Network Pharmacology and Zebrafish Model Elucidate the Hypoglycemic Mechanism of Major Compounds in Cyclocarya paliurus

TL;DR

This study identifies key compounds in Cyclocarya paliurus leaves and uses network pharmacology and zebrafish experiments to explain their blood sugar-lowering effects.

Contribution

The study combines network pharmacology and zebrafish models to reveal hypoglycemic mechanisms of Cyclocarya paliurus compounds.

Findings

Seven compounds in Cyclocarya paliurus leaves were identified, including Chlorogenic Acid and Quercetin derivatives.

Network pharmacology and zebrafish experiments showed AKT1, TNF, and IL1B are key targets for hypoglycemic activity.

The compounds regulate blood glucose by upregulating AKT1 and downregulating TNF and IL1B.

Abstract

Diabetes Mellitus is a complex metabolic disorder, primarily characterized by persistent high blood sugar levels, and it is becoming increasingly prevalent with numerous associated complications. The leaves of Cyclocarya paliurus (Batal.) Iljinskja, traditionally prepared as a tea beverage in China, is frequently used in folk medicine for managing metabolic syndromes, particularly diabetes and hyperlipidemia. However, the main active components responsible for its hypoglycemic effect and their underlying mechanisms remain unclear. The current study aimed to clarify the main chemical components of the aqueous extract of C. paliurus leaves and to explore their mechanisms of action. The primary constituents from the aqueous extract of C. paliurus leaves were isolated and identified using macroporous adsorption resin, preparative liquid chromatography, and nuclear magnetic resonance technology. The contents of these identified compounds in the leaves were quantified using HPLC. An integrated approach combining network pharmacology and molecular docking was initially used to predict the potential molecular targets and associated signaling pathways responsible for the hypoglycemic activity of the compounds, with subsequent experimental validation performed in a hyperglycemic zebrafish model. From the aqueous extract, a total of seven compounds were obtained and subsequently identified as Chlorogenic Acid (CA), Quercetin-3-O-β-D-glucuronide (Q3GA), Astragalin, 3,4-Dicaffeoylquinic Acid (3,4-DCA), Afzelin, Quercetin, and Kaempferol. Their contents in C. paliurus leaves, as determined by HPLC, were 24.88 mg/g, 30.87 mg/g, 1.21 mg/g, 1.19 mg/g, 5.24 mg/g, 2.43 mg/g, and 1.34 mg/g, respectively. Network pharmacology analysis identified AKT1, TNF, and IL1B as key targets for the hypoglycemic effects of both the aqueous extract and the seven individual compounds. These findings were further supported by RT-PCR experiments in a zebrafish model, which showed that blood glucose regulation occurs through the downregulation of TNF and IL1B and the upregulation of AKT1 protein. The aqueous extract is rich in Chlorogenic Acid, Quercetin, and their derivatives, all of which display significant hypoglycemic activity.

Figures

Full text

1. Introduction

Diabetes Mellitus (DM) is a systemic metabolic disorder resulting from multiple causes, characterized by persistent high blood sugar levels. Its pathogenesis is complex, often involving defects in insulin secretion or impaired insulin action, which can lead to severe complications affecting multiple organs, including the cardiovascular, renal, nervous, and ocular systems [1]. It has become a major global public health challenge that seriously threatens human health [2]. According to the International Diabetes Federation (IDF), there were approximately 537 million adults living with diabetes globally in 2021 [3]. The latest figures show that this number has risen to an estimated 589 million by 2024, indicating a continuous and severe growth trend [4]. Currently, the primary clinical drugs for treating diabetes include α-glucosidase inhibitors, biguanides, and sulfonylureas [5]. Although these synthetic drugs have achieved significant efficacy in glycemic control, their prolonged administration is associated with a range of adverse effects, such as gastrointestinal discomfort, risk of hypoglycemia, weight gain, and even hepato-renal impairment [6,7], thereby limiting their application in long-term management and early intervention. Consequently, the search for and development of safe, effective, natural hypoglycemic active ingredients with minimal side effects from traditional medicinal plants has become a crucial direction and research hotspot in the field of novel drug discovery and functional food development.

