Abstract
Background and objectives
On account of the long-term inflammatory microenvironment, diabetic
wounds are challenging to heal in which advanced glycation end products
are considered important factors hindering the healing of diabetic
wounds. Gum Arabic has demonstrated significant potential in the
treatment of various diseases owing to its anti-inflammatory and
antioxidant properties. Nonetheless, there is still insufficient
research on the role of Arabic gum in facilitating diabetic wounds
healing and its mechanisms. This study aims to investigate the
pharmacological targets and therapeutic mechanisms of Arabic Gum on
diabetic wound healing by adopting network pharmacology, molecular
docking, and experimental validation.
Methods
Key active components of Arabic Gum and disease targets were identified
through network pharmacology and bioinformatics. GO/KEGG enrichment was
performed to identify critical pathways. Cytoscape and AutoDock were
used for targets prediction and molecular docking validation. In vitro,
Transwell assay and tube formation assay were performed to evaluate the
effect of Arabic Gum on human fibroblasts migration and human umbilical
vein endothelial cells angiogenesis. Western blotting analyzed
Pro-caspase-1, ASC, NLRP3 and NF-κB pathway-related proteins. In vivo,
a full-thickness diabetic wound model was established. Histological
changes were assessed via H&E and Masson’s staining, oxidative stress
levels through DHE staining, inflammation levels with IL-1β, CD68 and
CD206 staining, angiogenesis and cell proliferation levels were
assessed by CD31 and Ki67 staining. The levels of pathway-related
proteins were analyzed by NLRP3 and Phospho-NF-κB P65 staining.
Results
Network pharmacology analysis identified key targets, encompassing
HSP90AA1, STAT3, and PRKCB, involved in the AGEs-NF-κB-NLRP3 signaling
axis. Molecular docking demonstrated strong binding affinity between AG
components and these targets. In vitro, AG lessened AGEs-induced
activation of the NLRP3 inflammasome via modulation of the NF-κB
pathway and reinforced cell migration and angiogenesis. In vivo,
AG-treated diabetic wounds exhibited accelerated healing, with
augmented collagen deposition, lowered oxidative stress and
inflammation, and strengthened cell migration and angiogenesis. AG
promotes diabetic wound healing by modulating the AGEs-NF-κB-NLRP3
axis, exerting anti-inflammatory, antioxidant, pro-angiogenic, and
cell-proliferative effects.
Conclusion
This study provides new insights into diabetic wound repair and
suggests that AG is a promising therapeutic agent for improving
diabetic wound healing.
Keywords: diabetic wound healing, Arabic gum, network pharmacology,
advanced glycation end products, AGEs-NF-κB-NLRP3 axis
Graphical Abstract
[44]graphic file with name FPHAR_fphar-2025-1528880_wc_abs.jpg
1 Introduction
For the time being, over 537 million adults (aged between 20 and 79)
across the globe are suffering from diabetes, which is a figure
anticipated to heighten to 643 million by the year of 2030 ([45]Ong et
al., 2023). Chronic wounds bound up with diabetes represent one of the
most prevalent complications of the disease, with approximately 1 in 6
individuals with diabetes will experience such wounds. Diabetic wounds
are linked to a significantly elevated risk of limb amputation and
increased mortality rates. Research indicates that individuals with
diabetic wounds face a 50%–68% higher risk of mortality over a
five-year period ([46]Jiang et al., 2023). Presently, existing
treatment modalities for diabetic wounds, including debridement and
wound offloading, have demonstrated inadequate efficacy, underscoring
the necessity for the development of more effective management
strategies for these wounds ([47]McDermott et al., 2023; [48]Wang et
al., 2024).
At both the microvascular and macrovascular levels, complications are
primary contributors to illness and death among individuals with type 2
diabetes. Notwithstanding the complexity to comprehend the
pathophysiology of type 2 diabetes, cutting-edge glycation end products
(AGEs) are regarded as significant factors that push ahead the
advancement of diabetes and the emergence of its related complications
([49]Lee et al., 2022). It is believed that diabetic complications
primarily arise from uncontrolled hyperglycemia, which brings about the
formation of AGEs.
It’s noteworthy that the formation of endogenous AGEs primarily takes
place via a complex, multi-step process of glycation referred to as the
Maillard reaction. As illustrated by growing evidence, in the context
of chronic diabetes, sustained hyperglycemia gives rise to heightened
levels of AGEs in the blood. These AGEs, by binding to their receptor
known as RAGE, trigger a cascade of signaling events. Such events
encompass the generation of reactive oxygen species (ROS),
calcification, and the formation of thrombi in the arterial walls. An
overproduction of ROS can give rise to oxidative stress and
inflammatory reactions, which brings about detrimental influences on
the process of wound healing ([50]Dunnill et al., 2017; [51]Khalid et
al., 2022; [52]Chiu et al., 2023). For this reason, products formed
through advanced glycation contribute to the aging of blood vessels and
associated damage.
Nuclear factor kappa-B (NF-κB) functions as a pivotal transcription
factor, initiating the activation of numerous genes integral to the
modulation of inflammatory responses and is ubiquitous across virtually
all cell types ([53]Aggarwal et al., 2006). Upon exposure to dissimilar
extracellular stimuli, rapid phosphorylation of NF-κB occurs, which in
turn modulates gene transcription. AGEs, a category of external
substances affecting the activation of NF-κB, can reinforce and prolong
signaling pathways, thereby giving rise to inflammatory responses
([54]Li J.-S. et al., 2022; [55]Shu et al., 2023). Aside from that, the
inflammasome that contains the nucleotide-binding domain (NBD),
leucine-rich repeat (LRR), and pyrin domain (PYD)-bearing protein 3
(NLRP3) serves as a crucial mediator within innate immune responses.
