Integrated Network Pharmacology and Metabolomics Reveals the Multi-Target Mechanism of Ginsenosides in Anti-Fibrinolysis After Hip Arthroplasty

Technical Summary: Integrated Network Pharmacology and Metabolomics of Ginsenosides in Post-THA Fibrinolysis

Problem Statement
Total hip arthroplasty (THA) is a standard treatment for end-stage hip disease but is frequently complicated by postoperative hyperfibrinolysis. This condition creates a dual clinical dilemma: it increases the risk of hidden blood loss and transfusion requirements while simultaneously predisposing patients to a rebound hypercoagulable state and venous thromboembolism (VTE). Current anticoagulant prophylaxis strategies struggle to balance these "thrombosis–bleeding" risks. While Panax ginseng and its primary active components, ginsenosides, possess known anti-inflammatory and cardiovascular protective properties, their specific molecular mechanisms in regulating the postoperative fibrinolytic system following THA remain unclear.

Methodology
This study employed a dual-approach strategy integrating network pharmacology and untargeted metabolomics to elucidate the multi-target mechanism of ginsenosides.

1. Network Pharmacology Screening:

   • Component Identification: Nine active ginsenoside components (Rh7, Rh2, Rh1, Rg5, Rg3, Rg2, F3, F2, R2) were screened from TCMSP and BATMAN-TCM databases based on Oral Bioavailability (OB ≥ 20%) and Drug-Likeness (DL ≥ 0.1) parameters.
   • Target Prediction: Potential targets for these components were predicted using SwissTargetPrediction and PharmMapper. Fibrinolysis-related targets were retrieved from GeneCards and OMIM.
   • Intersection and Analysis: The intersection of ginsenoside targets and fibrinolysis targets yielded 65 key targets. A Protein-Protein Interaction (PPI) network was constructed using the STRING database and visualized via Cytoscape. Core targets were identified using the Maximal Clique Centrality (MCC) algorithm.
   • Enrichment: Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on the core targets.

2. Clinical Metabolomics:

   • Cohort: Peripheral venous blood was collected from 30 patients undergoing elective unilateral total joint arthroplasty (THA or TKA) at two time points: 2 hours preoperatively (T0) and 24 hours postoperatively (T1).
   • Analysis: Untargeted metabolomics was conducted using Ultra-High Performance Liquid Chromatography Tandem Q Exactive Mass Spectrometry (LC-MS/MS).
   • Statistical Processing: Data were processed using Compound Discoverer and SIMCA-P for Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). Differential metabolites were screened using criteria of Variable Importance in Projection (VIP) > 1 and P < 0.05. Pathway enrichment was analyzed via MetaboAnalyst.

3. Integration and Validation:

   • Network Construction: Pathways from network pharmacology and metabolomics were intersected to identify common key pathways. A "component–target–metabolic pathway" association network was constructed.
   • Molecular Docking: To validate predictions, molecular docking was performed between core targets (AKT1, PTGS2, JUN, PIK3CA) and active ginsenosides (Rh7, Rg3, Rh1, F2) using AutoDock Vina. Binding energies < -5.0 kcal/mol were considered indicative of strong affinity.

Key Results

• Target Identification: The study identified 65 intersecting targets between ginsenosides and fibrinolysis. PPI network analysis highlighted AKT1, PTGS2, and JUN as core hub genes.
• Pathway Enrichment (Network Pharmacology): KEGG analysis revealed significant enrichment in the "complement and coagulation cascades," "platelet activation," "HIF-1 signaling pathway," and "VEGF signaling pathway."
• Metabolomics Findings: The study identified 292 differential metabolites between preoperative and postoperative states. These were primarily enriched in arachidonic acid metabolism, purine metabolism, and glycerophospholipid metabolism.
• Integrated Mechanism: The intersection of both analyses identified four critical common pathways: arachidonic acid metabolism, cGMP-PKG signaling, cAMP signaling, and sphingolipid signaling.
• Molecular Docking Validation: All tested docking pairs demonstrated favorable binding affinities. Notably:
  • Ginsenoside Rh1 and PIK3CA: -9.59 kcal/mol.
  • Ginsenoside Rh7 and AKT1: -5.1 kcal/mol.
  • Ginsenoside Rg3 and JUN, and F2 and PTGS2 also showed stable hydrogen bonding interactions.

Key Contributions
This study is the first to systematically elucidate the mechanism of ginsenosides in regulating postoperative fibrinolysis following THA by integrating computational prediction with clinical metabolomic data. The research constructs a "component–target–metabolic pathway" network, demonstrating that ginsenosides do not act on a single target but rather modulate a complex network involving:

• Core Targets: AKT1, PTGS2, JUN, PIK3CA.
• Key Metabolites: Arachidonic acid, prostaglandins, and adenosine.
• Regulatory Pathways: Complement and coagulation cascades, platelet activation, and arachidonic acid metabolism.

Significance and Claims
The authors claim that this work provides a new theoretical basis for the perioperative clinical application of ginsenosides as a precision antifibrinolytic strategy. By identifying that ginsenosides regulate multiple targets and pathways (specifically the complement/coagulation cascades and arachidonic acid metabolism), the study suggests a mechanism for restoring the coagulation-fibrinolysis balance without inducing the dual risks of bleeding or thrombosis.

The paper explicitly acknowledges limitations, noting that the findings rely on database-driven predictions and a relatively small clinical cohort. It states that the conclusions require validation in larger cohorts and that future work must include in vitro and in vivo functional experiments (e.g., Western blotting, RNA interference) to verify the phenotypic consequences of regulating core targets like AKT1 and PTGS2. The study does not claim immediate clinical adoption but rather establishes a scientific foundation for such future investigations.