Cyclocarya paliurus (Batal.) Iljinskja (C. paliurus), a species in the monospecific genus Cyclocarya of the Juglandaceae family, has historically been used as a folk remedy in southern China. Its tender leaves are typically processed into herbal tea to help regulate blood glucose and lipids [8]. In 2013, the leaves of C. paliurus were approved as a novel food ingredient by the National Health and Family Planning Commission of China [9]. Modern phytochemical screening has demonstrated that C. paliurus leaves are a rich source of numerous bioactive compounds, including polysaccharides, triterpenes, flavonoids, phenolic acids, saponins, amino acids, and a range of trace elements [10,11]. By inhibiting the enzymatic activity of α-glucosidase, C. paliurus polysaccharides (CPPs), especially CPP-1 and CPP-6, effectively reduce diet-induced hyperglycemia by slowing the digestive breakdown and subsequent absorption of carbohydrates [12]. The flavonoid compounds of C. paliurus are also considered one of the core groups of active constituents responsible for its hypoglycemic effects [13]. However, the majority of previous scholarly research has focused on the overall pharmacological activity of crude extracts (e.g., ethanol extract) [14] or a specific class of components (e.g., total polysaccharides, total triterpenes) [15,16]. A systematic and in-depth analysis of its traditional form of administration—the aqueous extract (i.e., C. paliurus tea)—is still lacking regarding its specific chemical profile, the precise content of major compounds, and the independent contributions and potential synergistic relationships of these compounds in exerting the hypoglycemic effect. Therefore, the definitive material basis and molecular mechanisms underlying its hypoglycemic action remain to be fully elucidated. The convergence of rapidly advancing systems biology and bioinformatics has given rise to network pharmacology, a pivotal scientific framework for investigating the ‘multi-component, multi-target, multi-pathway’ nature of therapeutic actions in traditional herbal medicines [17]. This approach integrates knowledge from multiple disciplines, including medicinal chemistry, genomics, proteomics, and computational biology, to predict the potential targets of active ingredients from a holistic and systematic perspective, construct “compound-target-disease” interaction networks, and reveal the core biological processes and signaling pathways of drug intervention through Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis [18]. For example, Zixin Lin et al. used this approach to predict the hypoglycemic activity of 39 triterpenoids identified in C. paliurus leaves through HPLC-MS/MS, preliminarily screening seven key compounds; however, their conclusions remain at the theoretical prediction stage and lack experimental validation [16]. Moreover, the mechanism by which C. paliurus leaves extract ameliorates diabetic fatty liver disease was investigated using an integrated approach of network pharmacology and experimental validation. This revealed that its therapeutic potential could be attributed to the modulation of specific signaling cascades, including the miR-199a-5p/miR-31a-5p/Jun pathway. This finding offers significant insights for future mechanistic studies concerning diabetes and its associated complications [19]. These studies show that network pharmacology is an effective approach for clarifying the complex pharmacological effects of C. paliurus; however, any in silico predictions must ultimately be validated through in vivo experiments to produce reliable scientific conclusions.

The zebrafish (Danio rerio), one of the primary model organisms following rats and mice, is extensively used in antihyperglycemic research due to its high similarity to humans in insulin regulation and glucose metabolism [20]. Hyperglycemic models in zebrafish can be easily and quickly established through high-glucose induction or chemical administration. This not only facilitates the rapid and efficient validation of network pharmacology predictions but also allows for direct in vivo assessment of the glucose-lowering efficacy of compounds. As a result, this model has been widely and successfully applied to evaluate the antidiabetic potential of various extracts from medicinal plants [21].

This study employs an integrated approach that combines phytochemical separation and identification, network pharmacology, and animal model validation. First, the main components are isolated and characterized from the aqueous extract. Subsequently, the hypoglycemic properties and underlying molecular mechanisms of these compounds are investigated using network pharmacology in conjunction with a zebrafish biological model. The findings aim to further clarify the antidiabetic function and bioactive principles of this plant when used as a traditional tea beverage, providing a novel scientific basis for its development into a natural therapeutic agent or functional food for glycemic control.

2. Materials and Methods

2.1. Materials

The leaves of cultivated Cyclocarya paliurus (Batalin) Iljinskaja were picked in early May 2023 from the production base of Guyanghe Tea Co., Ltd., located in Guzhang, China. The botanical identity was verified by Professor Qi Tang from the Department of Chinese Materia Medica Resources and Development at Hunan Agricultural University. After collection, the tender leaves were removed from the branches, dried in an oven at 60 °C, and then ground into a fine powder.