Comprising the NOD-like receptor NLRP3, the adaptor protein ASC, and
caspase-1, the NLRP3 inflammasome conducts a paramount role ([56]Fu and
Wu, 2023; [57]Zheng et al., 2023). Both the NLRP3 inflammasome and
NF-κB are crucial in the inflammatory progression of several diseases
([58]Wang et al., 2018; [59]Zhao et al., 2019; [60]Peng et al., 2020),
leading to a prolonged state of chronic inflammation that delays the
wound healing process in diabetes.
Arabic Gum (AG), a natural and thick exudate obtained from the branches
of Acacia seyal and Acacia senegal, is extensively acknowledged by the
U.S. Food and Drug Administration (FDA) as a safe source of dietary
fiber ([61]Al-Jubori et al., 2023). Numerous experimental
investigations have underlined the potential merits of AG in clinical
applications. As reported by [62]Ahmed et al. (2022) and his team, the
antioxidant and anti-inflammatory effects of AG might counteract
oxidative harm, inflammation, and cell death stemmed from exposure to
aflatoxin B1 in animal subjects. [63]Abu-Serie et al. (2021) and her
colleagues evidently illustrated that AG could reduce systemic
oxidative stress and necroinflammatory responses resulting from CCl4
administration. The anti-inflammatory and antioxidant properties of AG
exert beneficial effects on diabetic wounds featured by chronic
inflammation.
Network pharmacology integrates systems biology with network
informatics, which favorably provides profound insights into molecular
mechanisms from an all-round standpoint. It functions as both a
theoretical basis and a technical resource for contemporary drug
development, which not only accelerates the process of identifying
active compounds, but also clarifies drug effectiveness. This
methodology corresponds with the traits of drugs that are
multi-component, multi-targeted, and exhibit synergistic effects
([64]Nogales et al., 2022; [65]Shang et al., 2023). As a consequence,
by utilizing a blend of network pharmacology, molecular docking, and
experimental validation, we delved further into the active ingredients,
possible targets, and molecular mechanisms of Arabic Gum in addressing
diabetic chronic wounds. Initial validation was performed via cellular
and animal experiments, offering instructive guidance for the
subsequent development and application of Arabic Gum in reinforcing the
healing of diabetic chronic wounds.
2 Materials and methods
2.1 Network pharmacology-based analysis
2.1.1 Collection and screening of active chemical composition in Arabic gum
In this research, a search was performed on PubMed utilizing “Arabic
Gum” as our primary keyword to determine the active components of AG
([66]Ashour et al., 2022; [67]Afoakwah et al., 2023). The molecular
designations were submitted to the public chemical database PubChem
([68]https://pubchem.ncbi.nlm.nih.gov/) to acquire the molecular
representations in Canonical SMILES format ([69]Kim et al., 2023). The
molecular structures in.mol 2 format and Canonical SMILES expressions
were then imported into the SwissTargetPrediction database
([70]http://www.swisstargetprediction.ch/) ([71]Daina et al., 2019).
Active targets were recognized grounded in criteria of norm fit >0.9
and the top 15 rankings, separately. Subsequent to the consolidation of
the results and the elimination of duplicates, the potential target
names were standardized with the UniProt database
([72]https://www.uniprot.org/) ([73]UniProt Consortium, 2018).
Ultimately, the information was merged with data from existing
literature.
2.1.2 Collection of the targets of diabetic chronic wound
A keyword search was performed utilizing “diabetic wound” in the
GeneCards database ([74]https://www.genecards.org/) ([75]Rebhan et al.,
1997), the OMIM database ([76]https://www.omim.org/) ([77]Amberger et
al., 2015), and the DisGeNET database ([78]https://www.disgenet.org/)
to discover pertinent targets ([79]Piñero et al., 2020). The outcomes
were consolidated, and duplicate records were eliminated.
2.1.3 Construction the network of the
drug-components-targets-pathways-disease
The main components and potential targets of AG from [80]Section 2.1.1,
the potential targets for diabetic chronic wounds from [81]Section
2.1.2, and the KEGG pathways bound up with diabetic wounds analyzed in
[82]Section 2.1.5 were imported into Cytoscape 3.8.2 to construct a
drug-components-targets-pathways-disease network.
2.1.4 Construction of PPI network of common targets of AG and diabetic wound
The identification of the overlap between the targets of AG active
components and those bound up with chronic wounds in diabetes was
conducted by employing Venny 2.1
([83]https://bioinfogp.cnb.csic.es/tools/venny/). Afterwards, the
overlapping targets were uploaded to the STRING database
([84]https://cn.string-db.org/) ([85]Szklarczyk et al., 2023), where
“Homo sapiens” was selected for the species, and a confidence score
greater than 0.700 was specified, while disconnecting nodes were
hidden. The resulting data was then exported and visualized by adopting
Cytoscape 3.8.2. For the topological analysis of the resultant PPI
network, the CentiScaPe 2.2 plugin in Cytoscape 3.8.2 was utilized
accordingly ([86]Franz et al., 2023). Core targets were determined by
filtering the network through parameters exceeding the calculated
values of betweenness centrality, closeness centrality, and degree.
2.1.5 GO analysis and KEGG pathway enrichment analysis
The primary objectives of AG and chronic wounds associated with
diabetes were uploaded to the DAVID database
([87]https://david.ncifcrf.gov/) ([88]Sherman et al., 2022), selecting
“H. sapiens” as the species. The outcomes were subjected to filtering
and analysis, utilizing a significance threshold of P < 0.05.
2.1.6 Molecular docking
The primary targets identified in [89]Section 2.1.4 were prioritized on
the basis of their degree values, which was arranged in an order from
high to low. Afterwards, the three highest-ranking key targets and
their relevant AG active components were chosen for molecular docking
analysis. The chemical structures of these active components of AG,
sourced from the TCMSP database ([90]Ru et al., 2014), were analyzed by
employing PyMOL 2.6 and AutoDock 1.5.7, whereas the protein crystal
structures predominantly originated from the PDB database ([91]Nawaz et
al., 2023). Calculations of binding energies were performed, and the
resulting data were visualized through PyMOL 2.6.
