Introduction: Chan-Hou-Kang-Gao (CHKG) is a classical traditional Chinese medicine (TCM) formula widely used to promote uterine involution and manage postpartum hemorrhage (PPH). However, the pharmacological basis and molecular mechanisms of CHKG in treating PPH remain largely unclear. Methods: Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was employed to systematically identify the chemical constituents of CHKG. Network pharmacology was used to predict active compounds, potential targets, and relevant signaling pathways. Protein–protein interaction (PPI) analysis and molecular docking were performed to validate the interactions between key compounds and therapeutic targets. results: 3.1. Identification and Confirmation of the Chemical Conponents of CHKG. UPLC-Q-TOF-MS/MS has emerged as a high-throughput and sensitive analytical technique for profiling complex herbal formulas38, 39. Given the structural diversity of the chemical constituents in CHKG, a full scan was performed in both positive and negative ionization modes to maximize compound coverage. The total ion chromatogram (TIC) of CHKG is displayed in Figure. (2). Based on mass fragmentation patterns and characteristic ions, a total of 173 compounds were identified in CHKG, comprising 164 unique components and 9 shared components (Table 1). These compounds were classified into 12 major categories of natural products (Figure. 3), including 57 flavonoids, 66 terpenoids, 17 organic acids, 7 alkaloids, and various other bioactive compounds. Specifically, compound attribution to individual herbs was determined as follows: 7 compounds were unique to RSM, 12 to RL, 1 to P-RR, 10 to P-RPA, 9 to P-RG, 9 to P-RA1, 7 to P-RA2, 2 to P-MMF, 1 to P-FOG, 5 to P-FHG, 7 to P-FC, and 5 to P-EC. Additionally, several compounds were detected as shared among different herbs: α-pinene between P-RA2 and RL; β-selinene and caryophyllene oxide between P-RA2 and P-CR; β-elemene, β-caryophyllene, humulene, and nerolidol between P-RA2 and AA; vitexin-2-O-rhamnoside between P-MMF and P-FC; and hesperidin between P-FC and CR. Detailed compound characteristics including retention time, molecular formula, and mass-to-charge (m/z) values in both ion modes, as well as herb sources, are listed in Table 1. 3.2. Construction of Chemical Components and Action Targets of CHKG The identification of potential pharmacological targets for the 20 constituent herbs in CHKG was conducted using the TCMIP platform. Among the detected compounds, 6 were not registered in the PubChem database and were therefore excluded. A total of 182 unique compounds were retained for further analysis. Reverse pharmacophore screening was performed using the UniProt database to map compound structures to potential protein targets. After deduplication, a total of 393 unique targets were identified. These targets were associated with active compounds derived from key herbs including AA, RSM, P-RA2, P-RPA, P-AO, P-EC, P-FC, P-RG, P-CR, RL, CR, LH, P-RA1, CP and P-MMF by reverse pharmacophore screening using the Uniprot database. 3.3. Summary of disease targets To identify therapeutic targets associated with PPH, the term “postpartum hemorrhage” was used as a keyword to search both the GeneCards and OMIM databases. A total of 313 disease-related targets were retrieved from GeneCards, while 502 were obtained from the OMIM database. After removing duplicates, 860 unique PPH-related targets were consolidated (Figure. 4). Subsequently, the predicted targets of CHKG-derived active compounds were intersected with the PPH-related targets. This comparison yielded 67 overlapping genes, which were considered potential therapeutic targets of CHKG for the treatment of PPH, as illustrated by the Venn diagram. 3.4. Compound-Target Network Analysis To further elucidate the potential pharmacological mechanisms of CHKG, a compound-target interaction network was constructed using Cytoscape software based on the 67 overlapping targets. The resulting network comprised 137 nodes and 378 edges, with an average degree of 5.518, as calculated using the Network Analyzer plugin. As shown in Figure. 