Integrative Analysis of the Therapeutic Mechanisms of Astragaloside IV in Idiopathic Pulmonary Fibrosis via Network Pharmacology and Molecular Validation

Integrative Analysis of the Therapeutic Mechanisms of Astragaloside IV in Idiopathic Pulmonary Fibrosis via Network Pharmacology and Molecular Validation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Integrative Analysis of the Therapeutic Mechanisms of Astragaloside IV in Idiopathic Pulmonary Fibrosis via Network Pharmacology and Molecular Validation Shanshan Chen, Jin Yan, Jing Zhang, Yiwen Ma, Yiliang Su, Yiming Yu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6797667/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Background: Astragaloside IV (AS-IV), an essential active ingredient isolated from Astragalus membranaceus, has exhibited notable antifibrotic properties in diverse disease models. However, its exact role and underlying molecular mechanisms in idiopathic pulmonary fibrosis (IPF) remain insufficiently defined. Methods: In this study, we employed an integrative approach combining transcriptomic profiling, network pharmacology, and molecular docking techniques to investigate the critical targets and signaling pathways modulated by AS-IV in the context of IPF. Differentially expressed genes obtained from lung tissue datasets of IPF patients were cross-referenced with AS-IV-associated targets to identify overlapping candidates with potential therapeutic relevance. Results: Gene enrichment analyses revealed that the PI3K-AKT pathway plays a central role in mediating AS-IV’s biological effects. Molecular docking and subsequent dynamic simulations demonstrated that AS-IV binds stably to the PIK3CA protein. In vitro experiments confirmed that AS-IV suppressed the activation of fibroblasts and decreased the expression of fibrotic markers. Furthermore, in a bleomycin-induced mouse model, AS-IV administration significantly reduced collagen accumulation and pulmonary fibrosis. Conclusion: These results collectively suggest that AS-IV exerts protective effects against IPF progression primarily through modulation of the PI3K-AKT pathway by targeting PIK3CA, supporting its potential development as a novel antifibrotic therapeutic agent. Biological sciences/Drug discovery Biological sciences/Molecular biology Health sciences/Diseases Astragaloside IV (AS-IV) idiopathic pulmonary fibrosis PI3K-AKT signaling pathway PIK3CA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction Idiopathic pulmonary fibrosis, a long-term and worsening interstitial lung disease, typified by persistent alveolar inflammation and extensive fibrotic changes that progressively impair lung function and exacerbate breathing difficulties. As the most prevalent form of pulmonary fibrosis, untreated IPF has a median survival of merely 3 to 5 years [ 1 ] . Present therapeutic strategies are primarily focused on decelerating disease advancement, alleviating symptoms, and improving patients’ quality of life. Although antifibrotic agents such as Nintedanib and Pirfenidone have demonstrated the ability to slow the decline in lung function, their clinical utility is constrained by high costs and potential side effects [ 2 , 3 ] . In cases of advanced disease, lung transplantation may be the sole curative option; however, it remains applicable only to a limited group of patients due to strict eligibility and donor availability [ 4 ] . Thus, there is a pressing demand for innovative, effective, and widely accessible treatment solutions. An increasing body of clinical and preclinical evidence supports the therapeutic value of traditional Chinese medicine (TCM) in mitigating pulmonary fibrosis, offering a promising adjunctive approach to managing this complex disease [ 5 ] . Among various TCM constituents, Astragaloside IV (AS-IV)—a principal saponin derived from Astragalus membranaceus , a classical Chinese medicinal herb—has attracted substantial interest. AS-IV is chemically categorized as a triterpenoid glycoside, consisting of an aglycone moiety conjugated to glucose and rhamnose. It exhibits multiple pharmacodynamic actions, including anti-inflammatory, antioxidative, and immune-modulating effects [ 6 ] . Despite these promising attributes, the precise mechanisms by which AS-IV alleviates pulmonary fibrosis remain to be fully elucidated. Traditional pharmacological approaches often emphasize a "one drug–one target–one disease" paradigm. In contrast, network pharmacology offers a holistic and integrative methodology capable of capturing complex drug–target–pathway interactions. This systems-level framework is well-aligned with the foundational principles of TCM, which emphasize multi-component synergy and syndrome differentiation [ 7 ] . Network pharmacology is especially suitable for studying multifactorial diseases such as IPF. Building upon this concept, the present study aims to systematically identify the molecular targets and signaling pathways modulated by AS-IV in IPF, integrating transcriptomic profiling, network-based prediction, and experimental validation to provide mechanistic insights and potential clinical translation strategies. 2 Materials and methods 2.1 Network Pharmacology Analysis 2.1.1 Selection of Differential Genes in IPF The GEO database ( https://www.ncbi.nlm.nih.gov/geo ) was searched using the keyword "Idiopathic Pulmonary Fibrosis, IPF" to retrieve gene expression profiles. The dataset GSE53845 was selected, which includes 40 IPF lung tissue samples and 8 healthy controls [ 8 ] . Following the acquisition of the normalized expression matrix, differential gene expression was analyzed via the 'limma' package in R, employing criteria of |log2FC| >0.4 and p-value < 0.05 for gene selection. 2.1.2 Collect IPF Targets IPF-related targets were collected from multiple databases, including GeneCards, OMIM, PharmGKB, TTD, DisGeNET, and DrugBank, using “Idiopathic Pulmonary Fibrosis” as the search term. After removing duplicates, the combined set of genes was considered disease-related targets. A Venn diagram was generated to visualize intersections and unique targets among databases. 2.1.3 Identification of Active Constituents of AS-IV and Prediction of Potential Targets For AS-IV, active components were identified via the TCMSP database, filtered by pharmacokinetic parameters such as oral bioavailability (OB ≥ 20%) and drug-likeness (DL ≥ 0.18). Its molecular structure was obtained from the PubChem database. Target prediction was performed using SUPER-PRED and Swiss Target Prediction. All predicted targets were normalized to gene symbols for integration with disease data. 2.1.4 Target Acquisition Intersection analysis was conducted among the predicted AS-IV targets, IPF-related DEGs, and disease-associated genes. The overlapping genes were visualized via a Venn diagram and considered as potential therapeutic targets of AS-IV in IPF. 2.1.5 Functional Enrichment Analysis Functional annotation, including Gene Ontology (GO) for biological processes, cellular components, and molecular functions, as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, was performed with the 'clusterProfiler' package in R. Terms with p-values below 0.05 were deemed significant and utilized to infer the molecular mechanisms by which AS-IV may exert therapeutic effects against IPF. 2.1.6 Analysis of Target Gene Interactions and Key Gene Screening Shared targets were uploaded to the STRING database ( https://string-db.org/ ), specifying "Homo sapiens" as the species and applying a minimum confidence score of 0.4. The resulting protein–protein interaction (PPI) network was visualized using Cytoscape software. Key hub genes were identified using the CytoHubba plugin, based on parameters including degree, betweenness, and closeness centrality. Genes with high centrality values were regarded as core regulatory elements in IPF pathogenesis. 2.1.7 Molecular Docking and Molecular Dynamics Simulation The crystal structure of PIK3CA (PDB ID: 8EXL) was downloaded from the Protein Data Bank [ 9 ] and the 3D structure of AS-IV was retrieved from PubChem [ 10 ] and optimized using the MMFF94 force field. Molecular docking was conducted using AutoDock Vina 1.1.2 [ 11 ] . with the exhaustiveness parameter set to 32. The conformation exhibiting the lowest binding energy was selected as the starting point for molecular dynamics (MD) simulations. The best-scoring protein–ligand complex was used as the starting structure for MD simulation using AMBER 18 [ 12 ] . The system underwent 2500 steps of steepest descent and conjugate gradient minimization, then was heated to 298.15 K under NVT for 200 ps, followed by 500 ps of NVT and 500 ps of NPT equilibration. A 100 ns production run was performed under NPT conditions. Long-range electrostatic interactions were treated using the Particle Mesh Ewald (PME) method [ 13 ] , and hydrogen bonds were constrained using the SHAKE algorithm [ 14 ] , the Langevin thermostat was used for temperature control [ 15 ] , with the collision frequency γ set to 2 ps⁻¹. The system pressure was 1 atm, the integration time step was 2 fs, and trajectories were saved every 10 ps for subsequent analysis. 