DF herbal granules, consisting of Rhubarb (Batch No. A2092591), Radix Aconiti Lateralis (Batch No. A2071291), and Asarum heterotropoides (Batch No. A209A882), were sourced from the Guangdong Yifang Chinese Herbal Medicine Department in a 3:4:1 ratio.

Fingerprint analysis of DF was perfomed using a Thermo Vanquish Flex Ultra Performance Liquid chromatography system coupled with a Thermo Fisher QE high-resolution mass spectrometer (ThermoFisher, USA). Separation of the DF constituents was achieved with a Thermo Scientific HyPURITY C18 column (150 × 2.1 mm, 1.6 μm). The mobile phase consisted of methanol (solvent A) and 0.1% (v/v) phosphoric acid (solvent B), with the following elution gradient: 0–5 min, 3–21% A; 5–20 min, 21–36% A; 20–32 min, 36–50% A; 32–42 min, 50–62% A; 42–50 min, 62–85% A; 50–60 min, 85–95% A. The injection volume was 1 μL, and the column temperature was maintained at 30°C. Detection was carried out at 260 nm with a flow rate of 0.2 mL/min.

Thirty-six-week-old male Sprague-Dawley (SD) rats (200 ± 20 g) were sourced from Guangdong Medical Laboratory Animal Center (Certificate NO. SCXK[Guangdong]2022-0002, Guangzhou, China). The temperature and relative humidity were maintained at 26°C and 60–70%, respectively, under a 12 h dark-light cycle. The animals were randomly divided into six groups (n = 6 per group): sham group, CCI group, low-dose DF group (DF-L), medium-dose DF group (DF-M), high-dose DF group (DF-H), and pregabalin group (PGB). The study adhered to the ethical guidelines and regulations approved by the Animal Experimentation Ethics Committee at The First Affiliated Hospital of Guangzhou University of Chinese Medicine (License No. GZTCMF1-2021100).

The CCI model was established according to previously published protocols after inducing anesthesia with an intraperitoneal injection of pentobarbital sodium (Chen et al., 2023a,b). The left sciatic nerve was carefully exposed and ligated with four silk ligatures (4-0) at an average interval of 1–2 mm. The incision was closed in layers postoperatively. In the sham group, the sciatic nerve was exposed but not ligated. Rats in the DF-L (2.4 g/kg), DF-M (4.8 g/kg), and DF-H (9.6 g/kg) groups received DF solution via oral gavage once daily for 15 days, starting on the first postoperative day. The positive control group received pregabalin solution (15 mg/kg, Batch No. J20160021, Pfizer).

After the behavioral tests on day 15 post-surgery, rats were deeply anesthetized with an intraperitoneal injection of pentobarbital (40 mg/kg). Spinal cord tissues were harvested and homogenized using a tissue homogenizer. Levels of inflammatory cytokines (IL-1β, IL-6, and TNF-α) in the spinal cord were quantified using ELISA kits (Meimian, Jiangsu, China) following the manufacturer's instructions.

Western blotting was performed to assess the protein expressions of TNF-α, TNFR1, PI3K, AKT, IKKα/β, IKBα, NF-κB, p-PI3K, p-AKT, p-IKKα/β, p-IKBα, and p-NF-κB. Briefly, spinal cord tissues were lysed in RIPA buffer (Meilunbio, Dalian, China) and centrifuged at 12,000 × g for 5 min at 4°C. The supernatant was collected after dilution and denaturation. Protein samples of 40 μg were then subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) for separation. Following electrophoresis, proteins were transferred to a polyvinylidene difluoride membrane. After blocking with TBST containing 5% skim milk powder or 1% bovine serum albumin (for phosphorylated proteins) for 2 h, membranes were incubated overnight at 4°C with primary antibodies. The membranes were then incubated with a secondary antibody (IRDye 800CW Goat anti-Rabbit, Boster, Wuhan, China). The primary antibodies used included anti-TNFα (Beyotime, Shanghai, China), anti-TNFR1 (Abclonal, Wuhan, China), anti-PI3K (Affinity, Jiangsu, China), anti-AKT (Affinity, Jiangsu, China), anti-IKKα/β (Affinity, Jiangsu, China), anti-IKBα (Affinity, Jiangsu, China), anti-NF-κB (Affinity, Jiangsu, China), anti-p-PI3K (Affinity, Jiangsu, China), anti-p-AKT (Affinity, Jiangsu, China), anti-p-IKKα/β (Affinity, Jiangsu, China), anti-p-IκBα (Affinity, Jiangsu, China), anti-p-NF-κB (Affinity, Jiangsu, China), and anti-GAPDH (Goodhere, Hangzhou, China). Bands were quantified using Image-Pro Plus 6.0.