Zebrafish (Danio rerio) were obtained from Wuhan Wanwuyuan Experimental Equipment Co., Ltd. (Wuhan, China). The study was approved by the Ethics Committee of Hunan Agricultural University under number 2026 (13). The fish were housed and maintained in a dedicated zebrafish aquaculture system within the laboratory of the College of Fisheries at Hunan Agricultural University. Husbandry conditions included a constant temperature of 28.5 °C and a defined photoperiod of 10 h of darkness and 14 h of light. For breeding, male and female fish were placed in spawning boxes at a 1:1 ratio to facilitate natural spawning. The animal study protocol was also approved by the Biomedical Research Ethics Committee of Hunan Agricultural University (protocol code 202613; date of approval: 20 April 2024).

2.2. Instruments and Reagents

The main instruments and equipment used in this study were as follows: an LC-20AT liquid chromatograph (Shimadzu Corporation, Kyoto, Japan); an Acclaim™ 120 C_18_ column (4.6 × 250 mm, 5 µm; Thermo Fisher Scientific, Waltham, MA, USA) for HPLC Analysis, and a Hedera ODS-2 column (10 mm × 250 mm, 5 µm particle size) for Preparative HPLC; an Accu-Chek blood glucose meter (Roche Diagnostics, Mannheim, Germany); a GeneAmp^®^ 9700 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA); a Model 5430 R refrigerated high-speed centrifuge (Eppendorf, Hamburg, Germany); and a JXFSTPRP-48 tissue grinder (Shanghai Jingxin Industrial Development Co., Ltd., Shanghai, China).

Methanol (HPLC grade) and phosphoric acid (analytical grade) were purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). Dimethyl sulfoxide (DMSO) was obtained from Coolaber Science & Technology Co., Ltd. (Beijing, China). Alloxan (ALX, purity ≥ 98%) and Acarbose (ACA, purity ≥ 98%) were purchased from Aladdin Biochemical Technology Co., Ltd. (Shanghai, China). All primers were designed and synthesized by Tsingke Biotechnology Co., Ltd. (Beijing, China). The RT-PCR kit was supplied by Vazyme Biotech Co., Ltd. (Nanjing, China). The FastKing gDNA Dispelling RT SuperMix and the RNA Easy Fast Animal Tissue Total RNA Extraction Kit were purchased from Tiangen Biotech (Beijing) Co., Ltd. (Beijing, China).

2.3. Methods

2.3.1. Isolation and Identification of Major Compounds from the Leaves of C. paliurus

Preparation of the Crude Extract

A sample of powdered C. paliurus leaves (1.0 kg) was extracted three times with distilled water using ultrasonic assistance. The solvent-to-material ratios were 13:1 (v/w), 8:1 (v/w), and 8:1 (v/w), with extraction times of 45 min, 30 min, and 30 min, respectively. The filtrates from all three extraction stages were combined and then concentrated to a final volume of 750 mL, and the pH was adjusted to 3.0 with HCl.

HPLC Analysis of the C. paliurus Leaf Extract

HPLC analysis was performed using a mobile phase consisting of acetonitrile (solvent B) and 0.1% (v/v) aqueous phosphoric acid (solvent A). 0–35 min, solvent B gradient increasing from 5% to 52%. The column temperature was 30 °C, and the steady flow rate was 1.0 mL/min. Absorbance was 350 nm.

Preliminary Purification by Macroporous Adsorption Resin

A total of 800 mL of AB-8 macroporous adsorption resin was used to pack a glass column. The crude extract was loaded into the column at a flow rate of 2 bed volumes per hour (2 BV/h). After that, standing for 30 min, the column was washed with distilled water at a flow rate of 6 BV/h until the eluate was colorless. Subsequently, the column was sequentially eluted with 6 BV each of 20%, 70%, and 80% (v/v) aqueous ethanol solutions at a flow rate of 2–3 BV/h. High-performance liquid chromatography (HPLC) analysis was performed to determine the chemical profiles of the eluted fractions. The fractions eluted with 70% and 80% ethanol were collected and concentrated to dryness. The resulting residues were then redissolved in 10 mL of methanol for preparative HPLC separation.

Isolation of Compounds by Preparative HPLC

The mobile phase consisted of acetonitrile (solvent B) and 0.5% (v/v) aqueous glacial acetic acid (solvent A). Detection was performed at 254 nm, with an injection volume of 1 mL and a flow rate of 5 mL/min. Collection of the eluates was guided by the chromatographic peaks, followed by purity verification using HPLC.

For the 70% ethanol eluate, the compound separation gradient was: 0–25 min, 20–55% B. For the 80% ethanol eluate, the gradient was: 0–20 min, 38–58% B. After collecting the fractions corresponding to each peak, identical fractions were combined, concentrated, and lyophilized to obtain the dry compound powder.