2.2 In vitro experiment
2.2.1 Materials
Arabic Gum (AG) were purchased from Shanghai Aladdin Biochemical
Technology Co., Ltd. AGE-BSA (AGEs) were purchased from Biogradetech.
All other chemical reagents are of analytical grade.
2.2.2 Cell culture and treatment
Mouse macrophage cells (RAWs) (Thermo Fisher Scientific), human skin
fibroblasts (HSFs) (Fenghui Biotechnology) and human umbilical vein
endothelial cells (HUVECs) (Thermo Fisher Scientific) were cultured in
DMEM medium (Thermo Fisher Scientific), DMEM/F12 medium (Thermo Fisher
Scientific) and 1640 medium (Thermo Fisher Scientific) supplemented
with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin in a
5% CO[2] incubator at 37°C. In accordance with the experimental group
design, they were divided into three groups: the control group (NC
group), the AGEs group, and the AGEs + AG group. The pretreatment was
carried out 24 h in advance, followed by the next experiments.
2.2.3 Cell viability assay
Human skin fibroblasts (HSFs) were seeded into 96-well plates at a
concentration of 1 × 10^4 cells per well. Following exposure to varying
AG concentrations (25, 50, 100, and 200 mg/mL) for periods of 24 and
72 h, 10 μL of CCK-8 solution (Beyotime, Shanghai, China) was
introduced to each well. After a 1-h incubation at 37°C, the absorbance
of each well was recorded at 450 nm. The cell viability in response to
AG was determined by utilizing the following formula:
[MATH:
Cell viabilit
y %=AS−A0
AC−A0×100
% :MATH]
where A [S ]represents the absorbance of cells with AG, A [C
]symbolizes the absorbance of cells and A [0 ]refers to the absorbance
of cell media.
The dose response curve was plotted to compute the 50% (IC 50)
concentration of AG inhibiting cell growth.
2.2.4 In vitro blood compatibility assay
To comprehensively evaluate blood biocompatibility, a method was
utilized in a systematic manner, where rat citrated blood was mixed
with saline in a ratio of 5: 4. A volume of 1 mL from this
saline-diluted blood was incorporated into the AG solution, which was
prepared at a concentration of 25 mg/mL, and subsequently incubated for
1 h at 37°C. By contrast, red blood cells treated with normal saline
served as the control group. After a 5-min centrifugation at 1,000 RPM,
100 μL of the supernatant was transferred into a 96-well plate, and the
optical density was measured at 540 nm by employing a microplate
reader. The formula below was employed to compute the percentage of
hemolysis:
[MATH:
Hemolys
is %=ODS−O<
msub>DBOD
C−ODB<
/mrow>×100% :MATH]
where OD [S ], OD [B ]and OD [C ]are the optical density of sample,
blank (Normal saline treated with RBCs as negative control) and Control
(Triton-X treated with RBCs as positive control) severally.
2.2.5 Transwell assay
The upper chamber was inoculated with HSFs at a density of 2 × 10^4
cells per well. Afterwards, the cells were treated in the lower chamber
for 24 h under a range of group conditions, then fixed by utilizing
formaldehyde, stained with crystal violet, and observed through an
inverted fluorescence microscope for photography. On top of that, cell
scratch assays were conducted under diverse grouping scenarios, with
images captured by adopting an inverted microscope (IX73, Olympus)
after 24 and 48 h.
2.2.6 Tube formation assay
In an effort to assess the angiogenic potential of AG, a tube formation
assay was conducted accordingly. First and foremost, 100 μL of Matrigel
(Corning) was placed in a 96-well plate and allowed to gel at 37°C for
1 h. Afterwards, human umbilical vein endothelial cells (HUVECs) were
seeded onto the Matrigel at a density of 3 × 10^4 cells per well, with
100 μL of media that included various groups: AGEs group, AGEs + AG
group, and a control group with media only. Subsequent to a 6-h
incubation, the development of capillary-like structures was observed
by adopting an inverted microscope (IX73, Olympus). The tube networks
were quantitatively analyzed with the angiogenesis analyzer in ImageJ
software (NIH), measuring parameters such as the number of junctions
and total segment length.
2.2.7 Western blotting
The lysing of cultured cells was carried out by utilizing RIPA buffer
(Beyotime, China) and protease inhibitor (PMSF, Biosharp, China). A
20 g protein sample was separated via a 10% SDS-PAGE technique,
subsequently transferred to polyvinylidene difluoride membranes
(Millipore Sigma). To block the membranes, 5% non-fat milk was applied
at room temperature for 1 h. Following this, immunoblotting was
performed on the separated proteins, which were probed with anti-Pro
Caspase-1 + p10 + p12 Rabbit mAb (ABclonal, China; #[92]A25308,
1:2,000), anti-ASC/TMS1 Rabbit mAb (22,046, 1:6000), anti-NLRP3
(ABclonal, China; #A24294, 1:500), anti-NF-κB p65 mAb (Proteintech,
China; #66535-1-lg, 1:1,000), and anti-Phospho-NF-κB p65 rAb
(Proteintech, China; #82335-1-RR, 1:2000) overnight at 4 °C. The
following day, the membranes underwent rinsing for 10 min with
Tris-buffered saline containing Tween 20, followed by incubation at
room temperature with a peroxidase-conjugated secondary antibody
(Abcam, United Kingdom; ab205718, 1:10,000) (Biosharp, China; BL001A,
1:5,000) for 1 h. Protein bands were visualized by utilizing
strengthened chemiluminescence detection. Quantitative analysis of the
immunoreactive bands was performed by employing ImageJ software. Three
technical and three experimental replicates were conducted.