2.1.8 MM/GBSA Binding Free Energy Calculation Binding free energy between AS-IV and the protein was calculated using the MM/GBSA method [ 16 , 17 ] . Long molecular dynamics simulations may negatively impact the accuracy of MM/GBSA calculations; therefore, in this study, MD trajectories from 45–50 ns were used for the calculations. The specific formula is as follows: $$\:{{\Delta\:}G}_{bind}={{\Delta\:}\text{G}}_{\text{c}\text{o}\text{m}\text{p}\text{l}\text{e}\text{x}}\:-\:({{\Delta\:}\text{G}}_{\text{r}\text{e}\text{c}\text{e}\text{p}\text{t}\text{o}\text{r}}+\:{{\Delta\:}\text{G}}_{\text{l}\text{i}\text{g}\text{a}\text{n}\text{d}})$$ $$\:={{\Delta\:}\text{E}}_{\text{i}\text{n}\text{t}\text{e}\text{r}\text{n}\text{a}\text{l}}+{{\Delta\:}\text{E}}_{\text{V}\text{D}\text{W}}+{{\Delta\:}\text{E}}_{\text{e}\text{l}\text{e}\text{c}}{+{\Delta\:}\text{G}}_{\text{G}\text{B}}+{{\Delta\:}\text{G}}_{\text{S}\text{A}}$$ In the formula, \(\:{{\Delta\:}\text{E}}_{\text{i}\text{n}\text{t}\text{e}\text{r}\text{n}\text{a}\text{l}}\) represents the internal energy, \(\:{{\Delta\:}\text{E}}_{\text{V}\text{D}\text{W}}\) represents the van der Waals interactions, and \(\:{{\Delta\:}\text{E}}_{\text{e}\text{l}\text{e}\text{c}}\) represents the electrostatic interactions. Internal energy includes bond energy (Ebond), angle energy (Eangle), and torsion energy (Etorsion). \(\:{{\Delta\:}\text{G}}_{\text{G}\text{B}}\) and \(\:{{\Delta\:}\text{G}}_{\text{G}\text{A}}\) together represent the solvation free energy, where GGB is the polar solvation free energy, and GSA is the nonpolar solvation free energy. For ΔG_GB, the GB model developed by Nguyen et al was used for calculation (igb = 2) [ 18 ] . The nonpolar solvation free energy (ΔGSA) was calculated based on the product of the surface tension (γ) and the solvent-accessible surface area (SA), with ΔGSA = 0.0072 × ΔSASA [ 19 ] . Entropy changes were neglected in this study due to the high computational cost and low accuracy [ 20 ] . 2.2 Experimental validation 2.2.1 The culture and handling of cells Human lung fibroblasts were maintained in DMEM supplemented with 10% fetal bovine serum (FBS) at 37°C in a humidified incubator with 5% CO₂. Upon reaching 70–80% confluence, the medium was switched to serum-free DMEM and cultured for an additional 24 hours. Cells from passages 2–3 were used in subsequent experiments. Fibrotic modeling was induced by treating cells with 10 ng/mL TGF-β1 for 48 hours [ 21 ] . 2.2.2 Cell viability assay Cell viability was evaluated using the CCK-8 assay. HLFs (5×10³ cells/well) were seeded in 96-well plates, and after cell attachment, the medium was replaced with fresh DMEM containing varying concentrations of AS-IV (0.1, 1, 10, 50, 100, and 1000 µM). After a 48-hour incubation period, 10 µL of CCK-8 reagent was added to each well, followed by a 1-hour incubation at 37°C. Absorbance was measured at 450 nm using a microplate reader (Thermo Fisher Scientific, Model 1510). 2.2.3 Cell grouping ①Control group: treated with DMEM only; ②TGF-β1 group: treated with 10 ng/mL TGF-β1; ③TGF-β1 + AS-IV group: treated with 10 ng/mL TGF-β1 and 50 µM AS-IV; ④TGF-β1 + si-NC group: transfected with siRNA negative control, then treated with 10 ng/mL TGF-β1; ⑤TGF-β1 + si-PIK3CA group: transfected with siRNA targeting PIK3CA, then treated with TGF-β1; ⑥TGF-β1 + si-PIK3CA + AS-IV group: transfected with si-PIK3CA and treated with both TGF-β1 and 50 µM AS-IV. 2.2.4 Western blot Total protein was extracted from HLFs and mouse lung tissues using RIPA lysis buffer (Beyotime, Shanghai, China). Protein concentration was quantified using a BCA protein assay kit (Servicebio, China). Equal quantities of protein samples were loaded onto 4–12% SurePAGE gels (GenScript, USA) for SDS-PAGE and then transferred onto PVDF membranes. Membranes were blocked with 5% bovine serum albumin (BSA) or non-fat milk at room temperature for 1 hour and incubated overnight at 4°C with primary antibodies (dilution 1:1000). Following TBST washes, HRP-conjugated secondary antibodies (1:1000) were applied for 1 hour at room temperature. Detection was performed with ECL reagents, and images were captured using a Tanon 5200 imaging system. Band intensities were quantified using ImageJ software. Membranes were stripped and reprobed when necessary. All experiments were independently repeated at least three times. 2.2.5 Animal grouping and intervention Six-week-old male C57BL/6 mice were purchased from Jiangsu Jicao Biotechnology (License: SCXK(SU)2023-0042) and housed under SPF conditions at the Hongqiao International Medical Research Institute, Shanghai Tongren Hospital. Mice were randomly divided into four groups (n = 6/group): Control, BLM, BLM + AS-IV low-dose (50 µM), and BLM + AS-IV high-dose (100 µM). Bleomycin (BLM; 2 mg/kg, 40 µL/mouse) was administered intratracheally on Day 0 under anesthesia. The control group received saline. On Day 21, AS-IV was dissolved in 0.5% CMC and administered orally every other day for the low-dose group and daily for the high-dose group. The control and BLM groups received an equivalent volume of CMC. All treatments lasted until Day 35. At the endpoint, mice were sacrificed, and lung tissues were collected. Samples were either fixed in 4% paraformaldehyde for histological examination or stored at − 80°C for molecular analyses. All methods were performed in accordance with ARRIVE guidelines( https://arriveguidelines.org ). This study has been approved by the Ethics Committee of Tongren Hospital (Ethics Approval Number: 2024 − 164). 2.2.6 Histopathological analysis Lung tissues collected on Day 35 were fixed in 4% paraformaldehyde for 24 hours, followed by paraffin embedding and sectioning. Sections were stained with hematoxylin and eosin (H&E) and Masson’s trichrome. Slides were scanned using a Leica slide scanner and assessed for fibrosis severity using the scoring criteria established by Hubner et al. [ 22 ] . 2.2.7 Statistical Analysis All statistical analyses were performed using GraphPad Prism 10 Version 10.3.1. Graphs were prepared using Adobe Illustrator 2023. Data are presented as mean ± SEM. One-way ANOVA and unpaired t-tests were used to assess significance. A p-value < 0.05 was considered statistically significant. 3 Results 3.1 Identification of common targets between AS-IV and IPF 3.1.1 Differentially expressed genes The GSE53845 microarray dataset, comprising lung tissue samples from 40 patients diagnosed with IPF and 8 healthy individuals, was used to conduct differential gene expression analysis. Utilizing the 'limma' package in R, a total of 2,710 significantly differentially expressed genes (DEGs) were identified. Of these, 1,332 genes showed upregulation, while 1,378 were downregulated in the IPF group compared to controls. The distribution of these DEGs, in terms of adjusted p-values and log₂ fold changes, is visualized in a volcano plot (Fig. 1 A). 3.1.2 IPF target genes To collect IPF-related genes, six databases—GeneCards, OMIM, PharmGKB, TTD, DisGeNET, and DrugBank—were queried using “idiopathic pulmonary fibrosis” as the keyword. A total of 3,906 unique disease-related genes were compiled, with the following distributions: GeneCards (3,600), OMIM (115), PharmGKB (17), TTD (30), DisGeNET (803), and DrugBank (35) (Fig. 1 B). 3.1.3 Astragaloside IV targets AS-IV-related targets were predicted using SUPER-PRED and SwissTargetPrediction databases, yielding 177 and 106 targets, respectively. After eliminating redundancies, 265 unique targets remained (Fig. 1 C). 3.1.4 Identification of common gene targets A Venn analysis of the three datasets was performed, resulting in 40 common targets (Fig. 1 D). 3.1.5 Functional enrichment analysis Gene Ontology (GO) analysis showed significant enrichment in 508 biological processes (BP), 42 cellular components (CC), and 36 molecular functions (MF) (p < 0.05) (Fig. 2 A). KEGG pathway enrichment revealed 18 significantly associated pathways, with the PI3K-AKT signaling pathway being strongly implicated in IPF pathogenesis (Fig. 2 B). 3.1.6 PPI network To explore interactions among the 40 shared genes, a protein–protein interaction (PPI) network was built using the STRING database (species: Homo sapiens, interaction score > 0.4). The network contained 38 nodes and 84 edges (Fig. 2 C). Degree centrality analysis in R identified the top 10 hub genes (Fig. 2 D). Notably, PIK3CA—part of the PI3K-AKT pathway—ranked among the top hubs, suggesting it may play a pivotal role in AS-IV’s therapeutic effects against IPF. 3.1.7 Molecular docking and molecular dynamics Given the strong enrichment of the PI3K-AKT pathway, molecular docking was performed to assess the binding of AS-IV to PIK3CA. Hydrogen bonds were observed between AS-IV and residues GLN-728, SER-773, SER-854, VAL-851, ILE-771, ASN-853, ALA-775, and ARG-770, along with hydrophobic interactions with THR-856. The docking score was − 7.3 kcal/mol (Fig. 3 A), indicating a favorable binding affinity. Molecular dynamics simulations validated complex stability. RMSD analysis (Fig. 3 B) showed that the protein backbone stabilized after 20 ns, while the ligand (AS-IV) remained stably bound (within 1.5 Å deviation). RMSF analysis (Fig. 3 C) showed reduced fluctuations in local regions (e.g., residues 230–239), indicating a stabilizing effect. The radius of gyration (RoG) (Fig. 3 D) demonstrated more compact structure upon AS-IV binding. Solvent-accessible surface area (SASA) (Fig. 3 E) remained consistent for the complex but decreased for the free protein, implying structural stabilization. Binding free energy calculated via MM-GBSA was − 44.12 ± 2.53 kcal/mol, mainly driven by van der Waals, electrostatic, and polar solvation contributions (Table 1 ). Key binding residues included ILE932, GLU849, MET922, VAL850, TRP780, MET772, ILE800, VAL851, THR856, and HID855, with ILE932 and GLU849 contributing more than − 2 kcal/mol (Fig. 3 F). Hydrogen bond analysis showed 0–11 bonds during the simulation, with a typical maximum of 4 (Fig. 3 G), reinforcing the importance of hydrogen bonding in complex stability. Table 1 Binding free energies and energy components predicted by MM-GBSA method. System name AS-IV /PIK3CA Δ E vdw -55.28 ± 3.11 Δ E elec -30.54 ± 3.44 ΔG GB 49.27 ± 2.49 ΔG SA -7.56 ± 0.34 ΔG bind -44.12 ± 2.53 ΔE vdW : van der Waals energy;ΔE elec : electrostatic energy;ΔG GB : electrostatic contribution to solvation;ΔG SA : non-polar contribution to solvation;ΔG bind : binding free energy. 