Structural Elucidation of Compounds

The ^1^H and ^13^C Nuclear Magnetic Resonance (NMR) spectra of the isolated compounds were recorded at Hunan Normal University. By interpreting their corresponding NMR spectra, the chemical structures of the compounds were determined.

2.3.2. Quantification of Compounds Isolated from C. paliurus

The quantification of the isolated compounds was carried out using an extraction process that mimics traditional tea preparation. Specifically, 3.0 g C. paliurus leaves was accurately weighed and placed into a 500 mL conical flask, which was then infused with 450 mL of boiling distilled water. The mixture was subsequently leached by infusion for 45 min using boiling water. After extraction, the hot solution was filtered. The filtered liquid was diluted to a total volume of 500 mL with distilled water to serve as the test solution. For the quantification of each component, HPLC analysis was performed in Section HPLC Analysis of the C. paliurus Leaf Extract. The previously isolated compounds were used as reference standards to construct calibration curves. The amount of each analyte in the C. paliurus leaves material was then determined by referring to its respective calibration curve.

2.3.3. Network Pharmacology-Based Investigation of the Hypoglycemic Effects of Major Compounds from C. paliurus Leaves

Analysis of Potential Target Proteins of the Compounds

The seven compounds isolated and identified as described above were searched in the PubChem (https://pubchem.ncbi.nlm.nih.gov) database to obtain their SMILES strings, InChI keys, and PubChem CIDs. Subsequently, the SMILES strings were submitted to the Swiss TargetPrediction (http://swisstargetprediction.ch) server, while the InChI keys and PubChem CIDs were input into the BATMAN-TCM (http://bionet.ncpsb.org.cn) platform to predict their potential targets, with the species set to Homo sapiens. Concurrently, the GeneCards (https://www.genecards.org) database was queried using “Diabetes Mellitus” (DM) to screen for disease-related targets, and the median method was applied to retain a final set of 1000–1500 targets. The intersection of the active compounds’ targets and the disease-associated targets was visualized using a Venn diagram generated by Venny 2.1.0. These targets were then submitted to the STRING (https://cn.string-db.org) database (species: Homo sapiens) to construct a protein–protein interaction (PPI) network. The results were saved in TSV format and subsequently loaded into Cytoscape software (Version 3.7.1) for network visualization and further analysis. After performing network analysis using Network Analyzer, a native tool in Cytoscape (Version 3.7.1), the core targets were identified as the ten nodes with the highest degree centrality. Finally, the intersection targets of the active compounds and their associated disease-related target information were imported into Cytoscape (Version 3.7.1) to construct and visualize the “compound-target” network.

Functional Pathway Analysis of Potential Target Proteins

GO and KEGG pathway enrichment analyses were conducted using the DAVID database (https://davidbioinformatics.nih.gov/). The targets of seven compounds from C. paliurus associated with blood glucose regulation were imported for this purpose. The analysis was performed across three aspects of gene function: Cellular Component (CC), Biological Process (BP), and Molecular Function (MF). For the GO functional analysis, the top 10 significantly enriched terms, ranked in ascending order of their p-values, were selected. For the KEGG pathway enrichment analysis, the top 20 significant pathways, also ranked by ascending p-value, were extracted. The results were then imported into an online bioinformatics analysis platform (https://www.bioinformatics.com.cn/) for visualization, generating a composite bar chart for BP, CC, and MF, as well as a KEGG enrichment bubble plot.

Molecular Docking Analysis

The 3D structures of the bioactive constituents were obtained in sdf format from PubChem, while the crystal structures of the four main core target proteins were retrieved as sdf files from the RCSB Protein Data Bank (https://www.rcsb.org). Protein crystals were selected based on criteria including Homo sapiens origin, low resolution, X-ray diffraction method, and presence of a co-crystallized ligand. Pymol software(version 2.2.0) was used to add hydrogen atoms to the ligands; for the target proteins, water molecules and original ligands were removed, and hydrogen atoms were added. Subsequently, OpenBabel (version 2.4.1) was employed to convert all processed files into the PDBQT format. The generated structure files were then processed using AutoDockTools (version 1.5.7) to perform docking studies between the bioactive molecules and target receptors.

