Mechanisms of Action of Potentilla discolor Bunge in Type 2 Diabetes Mellitus Based on Network Pharmacology and Experimental Verification in Drosophila

Introduction

Diabetes mellitus (DM) is a persistent metabolic disorder characterized by elevated blood glucose levels, presenting a complex pathogenesis and substantial risks.¹ In particular, type 2 diabetes mellitus (T2DM) dominates, contributing to >90% of all diabetes cases through insulin resistance (IR) and β-cell dysfunction.² T2DM emerges when declining insulin efficacy triggers excess secretion, leading to hyperinsulinemia attributed to the mismatch between insulin resistance and inadequate compensatory insulin secretion.³ Although conventional treatments like metformin, GLP-1 receptor agonists, and insulin mitigate T2DM, challenges such as drug resistance and adverse reactions, including weight gain, hypoglycemia, gastrointestinal effects, and cardiovascular disease, persist. Traditional Chinese medicine (TCM), featuring multi-link, -target, and -pathway activation mechanisms, has demonstrated notable therapeutic effects in T2DM, with an excellent safety profile, rendering it of high research value.

Potentilla discolor Bunge (PDB) is a perennial herb belonging to the Rosaceae family with a broad distribution across Asia. It has a mild sweet-bitter taste.⁴ It is typically used in traditional medicine for its anti-inflammatory, heat-clearing, and haemostatic effects. PDB is mainly utilised to treat carbuncles, sores, damp-heat diarrhoea, lung-heat cough/asthma, and various haemorrhagic fevers.⁵ It contains various effective components such as quercetin, caffeic acid, kaempferol, protocatechuic acid, and β-sitosterol,^6,7 which exhibit antibacterial, anti-inflammatory, antioxidative, antidiarrheal, antitumor, and immunosuppressive effects. Notably, PDB has shown a substantial effect on T2DM.^8–10 Despite the known impact of PDB on insulin resistance and blood sugar levels,^11,12 its intricate mechanisms on insulin sensitivity, glucose–lipid metabolism, and oxidative stress are largely unknown and necessitate further investigation. In addition, the effective components, action targets, and molecular mechanisms of PDB in the treatment of T2DM have not yet been elucidated and warrant further investigation.

With the advantages of rapid reproduction, large numbers of offspring, simple genetic manipulation, and no stringent ethical issues,¹³ Drosophila melanogaster has emerged as an ideal experimental organism for investigating the pharmacodynamics of glucose and lipid metabolism disorders, as well as related diseases.^14,15 More than 70% of human disease genes have direct homologs in fruit flies, and many metabolic-related biochemical pathways, signaling pathways, and regulatory proteins are conserved in both fruit flies and humans^16. In contrast to the high-calorie diet-induced models of diabetes in mammals or flies,^17–19 the Cg>InR^K1409A diabetic fly model we employed in this study was developed using the GAL4/UAS expression technique, which was used to specifically express a dominantly negative form of the insulin receptor (InR) (UAS-InR^K1409A) in the fat body (equivalent to the mammalian adipose tissue and liver), thus interfering with the physiological function of the endogenous InR to cause IR and decrease the activity of insulin signaling. Therefore, this fly model may be more suitable for exploring the effects of drugs or active ingredients in treating diabetes and related diseases.

As a modern research method for exploring the relationship between drugs and diseases, Network pharmacology is a holistic and systematic approach that focuses on the interactions between drugs and targets, ensuring consistency with the holistic view, syndrome differentiation, and treatment principles of TCM, thus providing researchers with novel ideas and methods for investigation.²⁰ Thus, our study employed network pharmacology and molecular docking analyses to preliminarily identify the key components and core targets of PDB in treating T2DM. Next, we developed the Cg>InR^K1409A Drosophila diabetic model to further validate the regulatory effects among the core components and targets in vivo with the aim of exploring the underlaying molecular mechanisms of PDB extract in treating T2DM. Together, the findings reported herein provide experimental evidence and a theoretical basis for the clinical application of PDB in treating T2DM-related diseases.

Materials and Methods

Screening for Active Components and Action Targets of TCM

Screening for active ingredients and targets was performed using the TCMSP database (Supplementary Table 1) with “Fanbaicao” as the Chinese input and oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18 as the inclusion criteria.²¹ UniProt was used to retrieve the standardized protein names and genes associated with the identified targets.²² Both active components and related target gene names were then imported into Cytoscape V3.7.1 to construct an active component-target network.

Screening and Analysis of Intersecting TCM-Disease Targets

Disease targets were retrieved from OMIM, GeneCards, PharmGKB, TTD, and DrugBank (Supplementary Table 1) using “Type 2 Diabetes” as the query keyword, with the intersecting results considered as disease targets. Targets were then uploaded to the bioinformatics website for online analysis, and the obtained intersecting targets were used to construct a Venn diagram.