2.3 In vivo experiment
2.3.1 Preparation of type 2 diabetic rat model
All animal experimentation conducted in this research adhered to the
guidelines sanctioned by the Institutional Animal Care and Use
Committee at the Hubei Provincial Center for Disease Control and
Prevention (IACUC Number: 202,320,189). Type I diabetic rat model was
established in rats in line with previously reported protocols
([93]Huang et al., 2024). A group of male Sprague-Dawley (SD) rats
weighing approximately 250 ± 25 g underwent a 1-week acclimatization
period. Following an 18-h fasting period, the rats were administered
with injection of streptozotocin (STZ) at a dose of 75 mg/kg daily for
three consecutive days. Afterwards, the blood glucose levels of the
rats were monitored every 3 days over a span of 3 weeks. Rats
exhibiting a stable glucose level exceeding 16.6 mM were classified as
having successfully developed a type 2 diabetes model. The animals were
then randomly assigned for additional experiments.
2.3.2 Diabetic wound healing test
Animals were anesthetized by sevoflurane inhalation, and the dorsal of
rats were shaved or depilated. A circular biopsy punch with a diameter
of 15 mm was employed to induce full-thick wounds on the dorsal of
rats. Diabetic wounds were received dissimilar treatments, comprising
1) Blank control group (negative group); 2) Comfeel ^® hydrocolloid
dressing group (HCD group, No.1 positive control group); 3) YOUZHI ^®
medical chitosan dressing group (MCH group, No.2 positive control
group); 4) Acacia Gum Group (AG Group), which topically uses four
diverse materials to cover the wound, next, Tegaderm™ Company then (3M,
USA) covers the wound area and changes it every 3 days. Wounds were
photographed at dissimilar time points during healing process.
Afterwards, wound areas in each group were measured by ImageJ software
(NIH, United States).
2.3.3 Histological analysis
On days 3, 6, and 19 following the injury, we collected and fixed skin
tissues around the wounds for histological examination. With an aim to
assess epidermal regeneration and wound inflammation, we conducted
Hematoxylin & Eosin (H&E) staining. Collagen deposition within the
wound bed was assessed by adopting Masson’s trichrome staining. Aside
from that, we employed DHE and antibodies against IL-1β, CD68, CD206,
CD31, Ki67, NLRP3, and Phospho-NF-κB P65 to analyze tissue oxidative
stress, pro-inflammatory markers, macrophage polarization,
angiogenesis, cell proliferation, inflammasome activity, and NF-κB
pathway activation, severally.
2.3.4 Statistical analysis
Each experiment included a minimum of three independent trials. The
data are presented as mean ± standard deviation (SD). Statistical
analyses were performed by employing one-way analysis of variance
(ANOVA) to compare multiple groups, and graphs were generated by
utilizing GraphPad Prism 9.0 (San Diego, CA, United States). P-values
were classified as follows: *p < 0.05, **p < 0.01, ***p < 0.001, and
****p < 0.0001. A P-value of <0.05 is regarded as statistically
significant, whereas a P-value >0.05 is considered not significant
(ns).
3 Result
3.1 Network pharmacology-based analysis
Through a PubMed literature search ([94]Afoakwah et al., 2023), we
identified five active components in AG ([95]Table 1), which primarily
include D-galactose, L-arabinose, L-rhamnose, D-glucuronic acid, and
4-O-methyl-glucuronic acid. The molecular expressions in Canonical
SMILES format were imported into the SwissTargetPrediction database,
yielding a total of 255 corresponding targets.
TABLE 1.
Details of 5 active chemical composition in Arabic Gum (AG) ([96]Ashour
et al., 2022; [97]Afoakwah et al., 2023).
Compound name Molecular function Canonical SMILES Content
D-galactose C[6]H[12]O[6] C(C1C(C(C(C(O1)O)O)O)O)O 32.5%–35.0%
L-arabinose C[5]H[10]O[5] C1C(C(C(C(O1)O)O)O)O 31.7%–53.1%
L-rhamnose C[6]H[12]O[5] CC1C(C(C(C(O1)O)O)O)O 2.7%–16.3%
D-glucuronic acid C[6]H[10]O[7] C1(C(C(OC(C1O)O)C(=O)O)O)O 5.3%–14.0%
4-O-methyl-glucuronic acid C[7]H[12]O[7] COC1C(C(C(OC1C(=O)O)O)O)O
0.8%–5.2%
[98]Open in a new tab
The AG active component targets and diabetic wound targets were
imported into the Venny 2.1 website, which yields 105 intersecting
targets. Aside from that, a Venn diagram was generated ([99]Figure 1B).
The 105 intersecting targets were uploaded to the STRING platform.
Subsequently, a PPI (protein-protein interaction) network was generated
([100]Supplementary Figure S1) subsequent to the removal of
disconnected nodes. Topological analysis of the resulting PPI network
was conducted by utilizing the CentiScaPe 2.2 plugin in Cytoscape
3.8.2. Ultimately, 10 core targets were identified ([101]Figure 1C). It
was observed that AG primarily acts on diabetic wound-related targets
such as HSP90AA1, STAT3, PRKCB, and ESR1.
FIGURE 1.
[102]FIGURE 1
[103]Open in a new tab
Network pharmacology-based analysis. (A)
AG-components-targets-pathways-diabetic wound; (B) Venn diagram of
active ingredients and disease targets; (C) The top 10 core targets
among the intersecting genes; (D) GO analysis of the intersecting genes
between AG and diabetic wound; (E) KEGG analysis of the intersecting
genes between AG and diabetic wound; (F) The combinations of pivotal
compounds and protein targets. In the figure, the red sections
represent the drug molecules, while the yellow portions depict the
protein structures. The middle image shows the overall binding mode
between these two, and the right-side image is an enlarged view of the
molecular and protein interactions, with dashed lines indicating
hydrogen bonds.