2.3.4. Investigation of the Hypoglycemic Effects of C. paliurus Leaf Extract and Its Major Compounds in a Zebrafish Model

Determination of the Maximum Tolerated Concentration (MTC) of Different Samples

In accordance with Section 2.3.2, the C. paliurus aqueous extract was serially diluted with distilled water to produce graded concentrations ranging from 100 to 800 µg/mL before experimentation. Stock solutions of individual compounds were prepared at 1.0 mg/mL by dissolving them in 0.5% DMSO. After sonication, these solutions were serially diluted with distilled water to generate a concentration gradient spanning 6.25 to 400 µg/mL. Zebrafish were cultured in these respective solutions for 48 h. A concentration-mortality curve was plotted to determine the MTC for the aqueous extract and each compound, which were then used in subsequent experiments.

Assessing the Hypoglycemic Activity of the Extract and Its Constituent Compounds

The experiment was divided into a control group (CK), a model group (MOD), sample groups (including the C. paliurus aqueous extract group and seven compound groups), and a positive control group, with three replicates per group. The fish in each group were cultured in the following solutions, respectively: CK was maintained in distilled water; MOD in an alloxan aqueous solution; the sample groups in a solution of alloxan + sample; and the positive control group in a solution of alloxan + positive control drug (ACA). The final concentration of alloxan in the model, sample, and positive control groups was 0.20 mmol/L. The final concentration of ACA was 100 µg/mL, and the final concentrations for the sample groups were the respective MTCs of each sample. The specific procedure was as follows: 5 dpf wild-type zebrafish larvae were placed into 6-well plates, with 30 larvae per well, and 6.0 mL of the aforementioned rearing water was added. After 24 h, half of the rearing water was replaced. After 48 h, the larvae were collected with a sieve, washed twice with distilled water, and dried with filter paper. The larvae were then transferred into 1.5 mL centrifuge tubes and homogenized using a grinder. The homogenates were centrifuged at 12,000 r/min for 10 min under low-temperature conditions. The supernatant was collected with a pipette, and its blood glucose level was measured using a Roche Accu-Chek glucometer. The results were compared with the model group to determine statistical significance, and the hypoglycemic rate was calculated.

Determination of Related Gene Expression in Zebrafish by RT-PCR

Zebrafish from different groups were homogenized and kept on ice. Total RNA from zebrafish was isolated using the RNA Easy Fast kit, followed by complementary DNA (cDNA) synthesis via reverse transcription with the FastKing gDNA and RT SuperMix. Primer details are provided in Table 1. Using β-actin as the internal reference gene, the expression levels of three genes (AKT1, TNF, and IL1B) in zebrafish from different experimental groups were quantitatively analyzed using ChamQ Universal SYBR qPCR Master Mix. The specific procedure was as follows: a reaction mixture was prepared on ice according to the specified proportions (5.0 µL of 2 × ChamQ Universal SYBR qPCR Master Mix, 0.2 µL of Primer 1, 0.2 µL of Primer 2, and 2.6 µL of ddH_2_O). Then, 8 µL of this mixture was combined with 2 µL of cDNA, mixed, centrifuged, and subjected to amplification. The reaction conditions were: 95 °C for 30 s, followed by 40 cycles of 95 °C for 10 s and 60 °C for 30 s. Melting curve analysis was performed from 60 °C to 95 °C. Relative expression levels of the target genes were calculated using the 2^−ΔΔCt^ method.

2.3.5. Data Processing and Analysis

Following initial processing in Microsoft Excel 2016, the experimental data were visualized as plots using GraphPad Prism 8.0. One-way ANOVA was performed with IBM SPSS 27.0. The t-test was utilized for assessing differences between two groups, whereas Tukey’s HSD test was applied for comparisons involving multiple groups. The data were presented as the mean ± standard deviation ( $[eqn]$ ± SD), and a p-value of <0.05 was considered statistically significant.

3. Results

3.1. Isolation and Identification of Major Chemical Constituents from the Leaves of C. paliurus

3.1.1. HPLC Analysis of the Aqueous Extract

The HPLC chromatogram of the aqueous extract was shown in Figure 1. The chromatogram indicated that the extract had a complex composition, containing multiple compounds. Several chromatographic peaks with retention times before 35 min showed strong absorption at 350 nm and 328 nm and were therefore tentatively identified as flavonoids and phenolic acids.

3.1.2. Purity Determination and Structural Elucidation of Compounds

The major compounds from the 70% and 80% ethanol elution fractions were isolated by Preparative HPLC, yielding seven compounds. Their purities were determined by the area normalization method to be 95%, 96%, 95%, 91%, 92%, 94%, and 97%, respectively.