Construction of a Protein-Protein Interaction (PPI) Network

A PPI network was generated by importing the intersection targets into the STRING database, with the protein type set to “homo sapiens” and the medium confidence set to 0.4. The results were downloaded in TSV format and imported into Cytoscape V3.7.1. The topology of the PPI network was analyzed using the “Network Analyzer” function, and targets whose degree, betweenness, and closeness centrality were greater than or equal to the median were identified. This process was repeated in triplicate, and the results were used to construct a network of key targets.

Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) Enrichment Analysis

The TCM-disease intersection targets were input into the DAVID database with the species set to “H. sapiens”. GO functional analysis was performed on the top 10 targets and KEGG pathway enrichment analysis on the top 30 items ranked according to P values. The results were graphically presented using the bioinformatics website.

Molecular Docking Analysis

According to the sequence numbers of key targets identified in the UniProt database, three-dimensional images were downloaded from the PDB database and saved in the PDB format. Subsequently, the file was imported into Pymol, wherein non-polar hydrogens were introduced and water molecules and small molecular ligands were deleted to obtain the intended receptors. The three-dimensional structural diagrams of the main active components of PDB were downloaded from the TCMSP database and saved in mol2 format. The ligands and receptors were then imported into AutoDockTools V1.5.6 for molecular docking analysis and visual presentation.

PDB Extract Preparation

PDB samples were purchased from Beijing Tongrentang Tangshan Chain Store Drug Store Co., Ltd. (Beijing, China, No. 200401) and authenticated by Professor Wu Fanwu at the North China University of Science and Technology. PDB extraction was performed according to the method: (1) PDB whole plant was ground, and 80 g was packed into a gauze bag that was soaked in 1200 mL 70% ethanol for 48 h at 4 °C; (2) the liquid outside the gauze bag was filtered and the supernatant collected via centrifugation at 25 °C and 4200 ×g for 2 h; (3) the remaining residue was boiled in 1 L deionized water for 1 h, cooled, and centrifuged at 4200 ×g for 2 h; and (4) the supernatants from the above two steps were combined, filtered (0.45 μm), and diluted to obtain mother liquor at a concentration of 0.8 g/mL.

High-Performance Liquid Chromatography (HPLC) Analysis

HPLC to determine the representative components of PDB extract was performed using the LC-20A system (Shimadzu, Japan) with an Agilent Eclipse XDB-C18 column (4.6 × 250 mm, 5 μm) (Agilent Technologies, Inc., CA, USA). The mobile phase flow rate was set at 1 mL/min and the column temperature was 35 ± 1 °C. Standards (quercetin, kaempferol, and β-sitosterol) were obtained from the National Institute for Food and Drug Control (NIFDC). Detection was performed at a wavelength of 210 nm for β-sitosterol with methanol (A) and water (B) (A: B = 98:2) as the mobile phase, while that of quercetin and kaempferol was performed at 360 nm, with acetonitrile (C) and 0.2% phosphoric acid solution (D) (C: D = 15:85) as the mobile phase.

Drosophila Strains and Genetics

Drosophila melanogaster was grown at 25 °C under 55–65% humidity in a 12-h light/dark cycle with a culture medium comprising 50 g sucrose, 60 g cornmeal, 10 g agar, 30 g yeast, 6 mL propionic acid, and 1 L purified water. Drosophila strains w¹¹¹⁸ (#3605), Cg-GAL4 (#7011), and UAS-InR^K1409A (#8253) were purchased from the Bloomington Drosophila Stock Center (Indiana University, IN, USA). The prepared PDB extract mother liquor or the dissolved metformin mother liquor was introduced into double-distilled water and used to configure the medium with the specific concentration required for each experimental group. The fruit flies in the metformin positive control (Met) and PDB treatment groups were fed culture medium containing Met (10 mM) or PDB (2.0, 4.0, 8.0, 16.0, and 32.0 mg/mL), respectively.²³ Healthy, unmated female and male parents were randomly assigned to groups for hybridization.