3.2.1 AS-IV Suppresses Phenotypic Activation of Human Lung Fibroblasts via PIK3CA in vitro To investigate whether AS-IV suppresses fibrotic activation in human lung fibroblasts (HLFs), cells were treated with various concentrations of AS-IV for 48 hours. CCK-8 assays showed no cytotoxicity at concentrations below 50 µM (Fig. 4 A). TGF-β stimulation significantly increased expression of PIK3CA, p-PI3K/PI3K, p-AKT/AKT, and fibrotic markers α-SMA, collagen I, and fibronectin (Fig. 4 B). Treatment with 50 µM AS-IV markedly reduced these expressions (Fig. 4 C). siRNA-mediated knockdown of PIK3CA produced similar inhibitory effects (Fig. 4 D). Notably, AS-IV treatment after PIK3CA silencing did not further affect marker levels (Fig. 4 E), suggesting AS-IV acts primarily through PIK3CA modulation. 3.2.2 AS-IV Inhibits Pulmonary Fibrosis in vivo A mouse model of pulmonary fibrosis was established via intratracheal bleomycin (BLM) administration, which typically induces fibrotic features by day 21 [ 23 ] . H&E staining revealed thickened alveolar septa and fibrotic changes in the BLM group. Masson staining confirmed collagen accumulation (Fig. 5 A). AS-IV was administered orally beginning on day 21 for 14 days. In both low-dose (25 mg/kg) and high-dose (50 mg/kg) AS-IV treatment groups, histological analysis showed attenuated alveolar fibrosis and reduced collagen deposition compared to the BLM group. Immunohistochemical staining showed reduced α-SMA expression, while Western blot analysis demonstrated significant downregulation of PIK3CA, p-PI3K/PI3K, and p-AKT/AKT following AS-IV treatment (P < 0.001), particularly in the high-dose group (Fig. 5 B). 4 Discussions In this study, we assessed the therapeutic potential of Astragaloside IV (AS-IV), a primary bioactive compound extracted from Astragalus membranaceus , within the framework of idiopathic pulmonary fibrosis (IPF)—a prolonged and degenerative interstitial lung condition characterized by persistent inflammation and abnormal extracellular matrix deposition [ 24 , 25 ] . Despite the availability of antifibrotic agents like pirfenidone and nintedanib, limitations related to efficacy and adverse effects highlight the need for alternative treatments. Traditional Chinese medicine (TCM) has shown promise in treating IPF, supported by historical evidence and modern pharmacological studies [ 26 , 27 ] . Astragalus has emerged as a particularly noteworthy candidate, with AS-IV identified as a core component capable of modulating fibrosis through multiple signaling pathways [ 28 ] , including TGF-β1/PI3K/Akt [ 29 ] , RAS/RAF/FoxO [ 30 ] , and TGF-β1/Smad2/3 [ 31 ] . However, the precise mechanisms and key targets of AS-IV in IPF remain incompletely understood. Network pharmacology provides a comprehensive strategy to decode the multifaceted interactions among drugs, diseases, and targets [ 32 ] . In this study, we identified 40 overlapping targets among AS-IV, IPF-related genes, and DEGs from transcriptomic datasets. KEGG enrichment analysis highlighted the PI3K-AKT pathway as a central regulatory axis. Construction of the protein–protein interaction (PPI) network revealed PIK3CA as a central hub, indicating a potentially crucial role in mediating the effects of AS-IV. Subsequent molecular docking and dynamic simulation analyses demonstrated a robust interaction between AS-IV and PIK3CA, with a calculated binding free energy of − 44.12 ± 2.53 kcal/mol. These findings support the hypothesis that AS-IV may exert its antifibrotic effects in part through targeted modulation of PIK3CA. PIK3CA is a key regulator within the PI3K-AKT signaling cascade and is well-known for its involvement in tumorigenesis [ 33 ] , particularly in breast cancer [ 34 ] , myocardial injury [ 35 ] , and vascular anomalies [ 36 ] . Although studies on PIK3CA in pulmonary fibrosis are limited, the PI3K-AKT pathway is critically involved in regulating cellular survival, proliferation, and apoptosis [ 37 ] . Hyperactivation of this pathway has been implicated in fibrosis progression, and its inhibition is known to alleviate fibrotic responses [ 38 ] . Furthermore, PI3K-AKT signaling contributes to epithelial-mesenchymal transition (EMT), a key event in IPF pathogenesis [ 39 ] . Our results demonstrate that AS-IV alleviates IPF progression by suppressing PIK3CA activity and downregulating PI3K-AKT signaling, providing functional evidence for this regulatory axis. Molecular dynamics simulations suggest that AS-IV directly binds to PIK3CA, thereby modulating downstream signals and reducing fibroblast phenotypic transformation. In vitro assays confirmed that AS-IV at 50 µM did not induce cytotoxicity but significantly attenuated TGF-β1-induced activation of fibrotic markers. Moreover, siRNA-mediated PIK3CA knockdown diminished the antifibrotic effects of AS-IV, reinforcing that its action is PIK3CA-dependent. In vivo studies further validated these findings. AS-IV administration reduced α-SMA expression in lung tissues and decreased collagen deposition, as evidenced by Masson staining. These results confirm that AS-IV has notable antifibrotic efficacy in a bleomycin-induced mouse model of IPF. In summary, AS-IV primarily attenuates the progression of pulmonary fibrosis by modulating the PI3K/Akt signaling cascade via direct engagement with PIK3CA. These results offer a strong conceptual basis for positioning AS-IV as a promising therapeutic candidate for IPF and open new avenues for targeted drug development and clinical investigation. Nevertheless, this study has certain limitations. First, TCM formulations are inherently complex, and other active components might be generated during preparation. Second, IPF pathogenesis involves multiple interconnected signaling pathways, and the full spectrum of AS-IV’s regulatory effects remains to be clarified. Finally, to comprehensively assess the safety profile of AS-IV, future studies should evaluate organ function across multiple systems in IPF animal models. Declarations Ethics approval and consent to participate The studies involving human participants were reviewed and approved by the ethics committee of Tongren Hospital, Shanghai Jiao Tong University School of Medicine. The patients/participants provided their written informed consent to participate in this study. The animal study was reviewed and approved by the ethics committee of Tongren Hospital, Shanghai Jiao Tong University School of Medicine. Patient consent for publication Not applicable. Competing interests These authors have no conflict of interest to declare. Funding This work was supported by the Changning District Science and Technology Commission (CNKW2024Y06), the Changning District Health Commission (20234Y006), the Research Fund of the Center for Community Health Care, China Hospital Development Institute, Shanghai Jiao Tong University (2024SQYL01), and the Hospital-level Research Project of Shanghai Tongren Hospital (TRYJ2021JC01). Author Contribution SSC wrote the manuscript and performed experiments. JY performed experiments. JZ analyzed data. YWM evaluated the data. SSC revised the manuscript. YMY conceived and supervised this study and acquired funding. YLS designed the research. All authors contributed to the article and approved the submitted version. Acknowledgements Not applicable. Data Availability The data generated in the present study may be requested from the corresponding author. References León-Román, F., Valenzuela, C. & Molina-Molina, M. Idiopathic pulmonary fibrosis. Med. Clin. 159 (4), 189–194 (2022). Raghu, G. et al. Idiopathic Pulmonary Fibrosis (an Update) and Progressive Pulmonary Fibrosis in Adults: An Official ATS/ERS/JRS/ALAT Clinical Practice Guideline. Am. J. Respir. Crit Care Med. 205 (9), e18–e47 (2022). Marijic, P. et al. Pirfenidone vs. nintedanib in patients with idiopathic pulmonary fibrosis: a retrospective cohort study. Respir. Res. 22 (1), 268 (2021). Balestro, E. et al. 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Astragaloside IV protects against lung injury and pulmonary fibrosis in COPD by targeting GTP-GDP domain of RAS and downregulating the RAS/RAF/FoxO signaling pathway. Phytomedicine: Int. J. phytotherapy phytopharmacology . 