The structures of the compounds were elucidated by NMR spectroscopy: Compound 1 was chlorogenic acid according to the literature [22]. Compound 2 was Quercetin-3-O-β-D-glucuronide according to the literature [23]. Compound 3 was astragalin according to the literature [24]. Compound 4 was 3,4-di-O-Caffeoylquinic Acid according to the literature [25]. Compound 5 was afzelin according to the literature [26]. Compound 6 was Quercetin according to the literature [27]. Compound 7 was kaempferol according to the literature [28]. ^1^H and ^13^C NMR spectroscopic data in Table 2 and Table 3. The structures of the compounds are shown in Figure 2.

3.1.3. Quantitative Analysis of Major Chemical Constituents in C. paliurus Leaves

The quantitative results for the targeted chemical constituents are presented in Table 4. As presented in the table, among the compounds quantified in the aqueous extract, Q3GA was the most abundant, with a content of (30.87 ± 0.07) mg/g, followed by CA at (24.88 ± 0.03) mg/g. The contents of the other five compounds ranged from (1.19 ± 0.02) mg/g to (5.24 ± 0.5) mg/g, which were considerably lower than those of Q3GA and CA. The total content of these seven quantified compounds was 67.16 mg/g.

3.2. Network Pharmacology-Based Investigation of the Hypoglycemic Effect of C. paliurus Leaves

3.2.1. Analysis of Potential Target Proteins of the Active Compounds

The potential targets for the seven active compounds were predicted using the Swiss Target Prediction and BATMAN-TCM platforms, respectively. After merging the results and removing duplicates, a total of 355 compound-related targets were obtained. Concurrently, 16,800 diabetes-related targets were sourced from the Gene Cards database, from which 1051 key disease targets were subsequently selected via a median-based method. To identify the intersection between the two target sets, the 355 compound targets and the 1051 disease targets were subjected to a comparative analysis using Venny 2.1.0. This procedure yielded 153 common targets, which are visually represented in the Venn diagram (Figure 3A). In the subsequent step, the STRING database was employed to build a PPI network based on these common targets, allowing for an exploration of their potential therapeutic mechanisms. The network consisted of 153 nodes and 4136 edges, where the importance of a node is indicated by a deeper color and a larger diameter. The top 10 core targets were identified as AKT1, IL6, TNF, IL1B, PPARG, TP53, CASP3, STAT3, HIF1A, and NFKB1 (Figure 3B).

Seven compounds and their corresponding disease-associated targets were imported into Cytoscape 3.7.1 to construct a network. The resulting “compound-target” network is shown in Figure 4. The network reveals that various compounds are associated with multiple diabetes-related targets, with Quercetin linked to the highest number of targets and Q3GA associated with the fewest.

3.2.2. Analysis of Action Pathways of Potential Target Proteins

GO enrichment analysis was conducted on the 153 intersection targets, with the top 10 terms for Biological Process (BP), Cellular Component (CC), and Molecular Function (MF), ranked in ascending order by their p-values, shown in Figure 5. Analysis of the BP category indicated that the target proteins were primarily involved in several key pathways, including positive regulation of gene expression, inhibition of the apoptotic process, activation of phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) signal transduction, cellular response to lipopolysaccharide, inflammatory response, and enhancement of transcription by RNA polymerase II. For the CC category, the target proteins were mainly localized in the extracellular space, cytosol, extracellular region, and receptor complex. The primary molecular functions associated with the target proteins included enzyme binding, identical protein binding, and nuclear receptor activity.

The KEGG pathway enrichment analysis results were sorted in ascending order based on their p-values, with the top 20 pathways displayed in Figure 6. In this figure, the dot color indicates the level of statistical significance of the enrichment, with a gradient shifting toward red representing a smaller p-value and thus greater credibility. In this pathway analysis, the dot size is directly proportional to the number of enriched target genes, with a larger diameter signifying higher pathway significance. As shown, the top five signaling pathways included the AGE-RAGE signaling pathway in diabetic complications, Fluid shear stress and atherosclerosis, Lipid and atherosclerosis, Pathways in cancer, and Insulin resistance. Our findings suggest that the anti-diabetic activity of the compounds is mediated through the modulation of core targets within these key pathways.