Developmental and Fertility Assay

We selected 30 female and 20 male fruit fly parents from the w¹¹¹⁸ strain for crossbreeding and allowed them to lay eggs in a conventional culture medium or PDB-amended culture medium. Healthy larvae were selected 24 h after egg laying and placed in the new corresponding medium at 30 animals/tube. The numbers of pupae and fledged offspring in each tube were recorded every 4 h, and the results were used to plot a developmental curve and calculate viability.²⁴ For the fertility assay, male or female F1 flies from each group were successfully mated with healthy virgin w¹¹¹⁸ males or females. The F1 flies were classified as fertile or sterile depending on whether descendants were produced.²⁵

Measurement of Metabolites

Samples of third-instar larvae in each group were collected, washed with phosphate-buffered saline (PBS) solution, dried, and placed on slides. Haemolymph released by cuticle tearing was collected immediately, diluted by a factor of 20 with cold PBS, and measured for glucose content using HK reagent (Sigma-Aldrich, St. Louis, MO, USA, #G3293), according to Cao et al.²³ Trehalose measurement was performed by first conducting overnight digestion with porcine trehalase (Sigma-Aldrich, #T8778) at 37 °C, followed by the same procedure used for glucose measurements. The haemolymph trehalose concentration was determined by subtracting the value of free glucose from that of an untreated sample.

The third-instar larvae of each group were collected, washed with PBS, dried, placed in liquid nitrogen for rapid freezing, lysed with 100 µL of cold 0.05% PBST (PBS + 0.05% Tween-20), and ground. The powdered samples were heated at 75 °C for 10 min to remove endogenous enzymes and then cooled to 25 °C. Next, 10 μL of the homogenate was mixed with 10 μL of triglyceride (TAG) reagent (Sigma-Aldrich, #T2449) spiked with lipase, incubated for 1 h at 37 °C, and centrifuged for 3 min at 12,700 rpm. The supernatant (10 µL) was then removed and allowed to react with the free glycerol reagent (Sigma-Aldrich, #F6428), and absorbance was measured at 540 nm to determine the TAG concentration. Another 10 μL aliquot of homogenate was then centrifuged at 12,700 rpm for 3 min (without lipase treatment), and the supernatant was analysed to determine the free glycerol concentration. The TAG concentration in each sample was determined by subtracting the amount of free glycerol from that of the untreated samples. Homogenate (10 μL) was removed and measured for protein content using the bicinchoninic acid assay (Beyotime, China, #P0010). The resulting TAG per fly was normalized to obtain the soluble protein per fly.²⁶

Food Intake

Early third-instar larvae were washed with PBS and subjected to starvation for 2 h (the diet contained 0.8% agar in PBS) and fed 0.05% brilliant blue FCF (Blue-9) for 20 min, washed with PBS, dried, and ground in 100 μL of lysis buffer (PBS + 0.1% Triton X-100). The resulting mixture was subjected to a previously described protocol.²³

Immunofluorescence

The dissected larval tissues were fixed in 4% formaldehyde for 20 min at 20 °C, washed thrice in 0.3% (v/v) PBST, and stained with primary antibodies overnight at 4 °C and secondary antibodies at 25°C for 4 h. Mouse anti-Dlg1 (1:100, Developmental Studies Hybridoma Bank, #4F3 anti-discs large), rabbit anti-Akt [1:400, Cell signaling technology, MA, USA (CST), #4691], rabbit anti-p-Akt (1:400, CST, #4060), rabbit anti-cleaved Caspase 3 (1:400, CST, #9661) goat anti-mouse cyanine3 (Cy3) (1:1000, Life Technologies, CA, USA, #A10521), and goat anti-rabbit Alexa 488 (1:1000, CST, #4412) were used. Vectashield medium (Vector Laboratories, CA, USA, #H-1500) with 4′,6-diamidino-2- phenylindole was used for mounting.

Western Blotting

Whole larvae were lysed in radioimmunoprecipitation assay buffer (Beyotime, #P0013) with phosphatase inhibitor cocktail A (Beyotime, #P1082) and PMSF. Equal amounts of protein (10–30 µg, measured using bicinchoninic acid assay) were separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis, transferred to a polyvinylidene fluoride membrane, and subjected to standard WB. Rabbit anti-Akt (1:1000, CST, #4691), rabbit anti-p-Akt (1:2000, CST, #4060), rabbit anti-β-actin (1:1000, CST, #4967), and goat anti-rabbit IgG (H+L, HRP) (1:10,000, SeraCare Life Sciences Inc., MA, USA, #5220-0336) were used for incubation.

Statistical Analysis

All data were verified using at least three independent experiments. GraphPad Prism V8.0 software was used to process the results and produce bar graphs or line charts. One-way analysis of variance (ANOVA) was employed using Bonferroni’s multiple comparison test or the chi-squared test. The central values were taken as the mean, and error bars indicate the standard deviation (mean ± SD). Statistical significance was set at P < 0.05 and the central value was considered the mean.