5, the network includes 15 herbs (colored red), 55 active compounds (orange), and 67 target proteins (blue). The edges represent the predicted interactions between herbs, compounds, and targets. Degree centrality analysis was performed to identify core compounds. According to Table 2, the top 10 active compounds with the highest degree values were ursolic acid (17), adenosine (14), atractylenolide III (13), asiatic acid (12), kaempferol (11), luteolin (11), cyperol (11), alisol A 24-acetate (11), wogonin (10), and maslinic acid (10), suggesting that these constituents may serve as key pharmacologically active agents in the treatment of PPH. 3.5. Screening of Key Pathways of CHKG for Treating PPH GO enrichment analysis of the 67 overlapping target genes was performed using the R programming language. The analysis yielded 454 terms in the BP category, which were primarily associated with cellular responses to drugs, lipid localization, positive regulation of small molecule metabolic processes, modulation of inflammation, and response to steroid hormones. In the CC category, 9 GO terms were identified, including RNA polymerase II transcriptional regulatory complex, plasma membrane raft, glutamatergic synapse, outer plasma membrane, and cytoplasmic vesicle lumen. For the MF category, 58 annotation terms were obtained, including steroid hormone, nuclear, G protein-coupled amine receptor activitys, ligand-activated transcription factor activity, and hormone receptor binding. As shown in Figure. 6, the top 20 enriched terms from the BP, CC, and MF categories were visualized based on gene counts and statistical significance. These findings indicate that the bioactive compounds absorbed from CHKG may exert synergistic regulatory effects across multiple biological processes relevant to postpartum hemorrhage. 3.6. KEGG Pathway Enrichment Analysis KEGG pathway enrichment analysis was conducted using the R programming language on the 67 overlapping target genes to identify the biological pathways potentially involved in the therapeutic effects of CHKG against PPH. A total of 48 significantly enriched pathways (p 0.05) were identified, and the top 20 pathways, ranked by adjusted p-values, are presented in Figure. 7. The enrichment results revealed that the primary pathways were related to the immune system, endocrine system, and signal transduction. Specifically, immune-related pathways included the IL-17, C-type lectin receptor, Toll-like receptor signaling pathways, and platelet activation. Endocrine-related pathways comprised the prolactin signaling pathway, ovarian steroidogenesis, the AGE-RAGE signaling pathway in diabetic complications, and insulin resistance. Major signal transduction pathways included the TNF, cAMP, and HIF-1 signaling pathways. These KEGG enrichment results were consistent with those from the GO analysis, further suggesting that CHKG may exert therapeutic effects against PPH by modulating inflammatory responses and oxidative stress pathways. 3.7. Analyses of the PPI network To comprehensively elucidate the mechanisms of CHKG in treating PPH, PPI network was constructed based on experimentally validated interactions of the 67 overlapping targets, obtained from the STRING database. The network was visualized using Cytoscape 3.7.2, and core target proteins were identified using the CytoNCA plugin, which applies topological algorithms for network analysis. A total of 17 hub genes were identified, including IL6, TNF, PTGS2, ACTB, GAPDH, and AKT1 (Figure. 8 and Figure. S1). Among them, IL6, TNF, and PTGS2 were recognized as key nodes due to their high degree, betweenness centrality, and closeness centrality values. The size and color intensity of the nodes in the network diagram represent the degree centrality of the corresponding proteins (Table S1). As illustrated in Figure. 9, 41 active compounds derived from the 20 herbs of CHKG were found to interact with 52 vital protein targets. Functional analysis revealed that these targets are mainly involved in the endocrine system, immune system, signal transduction, cellular processes, and membrane transport, indicating that these pathways may constitute the principal signaling mechanisms through which CHKG exerts its therapeutic effects in PPH. 3.8. Molecular Docking Verification Based on the results of network pharmacology analysis, ursolic acid, adenosine, atractylenolide III, asiatic acid, and kaempferol were identified as key bioactive compounds, while TNF, IL6, and PTGS2 were recognized as central target proteins. To evaluate their potential interactions, molecular docking simulations were performed. As shown in Figure. 10, ursolic acid exhibited strong binding to IL6 (-32.50 kcal/mol), primarily through hydrophobic interactions with Glu55, Leu57, and Leu64, and polar contacts with Asn61 and Lys66. Kaempferol showed the strongest binding affinity to PTGS2 (-36.52 kcal/mol), involving hydrophobic interactions with Phe142, Tyr373, and Val538, and polar interactions with Asn375 and Arg376. Asiatic acid interacted with TNF (-31.80 kcal/mol) via hydrogen bonds with Arg82 and Gln125 and hydrophobic contacts with Leu36, Ala35, and Leu37. The binding pockets were predominantly hydrophobic, suggesting that van der Waals forces and hydrophobic effects play a key role in stabilizing the ligand–target complexes. These results support the network pharmacology predictions a
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