120 , 155066 (2023). Li, N. et al. Astragaloside IV alleviates silica–induced pulmonary fibrosis via inactivation of the TGF–β1/Smad2/3 signaling pathway. International J. Mol. medicine 47 (3). (2021). Wang, X., Wang, Z. Y., Zheng, J. H. & Li, S. TCM network pharmacology: A new trend towards combining computational, experimental and clinical approaches. Chin. J. Nat. Med. 19 (1), 1–11 (2021). Judd, S. et al. Access to innovative therapies in pediatric oncology: Report of the nationwide experience in Canada. Cancer Med. 13 (3), e7033 (2024). Han, B. Y. et al. Clinical sequencing defines the somatic and germline mutation landscapes of Chinese HER2-Low Breast Cancer. Cancer Lett. 588 , 216763 (2024). Wu, X. et al. Integrated analysis and validation of ferroptosis-related genes and immune infiltration in acute myocardial infarction. BMC Cardiovasc. Disord. 24 (1), 123 (2024). Castillo, S. D., Baselga, E. & Graupera, M. PIK3CA mutations in vascular malformations. Curr. Opin. Hematol. 26 (3), 170–178 (2019). Zhao, S. et al. Inhibitor of growth 3 induces cell death by regulating cell proliferation, apoptosis and cell cycle arrest by blocking the PI3K/AKT pathway. Cancer Gene Ther. 25 (9–10), 240–247 (2018). Wang, J. et al. Targeting PI3K/AKT signaling for treatment of idiopathic pulmonary fibrosis. Acta Pharm. Sinica B . 12 (1), 18–32 (2022). Li, J. et al. Tangeretin attenuates bleomycin-induced pulmonary fibrosis by inhibiting epithelial-mesenchymal transition via the PI3K/Akt pathway. Front. Pharmacol. 14 , 1247800 (2023). Additional Declarations No competing interests reported. Supplementary Files originalblots.pdf Cite Share Download PDF Status: Published Journal Publication published 12 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 01 Sep, 2025 Reviews received at journal 26 Aug, 2025 Reviewers agreed at journal 26 Aug, 2025 Reviews received at journal 20 Aug, 2025 Reviewers agreed at journal 11 Aug, 2025 Reviewers agreed at journal 07 Aug, 2025 Reviewers agreed at journal 07 Aug, 2025 Reviewers invited by journal 04 Aug, 2025 Editor assigned by journal 04 Aug, 2025 Editor invited by journal 16 Jun, 2025 Submission checks completed at journal 09 Jun, 2025 First submitted to journal 09 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6797667","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":495580279,"identity":"35e3d9a4-d902-4f42-8e54-ab22dec00f91","order_by":0,"name":"Shanshan Chen","email":"","orcid":"","institution":"Tongren Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shanshan","middleName":"","lastName":"Chen","suffix":""},{"id":495580282,"identity":"604a5656-30a4-424c-a7b5-9a4181cfbfff","order_by":1,"name":"Jin Yan","email":"","orcid":"","institution":"Tongren Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jin","middleName":"","lastName":"Yan","suffix":""},{"id":495580284,"identity":"82302e81-8471-46e3-b7bc-b2762ec896cd","order_by":2,"name":"Jing Zhang","email":"","orcid":"","institution":"Tongren Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Zhang","suffix":""},{"id":495580285,"identity":"13440666-d626-4491-a355-714de5176419","order_by":3,"name":"Yiwen Ma","email":"","orcid":"","institution":"Tongren Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yiwen","middleName":"","lastName":"Ma","suffix":""},{"id":495580286,"identity":"950a2e2f-e1cc-4006-98db-b3f4d2195a58","order_by":4,"name":"Yiliang Su","email":"","orcid":"","institution":"Tongren Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yiliang","middleName":"","lastName":"Su","suffix":""},{"id":495580287,"identity":"93e6f849-5ba2-4b99-a720-f78e15ed08a7","order_by":5,"name":"Yiming Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIie3PsUvDQBTH8XcErsurWV84iP/ClUAcLPRfSSjE5QZHx0AhXSyu+me4FMcngbgEXDvGJS4OWbOI1+LYNHVzuO/4uA/8DsDl+oct3lfMyR2hnOTy95aMmF2VNl09Dy+QzyVsotlTkUUhJWcSkXOsUJZpEXy2H70pwZ8YDf3LMPG8PFOIlihzFU23JQT3X1ps6mEigSuFdCBSCUv0zmhPFMMEwT5GvR/21ga9JYsxQrD0Zo9JFkmCmPbDNI0QTZVoOp6HEk2sptsbpLq9fd2cIv5Dx+k34eX6MOw69NfL56Y/QY58zsZ/AC6Xy+U60g/EW1CyFMH/ngAAAABJRU5ErkJggg==","orcid":"","institution":"Tongren Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yiming","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2025-06-01 21:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6797667/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6797667/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-23354-8","type":"published","date":"2025-11-12T15:57:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88502841,"identity":"827ca366-d686-4d55-9220-5c6aa0b895a8","added_by":"auto","created_at":"2025-08-07 07:02:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1783336,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Transcriptome volcano plot analysis of clinical samples. Red dots represent upregulated genes, while green dots represent downregulated genes. Black dots indicate genes with no significant differences in expression. (B) Network pharmacology analysis of IPF-related genes. (C) AS-IV target prediction. (D) Venn diagram of overlapping targets across the three datasets.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6797667/v1/f47711078fffdb5e30e879ed.png"},{"id":88501415,"identity":"73ca822d-8a47-4b86-a381-e738c3bd0e64","added_by":"auto","created_at":"2025-08-07 06:54:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5011785,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Gene Ontology (GO) analysis of common targets (top 10). Red indicates biological processes, green represents cellular components, and green represents molecular functions. (B) KEGG pathway enrichment analysis of common targets (top 18). The size of the bubble reflects the pathway count, while the colors indicate the significance of the p-value. (C) Protein-protein interaction (PPI) network of common targets. (D) Degree value ranking of target genes.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6797667/v1/8c2acfd22412d67affdc7ea6.png"},{"id":88501451,"identity":"37bad47d-1aeb-4204-aebd-b215a243a513","added_by":"auto","created_at":"2025-08-07 06:54:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":23503879,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Binding mode of AS-IV and PIK3CA during molecular dynamics simulation (MDS). Left: global view; right: local view. Wheat color indicates AS-IV, yellow dashed lines represent hydrogen bonds, and gray dashed lines show hydrophobic interactions. (B) Root Mean Square Deviation (RMSD) profile of AS-IV and PIK3CA during MDS. (C) Root Mean Square Fluctuation (RMSF) profile of PIK3CA with or without a ligand during MDS. (D) Radius of Gyration (RoG) profile of PIK3CA with and without AS-IV during MDS. (E) Solvent Accessible Surface Area (SASA) profile of PIK3CA with and without AS-IV during MDS. (F) Top 10 amino acids contributing to the binding of small molecules and protein complexes. (G) Variations in the number of hydrogen bonds between AS-IV and PIK3CA during MDS.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6797667/v1/5f5cb6a7aeab72d04fc425cf.png"},{"id":88501215,"identity":"5d41e665-b63f-4880-a520-1f0180ed3346","added_by":"auto","created_at":"2025-08-07 06:54:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":56586780,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Human lung fibroblasts treated with varying concentrations of AS-IV were analyzed using the CCK-8 assay. **p \u0026lt; 0.01, compared to 0.1% DMSO (n = 6). (B-E) Protein expression levels of PIK3CA, p-PI3K/PI3K, p-AKT/AKT, α-SMA, Col-I, and FN in different intervention groups, followed by semi-quantitative analysis (n ≥ 3). **p \u0026lt; 0.01, compared to control; ***p \u0026lt; 0.001, compared to control; ##p \u0026lt; 0.01, compared to TGF-β1; ###p \u0026lt; 0.001, compared to TGF-β1. All statistical analyses were performed using GraphPad Prism 10 Version 10.3.1. Graphs were prepared using Adobe Illustrator 2023.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6797667/v1/17c14190b4cf515b2ea4a5c4.png"},{"id":88501210,"identity":"5079772b-0580-4cbc-9402-de92c9c8d7d0","added_by":"auto","created_at":"2025-08-07 06:54:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":24865303,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Representative images of lung tissue stained with H\u0026amp;E, PAS, Masson, and PIK3CA immunohistochemistry after 14 days of AS-IV treatment (n = 6). Scale bar: 200 μm, original magnification X5. Mean IOD value = total IOD value/total lung tissue area in the same study group. (B) Protein expression levels of PIK3CA, p-PI3K/PI3K, p-AKT/AKT, α-SMA, Col-I, and FN in DKD model mice (n = 3). ***p \u0026lt; 0.001, compared to control; ##p \u0026lt; 0.01, compared to BLM; ###p \u0026lt; 0.001, compared to BLM. All statistical analyses were performed using GraphPad Prism 10 Version 10.3.1. Graphs were prepared using Adobe Illustrator 2023.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6797667/v1/48e660fdead208a401af9b87.png"},{"id":96105021,"identity":"84e97dda-e0dc-4d24-bc09-bc346e96469e","added_by":"auto","created_at":"2025-11-17 16:07:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":93018307,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6797667/v1/16953980-9aeb-45da-a76c-01dc93a07ad3.pdf"},{"id":88501199,"identity":"034d170b-ef66-47b5-afa4-71c702865a4c","added_by":"auto","created_at":"2025-08-07 06:54:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":4187729,"visible":true,"origin":"","legend":"","description":"","filename":"originalblots.