Results

Screening for Antidiabetic Targets

The entire PDB plant (Figure 1a and b) is utilized in clinical practice. The active constituents and antidiabetic mechanism for PDB were identified using the TCMSP database, which includes key information on the components, molecular structures, key ADME (absorption, distribution, metabolism, and excretion) parameters, component-target interactions, and relevant diseases for all TCM herbal drugs listed in the Chinese Pharmacopoeia, thus meeting the requirements of network pharmacology evaluation.²⁷

Figure 1 Bioinformatic analysis of PDB ingredients and disease targets. Drawing (a) and photograph (b) of PDB. (c) Active component-target network of PDB. The blue diamond represents PDB, pink circles are the active components, orange rectangles indicate targets, and connecting lines indicate relationships among linked nodes. (d) Disease database union of OMIM, GeneCards, PharmGKB, TTD, and DrugBank.

Utilizing TCMSP data led to the identification of 17 chemical components in PDB (Supplementary Table 2), of which five met the requirements of OB ≥30% and DL ≥0.18 (Table 1): β-sitosterol, sitosterol, kaempferol, (+)-catechin, and quercetin. Other ingredients, such as lignoceric and ursolic acids, were excluded according to their OB and DL values. The five active components and corresponding 170 targets (Supplementary Table 3) were imported into Cytoscape V3.7.1 to construct a drug-active component-target network relationship diagram (Figure 1c), which included 176 nodes and 249 edges (mutual interactions between active components and targets). Then, OMIM, GeneCards, DrugBank, PharmGKB, and TTD were used to obtain 1556 T2DM disease targets (Figure 1d), and duplicates were removed, resulting in 1429 T2DM-related disease targets. The obtained component and disease targets were then uploaded to the bioinformatics website for analysis, and 107 potential targets for treating T2DM were identified (Figure 2a).

Table 1 List of Chemical Components That Met the OB and DL Limits with Their Corresponding Molecule Name and ID

Figure 2 PDB-T2DM intersecting targets and PPI network analysis. (a) Venn diagram of PDB-T2DM intersection targets. The pink circle represents T2DM targets. The green circle represents PDB targets and orange segment represents intersecting targets. (b) Protein-protein interaction (PPI) analysis. Each node represents one protein. Lines represent associations between nodes. (c–f) Core proteins in the Semen PDB-T2DM PPI network. Screening criteria were set according to the median of degree, betweenness, and closeness.

PPI Network Analysis

To analyze the drug-disease intersection targets, we generated a PPI network diagram using Cytoscape V3.7.1 by importing the 107 target genes (107 nodes, 2024 edges, and an average of 37.8 nodes) into the STRING database (Figure 2b). Triplicate topological analysis (Figure 2c–f) revealed seven key targets [Vascular endothelial growth factor A (VEGFA), Interleukin-1 beta (IL1B), tumor necrosis factor (TNF), Interleukin-6 (IL6), Caspase-3 (CASP3), RAC-alpha serine/threonine-protein kinase (AKT1), and cellular tumor antigen p53 (TP53)] (Table 2) that may be central in treating T2DM.

Table 2 Identified Key Targets Using PPI Network Analysis That May Treat T2DMa

GO and KEGG Enrichment Analysis

To investigate the cell functions that are primarily impacted by the 107 candidate targets, GO enrichment analysis was performed, with biological processes, molecular functions, and cellular components analysis resulting in 705 entries (P < 0.05) (Supplementary Figure 1a). The 550 biological process entries included the cytokine-mediated signaling pathway, hypoxia response, and lipopolysaccharide response; the 50 cellular component entries included membrane raft, transcription factor complex, and mitochondrial outer membrane; the 105 molecular function entries included enzyme binding, RNA polymerase II transcription factor activity, ligand-activated sequence-specific DNA binding RNA, and transcription coactivator binding. The KEGG pathway enrichment analysis on the 107 intersection target genes resulted in a total of 161 pathways (P < 0.05), from which the top 30 pathways related to T2DM were identified (Supplementary Figure 1b and Supplementary Table 4), including the AGE-RAGE, PI3K-Akt, and TNF pathways.