On the basis of the lowest P-values, the top 10 biological processes
(BP) include cellular responses to hormone and hormone stimuli,
cellular responses to peptide, peptide hormone, and peptide hormone
stimuli, cellular responses to insulin and insulin stimuli, and
cellular responses to nitrogen compound. The top 5 cellular components
(CC) are the perinuclear region of the cytoplasm, membrane rafts,
membrane microdomain, caveola and plasma membrane rafts. The top 5
molecular functions (MF) are oxidoreductase activity (acting on paired
donors, with incorporation or reduction of molecular oxygen), heme
binding, tetrapyrrole binding, monooxygenase activity, and
oxidoreductase activity. (The bar chart for the top 10 is depicted in
[104]Figure 1D). KEGG pathway analysis identified 150 signaling
pathways (P < 0.05). The top 5 pathways are: pathways in cancer,
serotonergic synapse, chemical carcinogenesis-receptor activation,
PI3K-Akt signaling pathway, and AGEs-RAGE signaling pathway in diabetic
complications (the bubble chart for the top 10 is illustrated in
[105]Figure 1E).
As universally acknowledged, a docking score of <0 kcal/mol suggests
that a compound and target can bind spontaneously, with scores
<−4.25 kcal/mol indicating desirable docking affinity, and scores
<−7 kcal/mol being indicative of strong binding affinity
([106]Gaillard, 2018). For this reason, we obtained the crystal
structures of three target proteins from the PDB database and used BDSV
to predict the locations of the binding pockets and the dimensions of
the grid boxes ([107]Table 2). The key targets from the intersecting
genes were ranked by degree value, while the top three key targets,
along with their corresponding AG active components, were selected for
molecular docking. The three sets of target proteins and compound
molecules were imported into AutoDock Vina, and the binding affinity
values for the best docking poses were calculated ([108]Table 3). All
values were below −4.25 kcal/mol, suggesting satisfactory docking
affinity. As a consequence, molecular docking supports the therapeutic
potential of AG in the treatment of diabetic wounds (Specific
combinations are displayed in [109]Figure 1F).
TABLE 2.
Details of the top 3 targets related to AG-Diabetic wounds, as
identified from the Protein Data Bank (PDB) database.
Target gene PDB ID Protein pocket coordinates Grid box size
HSP90AA1 2QG2 x = 1.043, y = 31.279, z = 28.196 x = 46.0, y = 42.0, z =
46.0
STAT3 6NJS x = −4.846, y = 19.708, z = 24.77 x = 88.0, y = 118.0, z =
92.0
PRKCB 3PFQ x = −59.974, y = 5.387, z = −15.979 x = 86.0, y = 112.0, z =
76.0
[110]Open in a new tab
TABLE 3.
Binding affinity values of the optimal docking conformations of 3 sets
of target proteins and compound molecules.
Protein affinity kcal/mol compound 2QG2 6NJS 3PFQ
D-galactose −4.6 −4.3 −5.3
L-arabinose −5.0 −4.6 −5.1
L-rhamnose −5.5 −5.0 −5.5
D-glucuronic acid −5.7 −4.7 −5.8
4-O-methyl-glucuronic acid −4.7 −5.0 −5.5
[111]Open in a new tab
3.2 In vitro cellular functional assays
3.2.1 Biocompatibility of AG
In some sense, biocompatibility is reckoned as a predominant
requirement for biomaterials in wound dressings ([112]Siavash and
Noursina, 2023). To determine the effects of AG on human cells, cell
viability of HSFs treated with dissimilar concentrations of AG was
measured by employing the CCK-8 assay ([113]Figure 2A). As
conspicuously demonstrated by the experimental findings, at an AG
concentration of 20 mg/mL, the cell viability was 108.6% ± 8.1%. This
concentration was selected for subsequent experiments. Aside from that,
a hemolysis assay was performed ([114]Figure 2B) to assess the
hemocompatibility of AG. The experimental results display that AG has
similar hemocompatibility to the negative control, suggesting its
suitability for human use. The half-maximal inhibitory concentrations
(IC50) of AG at 24 and 48 h were calculated to be 144.6 mg/mL and
41.49 mg/mL, separately ([115]Supplementary Figure S2).
FIGURE 2.
[116]FIGURE 2
[117]Open in a new tab
In vitro cellular functional assays. (A) Cell viability of fibroblasts
treated with AG at different time points (Day 1 and Day 3) for in vitro
proliferation; (B) Percentage of hemolysis induced by 25 mg/mL AG; (C)
Representative images showing the effects of the control group, AGEs
group, and AGEs + AG group on HSFs migration; (D) Quantification of
HSFs migration; (E) Representative images showing the effects of the
control group, AGEs group, and AGEs + AG group on HUVECs tube
formation; (F) Quantification of the number of junction points in
HUVECs tube formation; (G) Quantification of the total segments length
in HUVECs tube formation.
Whether cells can efficiently and quickly migrate to the center of a
wound is one of the decisive factors affecting wound healing
([118]Martin and Nunan, 2015). On that account, a Transwell cell
migration assay was conducted to further look into the effect of AG on
HSFs migration. AGEs substantially inhibited HSFs migration in contrast
to the control group, while the addition of AG effectively reversed
this inhibition ([119]Figures 2C, D). Another major factor hindering
diabetic wound healing is lessened angiogenesis. On this basis, so a
tube formation assay by employing HUVECs was performed to dig into the
effect of AG on angiogenesis. The junction points generated in the
control, AGEs, and AGEs + AG groups were 711.3 ± 128.7, 347.7 ± 25.7,
and 1053 ± 235.9, separately. The total segment lengths were 52,445 ±
4,031, 26,783 ± 5,628, and 65,133 ± 12,975, severally ([120]Figures
2E–G). As these findings suggest, AG can effectively reverse the
negative effects of AGEs on cell migration and angiogenesis, even
surpassing the control group.