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6797667/v1/f53f89a5617817a531fbfddd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrative Analysis of the Therapeutic Mechanisms of Astragaloside IV in Idiopathic Pulmonary Fibrosis via Network Pharmacology and Molecular Validation","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eIdiopathic pulmonary fibrosis, a long-term and worsening interstitial lung disease, typified by persistent alveolar inflammation and extensive fibrotic changes that progressively impair lung function and exacerbate breathing difficulties. As the most prevalent form of pulmonary fibrosis, untreated IPF has a median survival of merely 3 to 5 years \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Present therapeutic strategies are primarily focused on decelerating disease advancement, alleviating symptoms, and improving patients\u0026rsquo; quality of life. Although antifibrotic agents such as Nintedanib and Pirfenidone have demonstrated the ability to slow the decline in lung function, their clinical utility is constrained by high costs and potential side effects \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. In cases of advanced disease, lung transplantation may be the sole curative option; however, it remains applicable only to a limited group of patients due to strict eligibility and donor availability \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Thus, there is a pressing demand for innovative, effective, and widely accessible treatment solutions.\u003c/p\u003e\u003cp\u003eAn increasing body of clinical and preclinical evidence supports the therapeutic value of traditional Chinese medicine (TCM) in mitigating pulmonary fibrosis, offering a promising adjunctive approach to managing this complex disease \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Among various TCM constituents, Astragaloside IV (AS-IV)\u0026mdash;a principal saponin derived from \u003cem\u003eAstragalus membranaceus\u003c/em\u003e, a classical Chinese medicinal herb\u0026mdash;has attracted substantial interest. AS-IV is chemically categorized as a triterpenoid glycoside, consisting of an aglycone moiety conjugated to glucose and rhamnose. It exhibits multiple pharmacodynamic actions, including anti-inflammatory, antioxidative, and immune-modulating effects \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Despite these promising attributes, the precise mechanisms by which AS-IV alleviates pulmonary fibrosis remain to be fully elucidated.\u003c/p\u003e\u003cp\u003eTraditional pharmacological approaches often emphasize a \"one drug\u0026ndash;one target\u0026ndash;one disease\" paradigm. In contrast, network pharmacology offers a holistic and integrative methodology capable of capturing complex drug\u0026ndash;target\u0026ndash;pathway interactions. This systems-level framework is well-aligned with the foundational principles of TCM, which emphasize multi-component synergy and syndrome differentiation \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Network pharmacology is especially suitable for studying multifactorial diseases such as IPF. Building upon this concept, the present study aims to systematically identify the molecular targets and signaling pathways modulated by AS-IV in IPF, integrating transcriptomic profiling, network-based prediction, and experimental validation to provide mechanistic insights and potential clinical translation strategies.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Network Pharmacology Analysis\u003c/h2\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003e2.1.1 Selection of Differential Genes in IPF\u003c/h2\u003e\u003cp\u003eThe GEO database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/geo\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was searched using the keyword \"Idiopathic Pulmonary Fibrosis, IPF\" to retrieve gene expression profiles. The dataset GSE53845 was selected, which includes 40 IPF lung tissue samples and 8 healthy controls \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Following the acquisition of the normalized expression matrix, differential gene expression was analyzed via the 'limma' package in R, employing criteria of |log2FC| \u0026gt;0.4 and p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for gene selection.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.1.2 Collect IPF Targets\u003c/h2\u003e\u003cp\u003eIPF-related targets were collected from multiple databases, including GeneCards, OMIM, PharmGKB, TTD, DisGeNET, and DrugBank, using \u0026ldquo;Idiopathic Pulmonary Fibrosis\u0026rdquo; as the search term. After removing duplicates, the combined set of genes was considered disease-related targets. A Venn diagram was generated to visualize intersections and unique targets among databases.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.1.3 Identification of Active Constituents of AS-IV and Prediction of Potential Targets\u003c/h2\u003e\u003cp\u003eFor AS-IV, active components were identified via the TCMSP database, filtered by pharmacokinetic parameters such as oral bioavailability (OB\u0026thinsp;\u0026ge;\u0026thinsp;20%) and drug-likeness (DL\u0026thinsp;\u0026ge;\u0026thinsp;0.18). Its molecular structure was obtained from the PubChem database. Target prediction was performed using SUPER-PRED and Swiss Target Prediction. All predicted targets were normalized to gene symbols for integration with disease data.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.1.4 Target Acquisition\u003c/h2\u003e\u003cp\u003eIntersection analysis was conducted among the predicted AS-IV targets, IPF-related DEGs, and disease-associated genes. The overlapping genes were visualized via a Venn diagram and considered as potential therapeutic targets of AS-IV in IPF.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.1.5 Functional Enrichment Analysis\u003c/h2\u003e\u003cp\u003eFunctional annotation, including Gene Ontology (GO) for biological processes, cellular components, and molecular functions, as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, was performed with the 'clusterProfiler' package in R. Terms with p-values below 0.05 were deemed significant and utilized to infer the molecular mechanisms by which AS-IV may exert therapeutic effects against IPF.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.1.6 Analysis of Target Gene Interactions and Key Gene Screening\u003c/h2\u003e\u003cp\u003eShared targets were uploaded to the STRING database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), specifying \"Homo sapiens\" as the species and applying a minimum confidence score of 0.4. The resulting protein\u0026ndash;protein interaction (PPI) network was visualized using Cytoscape software. Key hub genes were identified using the CytoHubba plugin, based on parameters including degree, betweenness, and closeness centrality. Genes with high centrality values were regarded as core regulatory elements in IPF pathogenesis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.1.7 Molecular Docking and Molecular Dynamics Simulation\u003c/h2\u003e\u003cp\u003eThe crystal structure of PIK3CA (PDB ID: 8EXL) was downloaded from the Protein Data Bank \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e and the 3D structure of AS-IV was retrieved from PubChem \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e and optimized using the MMFF94 force field. Molecular docking was conducted using AutoDock Vina 1.1.2 \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. with the exhaustiveness parameter set to 32. The conformation exhibiting the lowest binding energy was selected as the starting point for molecular dynamics (MD) simulations.\u003c/p\u003e\u003cp\u003eThe best-scoring protein\u0026ndash;ligand complex was used as the starting structure for MD simulation using AMBER 18 \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. The system underwent 2500 steps of steepest descent and conjugate gradient minimization, then was heated to 298.15 K under NVT for 200 ps, followed by 500 ps of NVT and 500 ps of NPT equilibration. A 100 ns production run was performed under NPT conditions. Long-range electrostatic interactions were treated using the Particle Mesh Ewald (PME) method \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, and hydrogen bonds were constrained using the SHAKE algorithm \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, the Langevin thermostat was used for temperature control \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, with the collision frequency γ set to 2 ps⁻\u0026sup1;. The system pressure was 1 atm, the integration time step was 2 fs, and trajectories were saved every 10 ps for subsequent analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.1.8 MM/GBSA Binding Free Energy Calculation\u003c/h2\u003e\u003cp\u003eBinding free energy between AS-IV and the protein was calculated using the MM/GBSA method \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Long molecular dynamics simulations may negatively impact the accuracy of MM/GBSA calculations; therefore, in this study, MD trajectories from 45\u0026ndash;50 ns were used for the calculations. The specific formula is