To ensure the accuracy and efficacy of clinical medication for DVT in the prevention and treatment of COVID-19 using associated drug combinations, this study conducted a statistical analysis of the dosages of traditional Chinese medicines involved in the identified drug combinations. The results showed that the primary dosage ranges for Danggui, Taoren, Honghua, Chishao, and Chuanxiong were all 10–15 g, while the primary dosage range for Niuxi was 10–18 g (Table 3).

2.5 Mechanistic Analysis of the Core Drug Combination for Antithrombotic Effects Based on Network Pharmacology

2.5.1 Collection of information on the active ingredients, molecular targets, and thrombotic targets of the core drug combination. The core drug combination consisting of Safflower, Peach Kernel, Red Peony Root, and Chuanxiong exhibits the highest confidence and the greatest degree of enhancement. On the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, http://tcmspw.com/tcmsp.php), the active constituents and molecular targets of these four herbs—Safflower, Peach Kernel, Red Peony Root, and Chuanxiong—are retrieved, with criteria set at oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18. ^[19] After removing duplicate entries and non-existent mapping relationships, 46 chemical constituents and 109 putative targets were identified. Using the GeneCards database (https://www.genecards.org/), 798 targets associated with thrombosis were retrieved.

2.5.2 Disease–Drug–Active Ingredient–Target Network and PPI Network Analysis A Venn diagram was used to identify 41 shared target proteins between the active ingredients of four traditional Chinese medicines and the disease. Protein–protein interaction data were obtained from the STRING database (https://string-db.org/), and Cytoscape software was then employed to construct the disease–drug–active ingredient–target network (Figure 3) and the PPI network (Figure 4). A barplot of the target proteins was generated using an R package (Figure 5). The disease–drug–active ingredient–target network comprises 69 nodes, including 41 target genes, 23 drug active ingredients, 4 traditional Chinese medicine names, and 1 disease name; among these, quercetin, β-sitosterol, baicalein, luteolin, kaempferol, and stigmasterol are the chemical constituents with the largest number of associated targets, as shown in Table 3. In the PPI network, the strength of interactions among target proteins is positively correlated with the size and color intensity of the corresponding circles, as well as with the thickness and color intensity of the connecting lines. The target protein barplot visually represents, in the form of a histogram, the number of nodes connected to each target protein in the PPI network; the greater the number of connected nodes, the stronger the interaction with other target proteins. Ultimately, the target proteins exhibiting the strongest interaction strengths (with more than 25 connected nodes) were identified as interleukin-6 (IL-6), vascular endothelial growth factor A (VEGFA), caspase-3 (CASP3), albumin (ALB), epidermal growth factor receptor (EGFR), and mitogen-activated protein kinase 8 (MAPK8).

2.5.3 GO and KEGG pathway enrichment analyses: GO and KEGG enrichment analyses were performed on the antithrombotic targets of the core drug combination using the database (https://org.Hs.eg.db). The ClusterProfilerGO.R package in R was used to generate advanced bubble plots for biological function and pathway enrichment analyses, focusing on the top 20 pathways. In these plots, larger bubbles indicate a greater number of enriched genes. P The lower the value, the redder the color, indicating a closer association with the core drug combination for thrombosis prevention and treatment. ^[11] . GO analysis identified 971 biological processes (BP), primarily involving oxidative stress response, homeostasis of anatomical structure, cellular response to oxidative stress, response to lipopolysaccharides, response to acidic chemical substances, and response to bacterial-derived molecules, among others. KEGG pathway enrichment analysis revealed 105 signaling pathways ( P (<0.05), primarily involving pathways such as Kaposi’s sarcoma-associated herpesvirus infection, human cytomegalovirus infection, fluid shear stress and atherosclerosis, and hepatitis B (Figures 6 and 7).

2.6 Molecular docking validation of the interactions between the common active ingredients of the core drug combination with antithrombotic activity and the core targets.

Molecular docking was performed between the core drug group and the chemically active constituents with the greatest number of intermediate targets and the core target protein IL-6, which has the highest number of connected nodes in the PPI network (Table 4), thereby validating the results obtained from network pharmacology. In molecular docking, a binding energy less than zero indicates that the ligand and receptor can bind spontaneously. ^[20] Moreover, the more stable the conformation, the lower the binding energy, and the greater the likelihood of small-molecule compounds interacting with proteins. ^[21] In this study, binding energy ≤ −20 kJ/mol was selected as the screening criterion. ^[12] Docking results indicate that all six active compounds can bind to IL-6; the docking poses are shown in Figure 8, with luteolin, quercetin, and baicalein exhibiting particularly strong binding affinities.

3 Discussion