3.2.2 AG regulates the NF-κB pathway to reduce AGEs-Induced activation of the
NLRP3 inflammasome
As evidently suggested by the research findings, AGEs can mediate the
activation of the NLRP3 inflammasome through oxidative stress ([121]Wan
et al., 2022). T As a consequence, we delved further into whether AG
could inhibit inflammasome activation by measuring key components of
the NLRP3 inflammasome, encompassing the NOD-like receptor NLRP3, the
adaptor protein ASC, and caspase-1. Treating RAW cells with 300 μg/mL
AGEs activated the NLRP3 inflammasome, giving rise to elevated protein
levels. In contrast to the AGEs-treated group, the AG-treated group
showed a reduction in the protein levels of Pro-caspase-1, ASC, and
NLRP3 by approximately 1.3-fold (p < 0.05), 1.8-fold (p < 0.05), and
5.3-fold (p < 0.01), separately, after 24 h ([122]Figures 3A–E).
FIGURE 3.
[123]FIGURE 3
[124]Open in a new tab
AG regulates the NF-κB pathway to reduce AGEs-induced activation of the
NLRP3 inflammasome. (A) Representative Western blotting images of Pro
caspase-1, cleaved caspase-1 (P12 + P10), ASC, NLRP3 and β-actin; (B–E)
Quantification of fold-change of: (B) Pro caspase-1; (C) cleaved
caspase-1 (P12 + P10); (D) ASC; (E) NLRP3; (F) Representative Western
blotting images of NF-κB p65, Phospho-NF-κB p65 and β-actin; (G)
Quantification of fold-change of Phospho-NF-κB p65.
In an effort to further elucidate the regulatory mechanism of AG on
AGEs-induced cellular dysfunction, we probed into Phospho-NF-κB p65, a
pivotal regulator in the NF-κB signaling pathway. The expression level
of p-p65 was measured by Western blot. In comparison with the control
group, treatment with 300 μg/mL AGEs reinforced p65 phosphorylation (p
< 0.01), thereby activating the NF-κB pathway. Nevertheless,
co-treatment with AG dramatically inhibited the AGEs-induced increase
in p-p65 protein expression ([125]Figures 3F, G). As these findings
demonstrates, AG regulates the NF-κB pathway to reduce AGEs-induced
activation of the NLRP3 inflammasome, thereby exerting a positive
effect on the wound healing process.
3.2.3 In vivo diabetic wound healing effect of AG
The wound healing ability of AG was studied by adopting a
full-thickness skin defect model in diabetic rats ([126]Figure 4A). The
wound size markedly lessened from day 3 and continued to decrease over
time ([127]Figure 4B). In contrast to the control group, the MCH and AG
groups exhibited higher degree of wound closure on days 9, 11, and 16
of treatment. By day 16, nearly all wounds were almost fully closed,
while lesions in the control group remained visibly noticeable. On day
19, the rats were euthanized, and skin tissue from the wound areas of
all four groups was excised for histological evaluation. As revealed by
H&E staining, only the control group’s wound tissue lacked a complete
and continuous epithelial structure by day 19 ([128]Figure 4C).
Nevertheless, the application of AG was bound up with the smallest
wound width ([129]Figure 4C), demonstrating a more rapid healing
process by AG treatment. As demonstrated by masson’s trichrome
staining, the collagen deposition rate in the AG group reached 71.6% ±
4.6%, which was not conspicuously dissimilar from the HCD group and MCH
group, but remarkably different from the control group. This
distinction highlights the potential of AG treatment to strengthen
collagen fiber deposition, thereby giving rise to ameliorated wound
healing and tissue regeneration in the treatment groups.
FIGURE 4.
[130]FIGURE 4
[131]Open in a new tab
In vivo diabetic wound healing effect of AG. (A) Schematic diagram of
the animal experiment protocol; (B) Representative images of wound
healing progression in the control, HCD, MCH, and AG groups; (C)
Representative H&E and Masson’s staining images of wound tissue from
different groups on day 19 post-wounding (The green line segment
denotes the area of the subcutaneous wound. The red arrow symbolizes
the epidermis.); (D) Quantification of collagen deposition in wound
tissues from different groups on day 19 post-wounding.
3.2.4 Histological analysis
An Immunofluorescence analysis was performed on each group of samples
to delve into the effects of AG on ROS generation, inflammatory
infiltration, angiogenesis, and cell proliferation in granulation
tissue. To start with, we assessed ROS levels in the wound sites of the
four groups on days 3 and 6 by employing DHE staining. On day 3, ROS
generation was remarkably lowered in the AG group and these two
positive control groups in contrast to the control group (p < 0.0001)
([132]Figures 5A, D). By day 6, there were no statistically significant
discrepancies between the groups (p > 0.05) ([133]Figures 5A, E). For
another, diabetic wounds, being chronic in nature, are featured by
prolonged inflammation. For this reason, IL-1β staining was conducted
on day 3, while CD68 and CD206 staining was performed on day 6 to
assess inflammatory infiltration in the wound area ([134]Dai et al.,
2021; [135]Xiao et al., 2024). Quantitative analysis further confirmed
that, in comparison with the control group, the AG group substantially
lowered the levels of the inflammatory cytokine IL-1β and facilitated
the polarization of macrophages from the M1 to the M2 phenotype
([136]Figures 5B, F; [137]Supplementary Figures S3A, C). This also
reflects the inflammatory phenotype mediated by the NLRP3 inflammasome.
FIGURE 5.
[138]FIGURE 5
[139]Open in a new tab
Immunofluorescence staining of skin tissues post diabetic wound
healing. (A) Representative images of DHE staining on days 3 and 6
post-wounding; (B) Representative images of IL-1β staining on day 3
post-wounding; (C) Representative images of CD31 and Ki-67 staining on
day 6 post-wounding; (D) Quantification of DHE staining on day 3
post-wounding; (E) Quantification of DHE staining on day 6
post-wounding; (F) Quantification of IL-1β staining on day 3
post-wounding; (G) Quantification of CD31 staining on day 6
post-wounding; (H) Quantification of Ki-67 staining on day 6
post-wounding.