as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{{\\Delta\\:}G}_{bind}={{\\Delta\\:}\\text{G}}_{\\text{c}\\text{o}\\text{m}\\text{p}\\text{l}\\text{e}\\text{x}}\\:-\\:({{\\Delta\\:}\\text{G}}_{\\text{r}\\text{e}\\text{c}\\text{e}\\text{p}\\text{t}\\text{o}\\text{r}}+\\:{{\\Delta\\:}\\text{G}}_{\\text{l}\\text{i}\\text{g}\\text{a}\\text{n}\\text{d}})$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:={{\\Delta\\:}\\text{E}}_{\\text{i}\\text{n}\\text{t}\\text{e}\\text{r}\\text{n}\\text{a}\\text{l}}+{{\\Delta\\:}\\text{E}}_{\\text{V}\\text{D}\\text{W}}+{{\\Delta\\:}\\text{E}}_{\\text{e}\\text{l}\\text{e}\\text{c}}{+{\\Delta\\:}\\text{G}}_{\\text{G}\\text{B}}+{{\\Delta\\:}\\text{G}}_{\\text{S}\\text{A}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the formula, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\Delta\\:}\\text{E}}_{\\text{i}\\text{n}\\text{t}\\text{e}\\text{r}\\text{n}\\text{a}\\text{l}}\\)\u003c/span\u003e\u003c/span\u003erepresents the internal energy, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\Delta\\:}\\text{E}}_{\\text{V}\\text{D}\\text{W}}\\)\u003c/span\u003e\u003c/span\u003e represents the van der Waals interactions, and\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\Delta\\:}\\text{E}}_{\\text{e}\\text{l}\\text{e}\\text{c}}\\)\u003c/span\u003e\u003c/span\u003erepresents the electrostatic interactions. Internal energy includes bond energy (Ebond), angle energy (Eangle), and torsion energy (Etorsion). \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\Delta\\:}\\text{G}}_{\\text{G}\\text{B}}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\Delta\\:}\\text{G}}_{\\text{G}\\text{A}}\\)\u003c/span\u003e\u003c/span\u003e together represent the solvation free energy, where GGB is the polar solvation free energy, and GSA is the nonpolar solvation free energy.\u003c/p\u003e\u003cp\u003eFor ΔG_GB, the GB model developed by Nguyen et al was used for calculation (igb\u0026thinsp;=\u0026thinsp;2) \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. The nonpolar solvation free energy (ΔGSA) was calculated based on the product of the surface tension (γ) and the solvent-accessible surface area (SA), with ΔGSA\u0026thinsp;=\u0026thinsp;0.0072\u0026thinsp;\u0026times;\u0026thinsp;ΔSASA \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Entropy changes were neglected in this study due to the high computational cost and low accuracy \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Experimental validation\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 The culture and handling of cells\u003c/h2\u003e\u003cp\u003eHuman lung fibroblasts were maintained in DMEM supplemented with 10% fetal bovine serum (FBS) at 37\u0026deg;C in a humidified incubator with 5% CO₂. Upon reaching 70\u0026ndash;80% confluence, the medium was switched to serum-free DMEM and cultured for an additional 24 hours. Cells from passages 2\u0026ndash;3 were used in subsequent experiments. Fibrotic modeling was induced by treating cells with 10 ng/mL TGF-β1 for 48 hours \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Cell viability assay\u003c/h2\u003e\u003cp\u003eCell viability was evaluated using the CCK-8 assay. HLFs (5\u0026times;10\u0026sup3; cells/well) were seeded in 96-well plates, and after cell attachment, the medium was replaced with fresh DMEM containing varying concentrations of AS-IV (0.1, 1, 10, 50, 100, and 1000 \u0026micro;M). After a 48-hour incubation period, 10 \u0026micro;L of CCK-8 reagent was added to each well, followed by a 1-hour incubation at 37\u0026deg;C. Absorbance was measured at 450 nm using a microplate reader (Thermo Fisher Scientific, Model 1510).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 Cell grouping\u003c/h2\u003e\u003cp\u003e①Control group: treated with DMEM only; ②TGF-β1 group: treated with 10 ng/mL TGF-β1; ③TGF-β1\u0026thinsp;+\u0026thinsp;AS-IV group: treated with 10 ng/mL TGF-β1 and 50 \u0026micro;M AS-IV; ④TGF-β1\u0026thinsp;+\u0026thinsp;si-NC group: transfected with siRNA negative control, then treated with 10 ng/mL TGF-β1; ⑤TGF-β1\u0026thinsp;+\u0026thinsp;si-PIK3CA group: transfected with siRNA targeting PIK3CA, then treated with TGF-β1; ⑥TGF-β1\u0026thinsp;+\u0026thinsp;si-PIK3CA\u0026thinsp;+\u0026thinsp;AS-IV group: transfected with si-PIK3CA and treated with both TGF-β1 and 50 \u0026micro;M AS-IV.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e2.2.4 Western blot\u003c/h2\u003e\u003cp\u003eTotal protein was extracted from HLFs and mouse lung tissues using RIPA lysis buffer (Beyotime, Shanghai, China). Protein concentration was quantified using a BCA protein assay kit (Servicebio, China). Equal quantities of protein samples were loaded onto 4\u0026ndash;12% SurePAGE gels (GenScript, USA) for SDS-PAGE and then transferred onto PVDF membranes. Membranes were blocked with 5% bovine serum albumin (BSA) or non-fat milk at room temperature for 1 hour and incubated overnight at 4\u0026deg;C with primary antibodies (dilution 1:1000). Following TBST washes, HRP-conjugated secondary antibodies (1:1000) were applied for 1 hour at room temperature. Detection was performed with ECL reagents, and images were captured using a Tanon 5200 imaging system. Band intensities were quantified using ImageJ software. Membranes were stripped and reprobed when necessary. All experiments were independently repeated at least three times.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003e2.2.5 Animal grouping and intervention\u003c/h2\u003e\u003cp\u003eSix-week-old male C57BL/6 mice were purchased from Jiangsu Jicao Biotechnology (License: SCXK(SU)2023-0042) and housed under SPF conditions at the Hongqiao International Medical Research Institute, Shanghai Tongren Hospital. Mice were randomly divided into four groups (n\u0026thinsp;=\u0026thinsp;6/group): Control, BLM, BLM\u0026thinsp;+\u0026thinsp;AS-IV low-dose (50 \u0026micro;M), and BLM\u0026thinsp;+\u0026thinsp;AS-IV high-dose (100 \u0026micro;M). Bleomycin (BLM; 2 mg/kg, 40 \u0026micro;L/mouse) was administered intratracheally on Day 0 under anesthesia. The control group received saline. On Day 21, AS-IV was dissolved in 0.5% CMC and administered orally every other day for the low-dose group and daily for the high-dose group. The control and BLM groups received an equivalent volume of CMC. All treatments lasted until Day 35. At the endpoint, mice were sacrificed, and lung tissues were collected. Samples were either fixed in 4% paraformaldehyde for histological examination or stored at \u0026minus;\u0026thinsp;80\u0026deg;C for molecular analyses. All methods were performed in accordance with ARRIVE guidelines(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://arriveguidelines.org\u003c/span\u003e\u003cspan address=\"https://arriveguidelines.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). This study has been approved by the Ethics Committee of Tongren Hospital (Ethics Approval Number: 2024\u0026thinsp;\u0026minus;\u0026thinsp;164).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e2.2.6 Histopathological analysis\u003c/h2\u003e\u003cp\u003eLung tissues collected on Day 35 were fixed in 4% paraformaldehyde for 24 hours, followed by paraffin embedding and sectioning. Sections were stained with hematoxylin and eosin (H\u0026amp;E) and Masson\u0026rsquo;s trichrome. Slides were scanned using a Leica slide scanner and assessed for fibrosis severity using the scoring criteria established by Hubner et al. \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e2.2.7 Statistical Analysis\u003c/h2\u003e\u003cp\u003eAll statistical analyses were performed using GraphPad Prism 10 Version 10.3.1. Graphs were prepared using Adobe Illustrator 2023. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. One-way ANOVA and unpaired t-tests were used to assess significance. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Identification of common targets between AS-IV and IPF\u003c/h2\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003e3.1.1 Differentially expressed genes\u003c/h2\u003e\u003cp\u003eThe GSE53845 microarray dataset, comprising lung tissue samples from 40 patients diagnosed with IPF and 8 healthy individuals, was used to conduct differential gene expression analysis. Utilizing the 'limma' package in R, a total of 2,710 significantly differentially expressed genes (DEGs) were identified. Of these, 1,332 genes showed upregulation, while 1,378 were downregulated in the IPF group compared to controls. The distribution of these DEGs, in terms of adjusted p-values and log₂ fold changes, is visualized in a volcano plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003e3.1.2 IPF target genes\u003c/h2\u003e\u003cp\u003eTo collect IPF-related genes, six databases\u0026mdash;GeneCards, OMIM, PharmGKB, TTD, DisGeNET, and DrugBank\u0026mdash;were queried using \u0026ldquo;idiopathic pulmonary fibrosis\u0026rdquo; as the keyword. A total of 3,906 unique disease-related genes were compiled, with the following distributions: GeneCards (3,600), OMIM (115), PharmGKB (17), TTD (30), DisGeNET (803), and DrugBank (35) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\u003ch2\u003e3.1.3 Astragaloside IV targets\u003c/h2\u003e\u003cp\u003eAS-IV-related targets were predicted using SUPER-PRED and SwissTargetPrediction databases, yielding 177 and 106 targets, respectively. After eliminating redundancies, 265 unique targets remained (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003e3.1.4 Identification of common gene targets\u003c/h2\u003e\u003cp\u003eA Venn analysis of the three datasets was performed, resulting in 40 common targets (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003e3.1.5 Functional enrichment analysis\u003c/h2\u003e\u003cp\u003eGene Ontology (GO) analysis showed significant enrichment in 508 biological processes (BP), 42 cellular components (CC), and 36 molecular functions (MF) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). KEGG pathway enrichment revealed 18 significantly associated pathways, with the PI3K-AKT signaling pathway being strongly implicated in IPF pathogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003e3.1.6 PPI network\u003c/h2\u003e\u003cp\u003eTo explore interactions among the 40 shared genes, a protein\u0026ndash;protein interaction (PPI) network was built using the STRING database (species: Homo sapiens, interaction score\u0026thinsp;\u0026gt;\u0026thinsp;0.4). The network contained 38 nodes and 84 edges (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Degree centrality analysis in R identified the top 10 hub genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Notably, PIK3CA\u0026mdash;part of the PI3K-AKT pathway\u0026mdash;ranked among the top hubs, suggesting it may play a pivotal role in AS-IV\u0026rsquo;s therapeutic effects against IPF.