Molecular Docking Analysis

To further clarify the possible potential interactions between the active components and core targets, seven core targets (VEGFA, IL1B, TNF, IL6, CASP3, AKT1, and TP53) and their corresponding chemical compounds (quercetin, kaempferol, and β-sitosterol) were screened via molecular docking analysis (Table 3), and results with a binding energy of < −5.0 kcal/mol were visualised.²⁸

Table 3 Chemical Compounds with Corresponding Key Targets

We selected certain interactions with remarkable affinity, namely IL1B-quercetin (−6.13), IL6-quercetin (−5.15), AKT1-quercetin (−6.48), TP53-quercetin (−5.76), TNF-kaempferol (−6.18), AKT1-kaempferol (−6.85), and CASP3-β-sitosterol (−7.1). The Pymol tool facilitated the in-depth examination of receptor–ligand interactions (Figure 3). These findings highlight the potent binding capabilities of these active constituents to T2DM-associated target genes. Specifically, quercetin exhibited a strong preference for IL1B, IL6, AKT1, and TP53; kaempferol exhibited superior binding to TNF and AKT1; β-sitosterol demonstrated pronounced binding to CASP3. Notably, β-sitosterol displayed the most favorable binding to CASP3, highlighting its strong binding activity. These data verify the action of the key identified PDB components in regulating IL1B, IL6, TP53, AKT1, and CASP3 in T2DM.

Figure 3 Docking conformation of active components and core target binding sites. Molecular docking of IL1B-quercetin (a), IL6-quercetin (b), AKT1-quercetin (c), TP53-quercetin (d), TNF-kaempferol (e), AKT1-kaempferol (f), and CASP3-β-sitosterol (g). Pink structures indicate chemical compounds; yellow dotted lines indicate hydrogen bonds, numbers indicate bond length, and blue structures indicate binding residues.

Analysis of Representative Compounds Using HPLC

PDB extract was prepared, and its quality was checked. Three representative compounds were selected as quality standards according to the results of the molecular docking analysis. Compared to the peaks of the standard controls (Supplementary Figure S2), distinguished peaks visualised using HPLC (Figure 4) indicated quercetin, kaempferol, and β-sitosterol at proportions of 0.030%, 0.025%, and 0.076%, respectively (Table 4). The results suggested that PDB contained the necessary active components for further in vivo study.

Table 4 PDB Components and Relevant Characteristicsa

Figure 4 HPLC chromatogram of PDB. HPLC analysis of three chemical constituents, β-sitosterol (210 nm, a), quercetin (360 nm, b), and kaempferol (360 nm, b) in a sample of PDB. Obtained peaks are indicated by pink, blue, and green arrows. Molecular chemical formula of β-sitosterol (c), quercetin (d), and kaempferol (e).

Effect of PDB on Drosophila Development, Viability, and Fertility

Drosophila melanogaster was selected to determine whether PDB affects the normal growth, development, and reproductive capacity of living organisms. The results suggested that the white pupal curve and mean pupation time of larvae were not affected by supplementation with PDB extract in comparison with the control (Figures 5a and b), and no notable changes were observed in the viability or fertility of Drosophila adults treated with PDB (Figures 5c and d). These results indicate that PDB does not affect the development, viability, or fertility of Drosophila.

Figure 5 Effect of PDB on the development, viability, and fertility of Drosophila. Statistical analysis of the white pupae rate (a, n = 5) and time to pupariation (b, n = 5) of w1118 larvae fed normal food or PDB-treated food. For time to pupariation statistics, a one-way ANOVA with Bonferroni’s multiple comparison tests was applied; ns indicates no significant difference. For the histogram of viability (c, n = 90) and fertility (d, n = 30) in w1118 adults, the chi-squared test was applied.

Effect of PDB on Glycolipid Metabolism Disorder in Diabetic Flies

An established diabetes Drosophila model (Cg>InR^K1409A) was employed, using the GAL4/UAS expression technique to selectively disrupt insulin receptor function in the adipose tissue of flies. This was achieved by genetically introducing the dominant-negative (DN) variant of InR (UAS-InR^K1409A), which in turn caused IR in Drosophila.²³ Consistent with previous findings, a considerable increase was observed in the circulating glucose and trehalose levels in the Cg>InR^K1409A diabetic fly model (Figure 6a and b). To further investigate the anti-diabetic effect of PDB, an extract was prepared and added to the medium fed to diabetic flies from egg to the third-instar larval stage. As expected, the increased hemolymph glucose and trehalose levels were largely inhibited by both PDB extract (Figure 6a and b) and Met (10 mM). The inhibitory effect was most notable in the 4.0 mg/mL PDB extract group.

Figure 6 PDB ameliorates glycolipid metabolism disorder in diabetic flies. Assays for circulating metabolites were performed on third instar larvae: hemolymph glucose (a, 10–12 larvae per pool, n = 6), and hemolymph trehalose (b, 6–8 larvae per pool, n = 6). (c) Determination of protein content. The amount of protein indicates the soluble fraction in 0.05% PBST after heat inactivation (3 larvae per pool, n = 6). (d) Stored triglycerides (TAG) contents at larval stage relative to the protein contents of the sample to normalize the weight difference between control and other indicated groups (3 larvae per pool, n = 6). Column statistical charts of 3rd instar larvae body weight (e, n = 5) and food intake (f, 6–8 larvae per pool, n = 5). (g) Photographs showing larval body size. Scale bar, 500 μm. Error bars indicate standard deviation (SD). Statistical difference was calculated using one-way ANOVA and Bonferroni’s multiple comparison test: ****P < 0.0001, ***P < 0.001, **P < 0.01, and *P < 0.05; ns: no significant difference.