Angiogenesis is another major challenge in diabetic wound healing. CD31
and Ki-67 staining was conducted on days 6 and 19 to evaluate
angiogenic capacity and cell proliferation ([140]Miller et al., 2018;
[141]Liu et al., 2023). CD31 and Ki-67 levels were noticeably higher in
the AG group in comparison with the control group during the early
stages of healing, with a 3.8-fold and 3.5-fold augment, separately
([142]Figures 5C, G, H). In the later stages of healing, only the
control group exhibited high CD31 levels, while no conspicuous
discrepancies in Ki-67 levels were observed between groups. This may be
attributable to the presence of granulation tissue in the control
group, which had not fully epithelialized by day 19 ([143]Supplementary
Figures S3B, D–E). As the testing results demonstrate, AG suggests
exceptional antioxidant, anti-inflammatory, pro-angiogenic, and cell
proliferation-promoting effects during the diabetic wound healing
process.
Aside from that, tissue samples on day 19 were stained for NLRP3 and
Phospho-NF-κB p65. The AG-treated group revealed dramatically lower
levels of NLRP3 (p < 0.05) and Phospho-NF-κB p65 (p < 0.001) in
contrast to the control group ([144]Figures 6A–C), which accords with
the prior study findings summarized in Western blot analysis. This
confirms that AG can lower NF-κB p65 phosphorylation, thereby
decreasing NLRP3 inflammasome activation and promoting diabetic wound
healing.
FIGURE 6.
[145]FIGURE 6
[146]Open in a new tab
Immunofluorescence staining of skin tissues post diabetic wound
healing. (A) Representative images of NLRP3 and Phospho-NF-κB p65
staining on day 19 post-wounding; (B) Quantification of NLRP3 staining
on day 19 post-wounding; (C) Quantification of Phospho-NF-κB p65
staining on day 19 post-wounding.
4 Discussion
Nowadays, there is a deficiency of effective and safe treatment methods
for diabetic chronic wounds, which may bring about amputations and
severely affect the quality of life of patients ([147]McDermott et al.,
2023; [148]Bus et al., 2024). As a result, there is an urgent need for
a novel, effective, and safe therapeutic strategy for treating diabetic
chronic wounds. This study probed deep into the potential of AG as a
therapeutic agent for diabetic chronic wounds through a combination of
network pharmacology analysis, molecular docking, and experimental
validation both in vitro and in vivo.
AG is a naturally occurring complex polysaccharide. Studies on diabetic
rats have shown that AG exhibits potent therapeutic effects on diabetes
([149]Ibrahim et al., 2023; [150]Keykhaee et al., 2023). In addition to
its role in diabetic recovery, AG has been extensively studied in the
context of chronic inflammation. Research indicates that AG effectively
regulates inflammatory and oxidative biomarkers, contributing to its
therapeutic potential ([151]Nemmar et al., 2019; [152]Ali et al., 2020;
[153]Gouda and Babiker, 2022). Specifically, AG exhibits significant
antioxidant and anti-inflammatory effects, making it a promising agent
for cardiovascular protection ([154]Barkeer et al., 2024). In
experimental models of ischemia/reperfusion (I/R) injury, AG treatment
has been shown to improve cardiac hemodynamics, reduce infarct size,
and decrease levels of cardiac enzymes ([155]Gouda and Babiker, 2022).
Moreover, AG administration resulted in a marked reduction of
pro-inflammatory cytokines, while boosting antioxidant enzyme levels
such as superoxide dismutase (SOD) ([156]Gouda and Babiker, 2022).
In our network pharmacology analysis suggested that AG promote diabetic
wound healing by regulating AGEs-RAGE signaling pathway, which plays a
crucial role in diabetic complications in diabetic complications.
Further analysis indicated that the active ingredients include
D-galactose, L-arabinose, L-rhamnose, D-glucuronic acid, and
4-O-methyl-glucuronic acid. Additionally, potential target proteins
such as HSP90AA1, STAT3, and PRKCB were highlighted as important links
in this pathway. HSP90AA1, STAT3, and PRKCB are potential target links
([157]Figure 1). Based on these evidences, the present study focused on
the bioactive components of AG to explore their effects on diabetic
chronic wound healing and to elucidate the underlying mechanisms that
promote wound healing.
In the tissues of diabetic patients, there is a high accumulation of
AGEs that can bind to RAGE and activate multiple signaling pathways,
such as NF-κB, MAPK, and PI3K-AKT-mTOR ([158]Chen et al., 2016; [159]Li
et al., 2025). This activation leads to inflammatory responses,
oxidative stress, endothelial dysfunction, and cell apoptosis
([160]Jere et al., 2019; [161]Jin et al., 2024). These events
collectively contribute to the pathophysiology of diabetes-related
wounds by impairing cellular migration and causing vascular damage,
both of which are key factors in the delayed wound healing process.
([162]Morton and Phillips, 2016; [163]Patel et al., 2019). As clearly
demonstrated by our findings, AGEs remarkably inhibited the migratory
ability of HSFs and the tube-forming capacity of HUVECs in comparison
with the control group. Nonetheless, co-treatment with AG reversed
these effects and even strengthened them ([164]Figures 2C–G). As these
results suggest, AG may offer potential advantages in promoting healing
in AGEs-related diabetic wounds.
The NLRP3 inflammasome, which is renowned as a sensor for metabolic and
inflammatory signals that induces IL-1β maturation, has captured
remarkable academic intention ([165]Kim et al., 2017; [166]Chen et al.,
2023). The classical activation of the NLRP3 inflammasome requires an
initial signal regulated by NF-κB ([167]Lee et al., 2020; [168]Li W. et
al., 2022; [169]Teh et al., 2023). As suggested by our research
findings, AG conducts a crucial role in inhibiting the NF-κB pathway by
decreasing the phosphorylation of the NF-κB p65 subunit, as
demonstrated in our Western blot analyses ([170]Figures 3F, G). This
inhibition illustrates that AG may hold back the priming phase
essential for the activation of the NLRP3 inflammasome. Considering
that the NLRP3 inflammasome functions downstream of NF-κB, we hold the
opinion that AG’s influence on NF-κB signaling gives rise to diminished
levels of NLRP3 components and pro-inflammatory cytokines.