3.2.3. Molecular Docking Analysis

The selected compounds were used as ligands, and the top four core targets identified from the PPI network (AKT1, IL6, TNF, and IL1B) served as receptors for molecular docking. Table 5 summarizes the computational docking results. It revealed that most compounds had lower binding energies with AKT1, TNF, and IL1B, and a relatively high binding energy with IL6, suggesting that their principal pharmacological activities may be mediated via the AKT1, TNF, and IL1B pathways.

3.3. Hypoglycemic Effect of the Aqueous Extract and Its Major Compounds in the Zebrafish Model

3.3.1. Determination of MTC of the Test Samples

Figure 7 illustrates the effects of the aqueous extract and isolated major compounds on the survival rate of zebrafish. The LC_0_ of the aqueous leaf extract was determined to be 200 µg/mL. The LC_0_ values for the individual compounds varied significantly: 12.5 µg/mL for CA, 25.0 µg/mL for Astragalin, Quercetin, and Q3GA, and 100.0 µg/mL for Afzelin, Kaempferol, and 3,4-DCA.

3.3.2. Hypoglycemic Effects of the Aqueous Extract and Isolated Compounds

Figure 8 presents the effects of the aqueous extract and seven isolated compounds at their respective LC_0_ concentrations on hyperglycemic zebrafish. Compared to the control (CK), blood glucose concentration in the model (MOD) group was significantly elevated by 49.6%, increasing from 4.2 to 6.3 (p < 0.05), confirming the successful establishment of the hyperglycemic model. In comparison to MOD, the blood glucose level in the ACA group was 3.3, representing a 47.9% reduction. The blood glucose levels in groups treated with C. paliurus leaf extract, CA, Astragalin, Quercetin, Q3GA, Afzelin, Kaempferol, and 3,4-DCA were 4.2, 3.3, 5.3, 3.1, 3.8, 5.5, 3.0, and 4.2, respectively. These values corresponded to significant reductions of 33.7%, 47.4%, 16.3%, 51.6%, 40.5%, 13.2%, 53.2%, and 34.2%, respectively (all p < 0.05). These results demonstrate that both the aqueous extract and the seven tested compounds exhibit significant hypoglycemic activity. Among the tested substances, Kaempferol and Quercetin showed the highest rates of glucose reduction at their MTC, with effects comparable to the positive control drug ACA. Additionally, CA also displayed notable hypoglycemic activity at a low concentration.

3.3.3. Effect of the Compounds on the mRNA Expression of Core Target Genes in Zebrafish

Molecular docking results revealed that several compounds exhibited low binding energies with the target proteins AKT1, TNF, and IL1B. Consequently, RT-PCR was performed to confirm the regulatory impact of these compounds on the transcription of AKT1, TNF, and IL1B (Figure 9). The data presented in the figure reveals that MOD exhibited a significant downregulation in the mRNA transcript level of AKT1 (p < 0.05) relative to CK. Conversely, the transcription of TNF and IL1B was markedly upregulated. Treatment with the seven compounds markedly elevated the mRNA expression of AKT1 (p < 0.05) while concurrently diminishing the mRNA levels of TNF and IL1B (p < 0.05), when compared with the MOD group. This trend was consistent with that observed in ACA. This study reveals that the monomeric compounds from C. paliurus exert their hypoglycemic effects primarily by modulating these three targets, namely AKT1, TNF, and IL1B.

4. Discussion

The results of compound separation and identification indicated that the aqueous extract of C. paliurus leaves mainly contains chlorogenic acid and its derivatives, flavonoids, and flavonoid glycosides. Several of these compounds have been reported in the literature to possess hypoglycemic activities; for example, chlorogenic acid can inhibit the activities of α-glucosidase and α-amylase, thereby reducing the absorption and digestion of glucose, while also modulating insulin sensitivity and ameliorating insulin resistance [29,30]. Quercetin and kaempferol have been shown to ameliorate diabetic symptoms, a therapeutic effect attributed to their capacity to improve pancreatic islet function while concurrently diminishing oxidative stress and suppressing the inflammatory cascade [31,32]. Furthermore, Quercetin-3-O-β-D-glucuronide has been identified as a powerful inhibitor of α-glucosidase [33]. The enzyme inhibitory effects of Chlorogenic Acid, Quercetin, Kaempferol, and Quercetin-3-O-β-D-glucuronide have been reported in the aforementioned literature; however, those of Astragalin, 3,4-Dicaffeoylquinic Acid, and Afzelin require further experimental validation. The enzyme inhibitory mechanism of the compounds in this study was hypothesized based solely on the literature reports cited above, with no direct validation via in vitro α-glucosidase and α-amylase inhibition assays, representing a limitation of this work. Furthermore, a study using a streptozotocin-induced diabetic mouse model found that C. paliurus extract with stronger hypoglycemic effects has a higher total flavonoid content. The researchers hypothesized that the levels of Quercetin and Kaempferol were key factors contributing to this activity, although the hypoglycemic efficacy of these individual compounds was not evaluated [34].