Moreover, the larval protein content, body weight, and body size were decreased in the Cg>InR^K1409A-induced diabetes fly model (Figure 6c, e and g, Supplementary Figure 3), with substantial amelioration of body weight and size associated with Met or 2.0, 4.0, 8.0, 16.0, and 32.0 mg/mL PDB (Figure 6e and g, Supplementary Figure 3). The protein content was unaffected. The reduced TAG contents of Cg>InR^K1409A were distinctly increased by Met, as well as 4.0 and 32.0 mg/mL PDB extracts, whereas treatment with 2.0, 8.0, and 16.0 mg/mL PDB had no effect (Figure 6d). The feed intake assay indicated no significant change in the ingestion rate among all groups (Figure 6f), excluding the possibility that different metabolic phenotypes are caused by changes in the feeding rate. Collectively, these results indicated that PDB could ameliorate the Cg>InR^K1409A-triggered glycolipid metabolism disorder, including the increased circulating sugar level and the decreased body weight, body size, and lipid (TAG) content of Drosophila. A PDB extract of 4.0 mg/mL was therefore selected for further experimentation.

Regulation of Akt Phosphorylation and CASP3 Expression in PDB Treatment

To further elucidate the action mechanism of PDB in the treatment of T2DM and IR based on the molecular docking results (Figure 3), two key targets, Akt and Caspase 3, were selected for validation. Firstly, Akt activity was monitored by checking its phosphorylation level via in vivo immunostaining and in vitro WB. As predicted, Cg>InR^K1409A promoted reduced Akt phosphorylation (p-Akt) levels at Ser505 (same as Ser473 in human Akt1) in the adipose tissue of flies with T2DM at the larval stage (Figure 7a, b, e, f, i, j, m, n and q–s), while total Akt levels were unchanged (Figure 7 and Supplementary Figure 4). The decrease in the p-Akt of Cg>InR^K1409A was moderately enhanced by Met or 4.0 mg/mL PDB (Figure 7c, d, g, h, k, l, o–s). However, the total Akt protein expression was unaffected by Met and PDB (Supplementary Figure 4). These results suggest that PDB improves Akt phosphorylation.

Figure 7 PDB increases Akt phosphorylation level. (a–d) Representative merged fluorescence micrographs showing Drosophila third-instar larval fat (body. Individual channels detecting only Dlg [red, (e–h)], only DAPI [blue, (i–l)], and only p-Akt [green, (m–p), fluorescent dots]. (q) Statistical analysis of the p-Akt fluorescence intensity in the indicated groups (n = 10). (r) Western blot analysis of whole-body extracts from third-instar larvae for phosphorylated Akt, total Akt, and β-actin (9 larvae per time); β-actin was used as a loading control. Groups (from left to right): Control (Cg-Gal4/+), Model (Cg-Gal4/+; UAS-InRK1409A/+), Metformin (Cg-Gal4/+; UAS-InRK1409A/+ files treated with 10 mM metformin), PDB (Cg-Gal4/+; UAS-InRK1409A/+ files treated with 4 mg/mL PDB). (s) Statistical analysis of the p-Akt/Akt relative level (n = 5). The error bars indicate the SD. One-way ANOVA with Bonferroni’s multiple comparison test was used to compute P values: ****P < 0.0001, and **P < 0.01. Scale bar, 20 μm.

Next, we examined the CASP3 expression level in larval adipose tissue cells, as it is a key protease/effector caspase cascade initiator that induces extrinsic apoptosis. Compared with the control (Figure 8a, e, i and m), immunofluorescence staining results showed an increased CASP3 expression in the diabetes model (Figure 8b, f, j and n), significant suppression by PDB, and slight suppression by Met (Figure 8c, d, g, h, k, l, o, p and q). This indicates that PDB extract may suppress CASP3 activity to improve insulin resistance in Drosophila with T2DM.