To further validate its feasibility and underlying mechanisms, a
full-thickness wound model on the dorsal area of diabetic rats was
employed in this study. we validated how AG conspicuously affects the
promotion of wound healing ([171]Figure 4B). The reinforced collagen
deposition and elevated expression of angiogenic markers like CD31 and
proliferation markers like Ki-67 in AG-treated wounds underscore its
anti-inflammatory, antioxidant, pro-angiogenic, and cell-proliferative
properties in tissue regeneration ([172]Figures 4D, [173]5C). Apart
from that, our in vivo results further substantiate this mechanism,
where treatment with AG led to lower concentrations of NLRP3 and IL-1β
in wound tissues ([174]Figures 5B, [175]F), aligning with our in vitro
findings ([176]Figures 3, [177]6).
As these findings evidently suggest, AG could reduce chronic
inflammation and oxidative stress by disrupting the AGEs-NF-κB-NLRP3
pathway ([178]Figure 7). By intervening in this inflammatory cascade,
AG may facilitate a more conducive environment for wound healing under
diabetic conditions. It’s pivotal to note that AG’s capability to
influence this signaling pathway addresses a paramount component of
diabetic wound pathology, which is an ongoing inflammatory condition
that obstructs the typical healing process.
FIGURE 7.
[179]FIGURE 7
[180]Open in a new tab
Arabic Gum’s role in promoting diabetic wound healing by modulating the
AGEs-NF-κB-NLRP3 axis.
While these promising findings are indeed noteworthy, it is crucial to
acknowledge several limitations in our research. Above all, the
long-term effects and possible side effects of AG treatment were not
evaluated in this study. Despite the fact that the FDA generally
considers AG safe and it has been utilized as a dietary fiber, its
therapeutic application at elevated doses or for extended durations
might bring about unexpected negative outcomes. As a consequence, it is
essential for future research to dig into the chronic toxicity,
immunogenicity, and overall safety of AG concerning diabetic wound
healing. Apart from that, this study only examined the dosing from the
standpoint of cytotoxicity, and further research is still needed on
dose optimization and administration methods. For example,
individualized dosage studies could be conducted based on factors such
as age, weight, liver function, and kidney function. And research on
drug release rates could be explored using hydrogels or microneedle
dressings. These aspects will be addressed in future studies by our
research team. On top of that, the specific bioactive constituents of
AG that induce the observed effects have yet to be fully clarified. For
this reason, gaining insight into the distinct roles of individual
components could facilitate the creation of more targeted therapies
with reinforced efficacy and safety profiles.
5 Conclusion
This research findings demonstrate that AG holds potential as a
therapeutic agent for improving diabetic wound healing by modulating
the AGEs-NF-κB-NLRP3 signaling axis. Nevertheless, addressing the
limitations mentioned above is essential for pushing ahead this
research. For future endeavors, it’s more preferable to include more
extensive experimental validation, exploration of the specific active
components of AG, and investigations into the long-term effects and
mechanisms in more complex models. Hopefully, such efforts will
reinforce our understanding of AG’s role in diabetic wound healing and
may drive the development of new therapeutic strategies for this
challenging condition.
Funding Statement
The author(s) declare that financial support was received for the
research, authorship, and/or publication of this article. Support for
this research was provided by the Hubei Provincial Natural Science
Foundation (Grants No. 2023AFB678). Zhongnan Hospital Fund for
Translational Medicine and Interdisciplinary Research (No. ZNJC202328).
Science Foundation of Zhongnan Hospital, Wuhan University (No.
CXPY2020039).
Data availability statement
The original contributions presented in the study are included in the
article/[181]Supplementary Material, further inquiries can be directed
to the corresponding authors.
Ethics statement
Ethical approval was not required for the studies on humans in
accordance with the local legislation and institutional requirements
because only commercially available established cell lines were used.
The animal study was approved by the Institutional Animal Care and Use
Committee at the Hubei Provincial Center. The study was conducted in
accordance with the local legislation and institutional requirements.
Author contributions
LC: Conceptualization, Data curation, Investigation, Methodology,
Writing–original draft. DC: Conceptualization, Data curation,
Investigation, Methodology, Writing–review and editing. LY: Data
curation, Investigation, Methodology, Writing–review and editing. PP:
Data curation, Investigation, Writing–review and editing. HW:
Conceptualization, Methodology, Writing–review and editing. NA:
Investigation, Writing–review and editing. NA-K: Investigation,
Writing–review and editing. JG: Investigation, Methodology, Software,
Writing–review and editing. QL: Conceptualization, Project
administration, Writing–review and editing. LG: Funding acquisition,
Project administration, Resources, Supervision, Writing–review and
editing.
Conflict of interest
The authors declare that the research was conducted in the absence of
any commercial or financial relationships that could be construed as a
potential conflict of interest.
Generative AI statement
The author(s) declare that no Generative AI was used in the creation of
this manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or claim
that may be made by its manufacturer, is not guaranteed or endorsed by
the publisher.
Supplementary material
The Supplementary Material for this article can be found online at:
[182]https://www.frontiersin.org/articles/10.3389/fphar.2025.1528880/fu
ll#supplementary-material
[183]DataSheet1.docx^ (1.3MB, docx)
Abbreviations
AG, Arabic Gum; AGEs, advanced glycation end products; CRF, chronic
renal failure; FBS, fetal bovine serum; FDA, Food and Drug
Administration; HSFs, human skin fibroblasts; HUVECs, human umbilical
vein endothelial cells; PDB, Protein Data Bank; LRR, leucine-rich
repeat; NBD, nucleotide-binding domain; PYD, pyrin domain; ROS,
reactive oxygen species.
References