaminergic
signaling, potentially improving motor symptoms associated with
Parkinsonism. Also, neuroactive ligand-receptor interaction pathway
including interactions between neurotransmitters and their receptors is
implicated in this study. Genes involved in dopamine, serotonin, and
acetylcholine signaling are likely enriched in this category, relevant
to DRD2, SLC6A3, SLC6A4, and CHRNA4. In general, naringenin’s
neuroprotective role may involve restoring dopamine balance, reducing
neuroinflammation, and improving vascular and metabolic health. The
pathways highlighted suggest overlapping mechanisms between
Parkinsonism pathology and other diseases or conditions, underscoring
the complexity of neurodegeneration and the potential multi-target
effects of naringenin. Visualization of the dopaminergic
neurotransmission pathway map viz: cocaine addiction and dopaminergic
synapse revealed the central role of the hub genes such as DAT, MAPK,
DRD2/D2R, VMAT, MAO and NF-kB. The KEGG dopaminergic pathway
illustrates the complex regulation of dopaminergic signaling and how
various proteins various genes are involved in the modulation of the
synthesis, release, action, and degradation of dopamine.
While network pharmacology provides a system-wide perspective of
drug-target interactions by examining the interconnected nature of
biological pathways and networks, molecular docking offers detailed
insights into the specific interactions between drugs and their targets
at the atomic level. To clarify such interaction, important hub genes
that show centrality and connectivity within the gene network and that
are suggested to play important role in the dopaminergic
neuroprotection were docked with naringenin. The DRD2 and MAOB
corresponding to dopaminergic targets as well as MAPK and NFKB in the
oxido-inflammatory process are not only suggested to be strategically
positioned to control the flow and stability of information within the
network, they are involved various biological, cellular and molecular
processes that may underlie neuroprotective potential of narigenin
making them potential key targets for therapeutic strategies in PD. In
this study, 4 targets were docked with naringenin in comparison with
their respective cocrystalized/reference drugs. DRD2 exhibits a
moderately strong binding affinity for naringenin, suggesting that
naringenin may effectively bind and potentially modulate the receptor
in a biological context. The higher binding affinity of rotigotine
compared to naringenin is expected since rotigotine is an established
dopaminergic agonist used in the treatment of PD. The more negative
docking score indicates stronger binding to the receptor, making it a
more potent activator of DRD2. Both compounds engage in similar
hydrophobic interactions with residues like VAL91, LEU94, and ILE183.
However, rotigotine benefits from additional interactions, such as π-π
stacking with PHE389/390 and hydrogen bonding with ASP114 and TYR416,
making its overall binding more stable. The binding affinity of
naringenin suggests it could contribute to dopaminergic modulation,
supporting its potential neuroprotective effects, especially in
complementary or alternative treatment strategies targeting PD. Docking
MAO-B with the ligands shows that, naringenin had identical binding
affinity as compared to safinamide suggesting that it could be as
effective as safinamide in inhibiting MAO-B. This implies that
Naringenin has strong potential as an alternative or adjunct therapy to
traditional MAO-B inhibitors like Safinamide. The two compounds share
some common MAO-B interactions, particularly with residues LEU171 and
LEU199, which help stabilize both compounds in the hydrophobic binding
pocket of MAO-B. While Naringenin engages with TYR57 and TYR398,
Safinamide forms additional interactions with GLY205, GLN206, and
ILE316, suggesting slightly more diverse contact points, which could
translate to nuanced differences in their inhibitory mechanisms. Both
compounds exhibit strong binding to MAO-B, supporting their role in the
inhibition of dopamine degradation. Naringenin shows promise as a
natural compound with similar efficacy to Safinamide, a clinically used
drug. As described earlier, MPTP is metabolised to MPP+ by the
monoamine-oxidase B (MAO-B), which is then selectively taken up by the
dopaminergic neurons, thus causing their death [215][2]. In the brain,
MPTP. Inhibiting MAO-B would impede MPTP uptake as well as contribute
to higher dopamine levels, which is crucial for alleviating the motor
symptoms of PD. Given the strong binding of naringenin and its natural
origin, it could be a valuable candidate for further investigation in
PD therapy, potentially complementing or offering an alternative to
traditional MAO-B inhibitors.
Naringenin's interaction with key residues (such as Lys93 and Met146)
of the active site of MAPK and the relatively strong docking score of
−9.3 kcal/mol suggest that it could effectively modulate MAPK
signaling. This interaction may contribute to its potential therapeutic
effects in MPTP-induced PD, offering neuroprotection and reducing
neuronal damage. Naringeni interacts with Lys93, Val78, Ile70, Ala91,
and Met146 in MAPK through multiple hydrogen bonds and hydrophobic
interactions. The Lys93 and Ala91 likely provide stabilizing hydrogen
bonds. Hydrophobic interactions with Val78, Ile70, and Met146 anchor
Naringenin in the binding site. This suggests that Naringenin has a
stable binding within the MAPK active site, which might contribute to
its potential inhibitory effect on MAPK signaling. In PD, inhibition of
MAPK pathways has been linked to reduced neuroinflammation and
protection against neuronal death, which is crucial in mitigating
disease progression. MAPK signaling is involved in regulating cell
responses to oxidative stress and apoptosis, both of which are
important in the pathology of PD. Naringenin's ability to bind MAPK
could contribute to its neuroprotective effects by modulating this
pathway, potentially reducing neuroinflammation and protecting
dopaminergic neurons from degeneration. Both naringenin and curcumin
may exert neuroprotective effects by modulating the NF-κB pathway,
which is implicated in neuroinflammation, and the progression of PD.
Naringenin's slightly more favorable binding energy suggests it could
be an effective modulator of NF-κB, potentially reducing inflammation
and oxidative stress in MPTP-induced PD models. Thus, the docking
results highlight naringenin as a promising candidate for attenuating
NF-κB activity and provide a mechanistic rationale for its ameliorative
role in neuroinflammatory conditions like PD.
5. Conclusion
This study focused on probing the neuroprotective potential of
naringenin in an MPTP-induced D. melanogaster model of PD, integrating
experimental findings with computational insights. Our results
demonstrate that naringenin exhibits hormetic behavior, where
low-to-moderate doses confer significant neuroprotection. These effects
are mediated through antioxidant, anti-inflammatory, and dopaminergic
pathways, with optimal dosing playing a crucial role in efficacy.
Network pharmacology and molecular docking analyses support the
interactions of naringenin with key molecular targets, further
supporting its potential as a therapeutic candidate for PD. Despite
these promising findings, further research is necessary to enhance
their translational relevance. Rigorous clinical trials are needed to
validate naringenin’s neuroprotective effects in PD patients and
establish its optimal dosing in humans. Also, experimental validation
of its interactions with key molecular targets identified through
computational studies will provide deeper mechanistic insights.
Additionally, investigating the long-term effects of naringenin
supplementation and its precise dose-response relationship will be
essential for defining its therapeutic window and potential clinical
applications.
CRediT authorship contribution statement
Ogunyemi Oludare Michael: Writing – review & editing, Writing –
original draft, Visualization, Software, Methodology, Investigation,
Formal analysis. Okonta Clive: Writing – review & editing, Writing –
original draft, Methodology, Investigation, Formal analysis, Data
curation. Abolaji Amos Olalekan: Writing – review & editing,
Validation, Supervision, Resources, Project administration,
Investigation, Conceptualization. Olabuntu Babatunde: Visualization,
Software, Methodology, Formal analysis, Data curation.
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.
Acknowledgements