This research further explored the differential hypoglycemic effects and underlying mechanisms of an aqueous extract and its constituent monomer compounds. Network pharmacology analysis indicated that seven compounds from the leaves of C. paliurus primarily exert their effects through pathways such as the AGE-RAGE signaling pathway, Fluid shear stress and atherosclerosis, Lipid and atherosclerosis, Pathways in cancer, and Insulin Resistance. The AGE-RAGE signaling pathway is closely associated with diabetes mellitus and its complications. In a hyperglycemic state, it activates various signaling cascades that lead to inflammation, oxidative stress, vascular endothelial dysfunction, and apoptosis. This process is therefore involved in the development of diabetes and its subsequent comorbidities, including neuropathy, cognitive impairment, nephropathy, retinopathy, atherosclerosis, and microvascular lesions [35,36,37,38]. Furthermore, complex interactions exist among diabetes, atherosclerosis, inflammation, and cancer. Patients with diabetes often exhibit a chronic inflammatory state, in which hyperglycemia stimulates the secretion of inflammatory cytokines [39]. These cytokines not only worsen insulin resistance but also contribute to the formation of atherosclerotic plaques [40]. The inflammatory response contributes to the development of atherosclerosis, primarily by inducing oxidative stress and disrupting lipid metabolism. Additionally, inflammation can promote the proliferation, invasion, and metastasis of tumor cells. Diabetes-related metabolic abnormalities may also facilitate the development of certain cancers by activating growth factor signaling pathways [41]. In this paper, molecular docking analysis showed that the main components exhibited strong binding affinity predominantly for key diabetes-associated target proteins, including AKT1, TNF, and IL1B. AKT1 is a critical molecule in the insulin signaling pathway, while IL1B and TNF are key inflammatory cytokines. Furthermore, RT-PCR analysis indicated that the compounds significantly upregulated the expression of the AKT1 gene and markedly downregulated the expression of the TNF and IL1B genes in zebrafish. These findings suggest that in the case of β-cell damage, the experimental sample exerts a glucose-lowering effect by regulating inflammatory pathways and potentially enhancing residual insulin signaling.

Interestingly, our findings complement those of Lin et al. Their study focused on 39 triterpenoid compounds in C. paliurus and, through network pharmacology, identified that their hypoglycemic activity was primarily associated with targets such as PTGS2, VEGFA, and CASP3, which are more directly linked to prostaglandin synthesis (inflammation), angiogenesis, and apoptosis [16]. This comparison clearly indicates that different chemical classes of compounds in C. paliurus may exert their hypoglycemic effects via distinct molecular targets and signaling pathways. Far from being contradictory, this collective evidence corroborates the complexity and sophistication of the “multi-component, multi-target” mode of action characteristic of herbal medicines.

Quantitative analysis revealed that the total content of seven identified compounds in the tender leaves of C. paliurus was 67.16 mg/g. The aqueous extract exhibited a significant hypoglycemic effect at a concentration of 200 mg/g (based on crude drug weight). At this concentration, the content of the seven specified compounds was substantially lower than the LC_0_. Therefore, it is speculated that the hypoglycemic activity of the aqueous extract may be due to the synergistic effects of these compounds; however, further research is needed to confirm these synergistic effects.

5. Conclusions

In this study, the primary chemical constituents of the aqueous extract of C. paliurus leaves and its hypoglycemic mechanism were systematically elucidated. Seven compounds were isolated and identified from the extract, and their contents in the leaves were determined. Through network pharmacology combined with molecular docking technology, these components were predicted to exert hypoglycemic effects by regulating key targets such as AKT1, TNF, and IL1B. Experimental validation using a hyperglycemic zebrafish model demonstrated that the hypoglycemic mechanism was associated with the down-regulation of TNF and IL1B expression and the up-regulation of AKT1 protein levels. This study provides new insights for an in-depth understanding of the hypoglycemic material basis and molecular mechanism of C. paliurus leaves, lays a scientific foundation for its further development and utilization in the field of diabetes, and also offers a theoretical basis for the discovery of multi-target hypoglycemic active components from food sources.