Figure 8 PDB reduces CASP3 expression. (a–d) Merged fluorescence micrographs of Drosophila third-instar larval fat body. Individual channels detecting only Dlg [red, (e–h)], only DAPI [blue, (i–l)], and only CASP3 [green, (m–p), fluorescent dots]. Groups (from left to right): Control (Cg-Gal4/+), Model (Cg-Gal4/+; UAS-InRK1409A/+), Metformin (Cg-Gal4/+; UAS-InRK1409A/+ files treated with 10 mM metformin), PDB (Cg-Gal4/+; UAS-InRK1409A/+ files treated with 4 mg/mL PDB). (q) Statistical analysis of the CASP3 fluorescence intensity in indicated groups (n =10). Error bars indicate the SD. One-way ANOVA with Bonferroni’s multiple comparison test was used to compute P values: ****P < 0.0001. Scale bar, 20 μm.

Discussion

In recent decades, the number of people with diabetes has increased globally, with T2DM accounting for more than 90% of these cases.²⁹ T2DM is a chronic metabolic disorder with a high incidence rate, which is mainly characterised by IR caused by hyperglycaemia and insufficient insulin secretion.³⁰ It can lead to an increased risk of serious complications, especially the most prevalent microvascular and macrovascular complications including kidney disease, blindness, amputation, heart disease, and stroke.³¹ Hence, there is an urgent need for the research and development of antidiabetic drugs with low toxicity and minimal side effects.

As a traditional herb, PDB has a long history of medicinal use with satisfactory drug efficacy in ameliorating diabetes and its complications.¹⁰ In particular, in some provinces in southern China, people make tea directly from PDB for the treatment of T2DM.³² Research has demonstrated that PDB has antibacterial, anti-inflammatory, antioxidant, and other pharmacological effects.^33,34 Recently, Wang et al confirmed the therapeutic effect of the water extract of Potentilla discolor Bunge (PDW) in Drosophila on diabetes via JAK/STAT signalling.³⁵ Consistently, our research demonstrated the anti-diabetic effect of PDB in Drosophila with T2DM. However, the two studies differ as follows: 1) compared to the high-sugar diet (HSD)-induced T2DM fly model (dietary change), our work involved using the Cg>InR^K1409A diabetes Drosophila model (only modification of the genotype), thus in turn causing IR and establishing a diabetic model. Given the complexity of IR during T2DM occurrence and development, applying the Cg>InR^K1409A model could better elucidate the roles of IR in diabetes and screen potential drugs or ingredients; 2) in addition to animal experiments, our work involved network pharmacology and molecular docking analysis, which provides valuable insights into exploring the molecular mechanism of PDB in treating diabetes; 3) during drug extract preparation, Wang et al used distilled water as the carrier, whereas we first ground and soaked the PDB whole plant in 70% ethanol, then combined deionized water with the extract; 4) with regards to drug dosages, Wang et al used 0.02, 0.05, 0.1, and 0.2 g/mL PDW reserve solution to the HSD fly model, while our work utilised PDB dosages of 2.0, 4.0, 8.0, 16.0, and 32.0 mg/mL; and 5) regarding the molecular mechanism, our work uncovered that PDB may improve Akt phosphorylation and suppress CASP3 activity to ameliorate insulin resistance in Drosophila with diabetes. Thus, our work on PDB provides a new experimental basis and mechanism for treating diabetes.

Herein, molecular docking analysis elucidated the three effective constituents (quercetin, kaempferol, and β-sitosterol) of PDB, possessing high binding activities with the core targets. Structurally, quercetin has two hydroxyl groups on the benzene ring, while kaempferol has only one; therefore, quercetin is slightly less hydrophobic than kaempferol. The hydrophobicity of β-sitosterol is much higher than that of quercetin and kaempferol. As shown in Table 3, the affinity of quercetin to CASP3 is slightly lower than that of kaempferol and much lower than that of β-sitosterol, which is consistent with the trend of hydrophobicity. The affinity of quercetin to the TNF/AKT1 protein is also slightly lower than that of kaempferol. Based on this, we speculate that the hydrophobicity of the drug may affect its binding activity with CASP3, which can provide valuable information for the structural modification and optimization of drug molecules in the future.