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section3\"\u003e\u003ch2\u003e3.1.7 Molecular docking and molecular dynamics\u003c/h2\u003e\u003cp\u003eGiven the strong enrichment of the PI3K-AKT pathway, molecular docking was performed to assess the binding of AS-IV to PIK3CA. Hydrogen bonds were observed between AS-IV and residues GLN-728, SER-773, SER-854, VAL-851, ILE-771, ASN-853, ALA-775, and ARG-770, along with hydrophobic interactions with THR-856. The docking score was \u0026minus;\u0026thinsp;7.3 kcal/mol (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), indicating a favorable binding affinity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eMolecular dynamics simulations validated complex stability. RMSD analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) showed that the protein backbone stabilized after 20 ns, while the ligand (AS-IV) remained stably bound (within 1.5 \u0026Aring; deviation). RMSF analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC) showed reduced fluctuations in local regions (e.g., residues 230\u0026ndash;239), indicating a stabilizing effect. The radius of gyration (RoG) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD) demonstrated more compact structure upon AS-IV binding. Solvent-accessible surface area (SASA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE) remained consistent for the complex but decreased for the free protein, implying structural stabilization.\u003c/p\u003e\u003cp\u003eBinding free energy calculated via MM-GBSA was \u0026minus;\u0026thinsp;44.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53 kcal/mol, mainly driven by van der Waals, electrostatic, and polar solvation contributions (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Key binding residues included ILE932, GLU849, MET922, VAL850, TRP780, MET772, ILE800, VAL851, THR856, and HID855, with ILE932 and GLU849 contributing more than \u0026minus;\u0026thinsp;2 kcal/mol (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). Hydrogen bond analysis showed 0\u0026ndash;11 bonds during the simulation, with a typical maximum of 4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG), reinforcing the importance of hydrogen bonding in complex stability.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBinding free energies and energy components predicted by MM-GBSA method.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystem name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAS-IV /PIK3CA\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eΔ\u003c/b\u003e\u003cb\u003eE\u003c/b\u003e\u003csub\u003e\u003cb\u003evdw\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e-55.28\u0026thinsp;\u0026plusmn;\u0026thinsp;3.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eΔ\u003c/b\u003e\u003cb\u003eE\u003c/b\u003e\u003csub\u003e\u003cb\u003eelec\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e-30.54\u0026thinsp;\u0026plusmn;\u0026thinsp;3.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eΔG\u003c/b\u003e\u003csub\u003e\u003cb\u003eGB\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e49.27\u0026thinsp;\u0026plusmn;\u0026thinsp;2.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eΔG\u003c/b\u003e\u003csub\u003e\u003cb\u003eSA\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e-7.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eΔG\u003c/b\u003e\u003csub\u003e\u003cb\u003ebind\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e-44.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eΔE\u003csub\u003evdW\u003c/sub\u003e: van der Waals energy;ΔE\u003csub\u003eelec\u003c/sub\u003e: electrostatic energy;ΔG\u003csub\u003eGB\u003c/sub\u003e: electrostatic contribution to solvation;ΔG\u003csub\u003eSA\u003c/sub\u003e: non-polar contribution to solvation;ΔG\u003csub\u003ebind\u003c/sub\u003e: binding free energy.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1 AS-IV Suppresses Phenotypic Activation of Human Lung Fibroblasts via PIK3CA in vitro\u003c/h2\u003e\u003cp\u003eTo investigate whether AS-IV suppresses fibrotic activation in human lung fibroblasts (HLFs), cells were treated with various concentrations of AS-IV for 48 hours. CCK-8 assays showed no cytotoxicity at concentrations below 50 \u0026micro;M (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). TGF-β stimulation significantly increased expression of PIK3CA, p-PI3K/PI3K, p-AKT/AKT, and fibrotic markers α-SMA, collagen I, and fibronectin (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Treatment with 50 \u0026micro;M AS-IV markedly reduced these expressions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). siRNA-mediated knockdown of PIK3CA produced similar inhibitory effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Notably, AS-IV treatment after PIK3CA silencing did not further affect marker levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE), suggesting AS-IV acts primarily through PIK3CA modulation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec30\" class=\"Section3\"\u003e\u003ch2\u003e3.2.2 AS-IV Inhibits Pulmonary Fibrosis in vivo\u003c/h2\u003e\u003cp\u003eA mouse model of pulmonary fibrosis was established via intratracheal bleomycin (BLM) administration, which typically induces fibrotic features by day 21 \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. H\u0026amp;E staining revealed thickened alveolar septa and fibrotic changes in the BLM group. Masson staining confirmed collagen accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAS-IV was administered orally beginning on day 21 for 14 days. In both low-dose (25 mg/kg) and high-dose (50 mg/kg) AS-IV treatment groups, histological analysis showed attenuated alveolar fibrosis and reduced collagen deposition compared to the BLM group. Immunohistochemical staining showed reduced α-SMA expression, while Western blot analysis demonstrated significant downregulation of PIK3CA, p-PI3K/PI3K, and p-AKT/AKT following AS-IV treatment (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), particularly in the high-dose group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4 Discussions","content":"\u003cp\u003eIn this study, we assessed the therapeutic potential of Astragaloside IV (AS-IV), a primary bioactive compound extracted from \u003cem\u003eAstragalus membranaceus\u003c/em\u003e, within the framework of idiopathic pulmonary fibrosis (IPF)\u0026mdash;a prolonged and degenerative interstitial lung condition characterized by persistent inflammation and abnormal extracellular matrix deposition \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Despite the availability of antifibrotic agents like pirfenidone and nintedanib, limitations related to efficacy and adverse effects highlight the need for alternative treatments.\u003c/p\u003e\u003cp\u003eTraditional Chinese medicine (TCM) has shown promise in treating IPF, supported by historical evidence and modern pharmacological studies\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cem\u003eAstragalus\u003c/em\u003e has emerged as a particularly noteworthy candidate, with AS-IV identified as a core component capable of modulating fibrosis through multiple signaling pathways \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e, including TGF-β1/PI3K/Akt \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, RAS/RAF/FoxO \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e, and TGF-β1/Smad2/3 \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. However, the precise mechanisms and key targets of AS-IV in IPF remain incompletely understood.\u003c/p\u003e\u003cp\u003eNetwork pharmacology provides a comprehensive strategy to decode the multifaceted interactions among drugs, diseases, and targets \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. In this study, we identified 40 overlapping targets among AS-IV, IPF-related genes, and DEGs from transcriptomic datasets. KEGG enrichment analysis highlighted the PI3K-AKT pathway as a central regulatory axis. Construction of the protein\u0026ndash;protein interaction (PPI) network revealed PIK3CA as a central hub, indicating a potentially crucial role in mediating the effects of AS-IV. Subsequent molecular docking and dynamic simulation analyses demonstrated a robust interaction between AS-IV and PIK3CA, with a calculated binding free energy of \u0026minus;\u0026thinsp;44.