Among the active components of PDB, quercetin has been reported to have various pharmacological properties and a component of several plants. In addition, it is considered as one of the most widely used flavonoids to treat metabolic and inflammatory disorders,³⁶ with its anti-hyperglycemic effects enhancing insulin sensitivity, promoting glycogen synthesis, inhibiting α-glucosidase activity, and improving IR. Moreover, quercetin enhances glucose uptake in skeletal muscle by affecting glucose transport and insulin receptor signaling, thus improving glucose utilization.³⁷ Additionally, it can prevent diabetes by reducing oxidative stress, decreasing insulin-producing cell dysfunction, and enhancing insulin secretion from β-cells.³⁸ Kaempferol is a flavanol compound in diets and medicinal plants with antioxidant, anti-inflammatory, anti-tumor, anti-diabetic, and cardioprotective effects.³⁹ It protects against the chronic complications of T2DM by lowering blood glucose levels, improving the insulin sensitivity index, and maintaining normal blood lipid levels.⁴⁰ Previous studies demonstrate that the antidiabetic effects of kaempferol are mainly a consequence of three mechanisms: 1) improving insulin signaling and restoring the balance between glucose utilization and production, thereby improving glucose toxicity;^41,42 2) regulating lipid metabolism and improving IR to reduce lipotoxicity;^43–45 and 3) restoring the autophagy–apoptosis imbalance to protect β cells. β-sitosterol, a sterol compound and a naturally effective antioxidant, has various functions, such as the regulation of cholesterol, and anti-inflammatory, analgesic, anti-tumor, anti-oxidative stress, and anti-diabetic effects.^46–48 Several studies suggest that β-sitosterol possesses antioxidant activity, thus functioning as a modest radical scavenger and physically as a membrane stabilizer.^49,50 As a scavenger of reactive oxygen species, β-sitosterol reduces oxygen free radicals and hydrogen peroxide levels and stimulates the enzymatic antioxidant which dependant on the activation of the oestrogen receptor/PI3K pathway.⁵¹ Further, β-sitosterol has been proven to inhibit the intestinal absorption of cholesterol and elevate antioxidants, both enzymatic and non-enzymatic, making it an effective antidiabetic, hypolipidemic, neuroprotective, and chemopreventive agent. In this study, quercetin, kaempferol, and β-sitosterol were all present in the PDB extract, indicating that the anti-diabetic effect of PDB might be due to their synergistic effects, which needs further study.

Of the seven core PDB targets proteins identified for T2DM treatment, five were obtained via molecular docking analysis, namely IL1B, IL6, TP53, AKT1, and CASP3, of which IL1B is heavily involved in the pro-inflammatory process and highly associated with T2DM development.⁵² TNF-α, an inflammatory factor, is associated with metabolic disorders and can alter insulin sensitivity, weaken insulin receptor signaling, reduce glucose transporter 4 in adipocytes, and inhibit adiponectin.⁵³ Further, IL6 is a pro-inflammatory cytokine that regulates cell differentiation, migration, proliferation, and apoptosis. Studies have shown that IL6 can induce the expression of SOCS-3 (insulin signaling inhibitor), which impairs insulin receptors and insulin receptor substrate-1 phosphorylation, leading to IR.⁵⁴ TP53 is known to respond to metabolic changes, affect metabolic pathways, and can be used as a novel therapeutic target to block cardiovascular and metabolic abnormalities associated with obesity.⁵⁵ The AKT protein is a core downstream factor of insulin/PI3K/AKT signalling,^56,57 is widely expressed in insulin-sensitive tissues, and can regulate glucose metabolism by inducing downstream molecules such as Glut to enhance glucose uptake.^58,59 Cell apoptosis is also an important factor in the development of diabetes, and CASP3, currently the most important executioner protein of the caspase cascade signal pathway, is widely used as a biomarker for apoptosis.^60,61

Drosophila melanogaster is an invaluable model organism, offering insights into glucose and lipid metabolism disorders stemming from IR and T2DM.^23,62 Due to the superiority of the highly conserved circulatory system for maintaining the systemic sugar balance in flies and humans, we employed a well-established Cg>InR^K1409A diabetic Drosophila model to explore the therapeutic effect of PDB in T2DM. Based on quantification of Drosophila daily food intake and the drug dose conversion between Drosophila and humans,^63–65 PDB extract was administered into the animal medium at concentrations of 2.0, 4.0, 8.0, 16.0, or 32.0 mg/mL, which were comparable to human treatment dosages of 4.17, 8.33, 16.67, 33.33, or 66.67 g/day, respectively. In our fly assay, the circulating glucose, trehalose, and triglyceride levels during the larval stage were evaluated. Remarkably, PDB displayed optimal inhibitory effects at 4 mg/mL, mirroring the therapeutic dose of 8.33 g/day in human patients, largely aligning with the recommended dosage range for humans in the Chinese Pharmacopoeia (9–15 g/day). These findings provide valuable insights into the clinical application of PDB in treating T2DM.

Conclusion

Building upon prior research, we integrated network pharmacology, molecular docking, and in vivo animal experiments to elucidate the active constituents, targets, and mechanisms underlying the efficacy of PDB in T2DM treatment. The results demonstrate that PDB ameliorates diabetes metabolism disorders by improving Akt activity and decreasing CASP3 expression at a concentration of 4 mg/mL in Drosophila (equal to 8.33 g/day for human patients). These findings provide information on key drug targets and crucial strategies for the clinical treatment of T2DM and related metabolic diseases.