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53 kcal/mol. These findings support the hypothesis that AS-IV may exert its antifibrotic effects in part through targeted modulation of PIK3CA.\u003c/p\u003e\u003cp\u003ePIK3CA is a key regulator within the PI3K-AKT signaling cascade and is well-known for its involvement in tumorigenesis \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e, particularly in breast cancer \u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e, myocardial injury \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e, and vascular anomalies \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. Although studies on PIK3CA in pulmonary fibrosis are limited, the PI3K-AKT pathway is critically involved in regulating cellular survival, proliferation, and apoptosis \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. Hyperactivation of this pathway has been implicated in fibrosis progression, and its inhibition is known to alleviate fibrotic responses \u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. Furthermore, PI3K-AKT signaling contributes to epithelial-mesenchymal transition (EMT), a key event in IPF pathogenesis \u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. Our results demonstrate that AS-IV alleviates IPF progression by suppressing PIK3CA activity and downregulating PI3K-AKT signaling, providing functional evidence for this regulatory axis.\u003c/p\u003e\u003cp\u003eMolecular dynamics simulations suggest that AS-IV directly binds to PIK3CA, thereby modulating downstream signals and reducing fibroblast phenotypic transformation. In vitro assays confirmed that AS-IV at 50 \u0026micro;M did not induce cytotoxicity but significantly attenuated TGF-β1-induced activation of fibrotic markers. Moreover, siRNA-mediated PIK3CA knockdown diminished the antifibrotic effects of AS-IV, reinforcing that its action is PIK3CA-dependent.\u003c/p\u003e\u003cp\u003eIn vivo studies further validated these findings. AS-IV administration reduced α-SMA expression in lung tissues and decreased collagen deposition, as evidenced by Masson staining. These results confirm that AS-IV has notable antifibrotic efficacy in a bleomycin-induced mouse model of IPF.\u003c/p\u003e\u003cp\u003eIn summary, AS-IV primarily attenuates the progression of pulmonary fibrosis by modulating the PI3K/Akt signaling cascade via direct engagement with PIK3CA. These results offer a strong conceptual basis for positioning AS-IV as a promising therapeutic candidate for IPF and open new avenues for targeted drug development and clinical investigation.\u003c/p\u003e\u003cp\u003eNevertheless, this study has certain limitations. First, TCM formulations are inherently complex, and other active components might be generated during preparation. Second, IPF pathogenesis involves multiple interconnected signaling pathways, and the full spectrum of AS-IV\u0026rsquo;s regulatory effects remains to be clarified. Finally, to comprehensively assess the safety profile of AS-IV, future studies should evaluate organ function across multiple systems in IPF animal models.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\u003cp\u003eThe studies involving human participants were reviewed and approved by the ethics committee of Tongren Hospital, Shanghai Jiao Tong University School of Medicine. The patients/participants provided their written informed consent to participate in this study. The animal study was reviewed and approved by the ethics committee of Tongren Hospital, Shanghai Jiao Tong University School of Medicine.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003ePatient consent for publication\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThese authors have no conflict of interest to declare.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by the Changning District Science and Technology Commission (CNKW2024Y06), the Changning District Health Commission (20234Y006), the Research Fund of the Center for Community Health Care, China Hospital Development Institute, Shanghai Jiao Tong University (2024SQYL01), and the Hospital-level Research Project of Shanghai Tongren Hospital (TRYJ2021JC01).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSSC wrote the manuscript and performed experiments. JY performed experiments. JZ analyzed data. YWM evaluated the data. SSC revised the manuscript. YMY conceived and supervised this study and acquired funding. YLS designed the research. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data generated in the present study may be requested from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLe\u0026oacute;n-Rom\u0026aacute;n, F., Valenzuela, C. \u0026amp; Molina-Molina, M. Idiopathic pulmonary fibrosis. \u003cem\u003eMed. Clin.\u003c/em\u003e \u003cb\u003e159\u003c/b\u003e (4), 189\u0026ndash;194 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRaghu, G. et al. 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Pharmacol.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e, 1247800 (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Astragaloside IV (AS-IV), idiopathic pulmonary fibrosis, PI3K-AKT signaling pathway, PIK3CA","lastPublishedDoi":"10.21203/rs.3.rs-6797667/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6797667/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAstragaloside IV (AS-IV), an essential active ingredient isolated from Astragalus membranaceus, has exhibited notable antifibrotic properties in diverse disease models. However, its exact role and underlying molecular mechanisms in idiopathic pulmonary fibrosis (IPF) remain insufficiently defined.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn this study, we employed an integrative approach combining transcriptomic profiling, network pharmacology, and molecular docking techniques to investigate the critical targets and signaling pathways modulated by AS-IV in the context of IPF. Differentially expressed genes obtained from lung tissue datasets of IPF patients were cross-referenced with AS-IV-associated targets to identify overlapping candidates with potential therapeutic relevance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGene enrichment analyses revealed that the PI3K-AKT pathway plays a central role in mediating AS-IV\u0026rsquo;s biological effects. Molecular docking and subsequent dynamic simulations demonstrated that AS-IV binds stably to the PIK3CA protein. In vitro experiments confirmed that AS-IV suppressed the activation of fibroblasts and decreased the expression of fibrotic markers. Furthermore, in a bleomycin-induced mouse model, AS-IV administration significantly reduced collagen accumulation and pulmonary fibrosis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThese results collectively suggest that AS-IV exerts protective effects against IPF progression primarily through modulation of the PI3K-AKT pathway by targeting PIK3CA, supporting its potential development as a novel antifibrotic therapeutic agent.\u003c/p\u003e","manuscriptTitle":"Integrative Analysis of the Therapeutic Mechanisms of Astragaloside IV in Idiopathic Pulmonary Fibrosis via Network Pharmacology and Molecular Validation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-07 06:53:22","doi":"10.21203/rs.3.rs-6797667/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-01T19:14:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-26T08:36:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"32266939329810459388182958408338473023","date":"2025-08-26T07:03:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-20T07:52:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191236865701454518265527153468292186141","date":"2025-08-11T22:51:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"219147387448347217021872303973494007004","date":"2025-08-07T14:26:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"118595660417797793343245539491438984977","date":"2025-08-07T05:11:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-04T13:11:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-04T12:14:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-16T14:43:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-10T01:56:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-06-10T01:52:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f3874a35-3668-42e1-bb37-aa24e7de3bab","owner":[],"postedDate":"August 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":52632170,"name":"Biological sciences/Drug discovery"},{"id":52632171,"name":"Biological sciences/Molecular biology"},{"id":52632172,"name":"Health sciences/Diseases"}],"tags":[],"updatedAt":"2025-11-17T16:00:29+00:00","versionOfRecord":{"articleIdentity":"rs-6797667","link":"https://doi.org/10.1038/s41598-025-23354-8","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-12 15:57:03","publishedOnDateReadable":"November 12th, 2025"},"versionCreatedAt":"2025-08-07 06:53:22","video":"","vorDoi":"10.1038/s41598-025-23354-8","vorDoiUrl":"https://doi.org/10.1038/s41598-025-23354-8","workflowStages":[]},"version":"v1","identity":"rs-6797667","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6797667","identity":"rs-6797667","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}