Immunofluorescence assays were conducted following established protocols. Briefly, spinal cord tissues were dehydrated with increasing concentrations of alcohol and subsequently cleared with xylene. The cleared tissues were embedded in paraffin, and sections were prepared using a microtome. Paraffin was removed from the sections, and antigen retrieval was performed with an electric heat-retrieval device. Normal serum was applied around the sections for blocking. Diluted primary antibodies were added and incubated overnight. Following washes, sections were treated with Cy3-labeled goat anti-rabbit IgG secondary antibody (Boster, Wuhan, China). Nuclear staining was achieved using DAPI. Excess liquid was removed, and sections were mounted and visualized under a fluorescence microscope. The primary antibodies utilized included anti-TNFR1 (Abclonal, Wuhan, China), anti-TNF-α (Beyotime, Shanghai, China), and anti-p-NF-κB (Affinity, Jiangsu, China).

For molecular docking, the three-dimensional structure of the target protein was retrieved from the Protein Data Bank (PDB). The protein was then optimized using specialized software such as PyMOL or Chimera. During optimization, water molecules were removed, missing hydrogen atoms were added, and any non-standard residues were corrected to ensure a reliable protein structure. The three-dimensional structure of the ligand was obtained from a relevant database like PubChem, and the ligand was optimized using molecular editing software such as Open Babel or Avogadro. This optimization involved adding hydrogen atoms, adjusting charge states, and generating Gasteiger-Marsili type charges for accurate ligand representation. Finally, the prepared protein and ligand structure files were imported into Autodock Vina for docking simulations.

Experimental data are presented as means ± standard deviations and analyzed using one-way analysis of variance (ANOVA) in IBM SPSS Statistics 26.0. A p-value of < 0.05 was considered statistically significant.

The ingredients of DF were identified using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS). Figures 1A, B illustrate the total ion current chromatograms, while Table 1 lists the identified components. A total of 24 ingredients were tentatively characterized, with their structural formulas presented in Figure 1C.

To assess the analgesic effect of DF, MWT and TWL were measured before and at 3, 7, 11, and 15 days post-CCI surgery (Figures 2A, B). There were no significant differences in MWT and TWL values across the groups prior to surgery (P > 0.05). From the third day after operation, y the third postoperative day, MWT and TWL values in the CCI group significantly declined and remained low compared to the sham group (P < 0.01). Starting from day 7 post-drug administration, both the DF-M and pregabalin groups exhibited a significant increase in MWT and TWL compared to the CCI group (P < 0.05). The DF-L and DF-H groups also demonstrated varying improvements in these values during the treatment period. These findings indicate that DF has a notable analgesic effect in CCI rats.

Network pharmacology was utilized to predict the targets of DF against NeP. The 24 compounds of DF identified by UHPLC-HRMS served as input for the analysis. This approach yielded 843 targets linked to the 24 DF ingredients and 1,321 targets associated with NeP (Figure 3A). Among them, 229 targets were identified as common targets between DF and NeP (Figure 3A). A drug-disease-ingredients-targets network was constructed, as shown in Figure 3B. To explore the interactions among DF's targets in relation to NeP, a protein-protein interaction (PPI) network was created using STRING. This network included 228 nodes and 3,047 edges, with an average degree of 26.7 (Figure 3C). Each node represented a target, with node size reflecting degree value and connection strength. Topological analysis of the PPI network was performed to identify core targets, revealing 51 targets with values exceeding the 2-fold median (Figure 3C). Further analysis in STRING, using the 2-fold median as the criterion, identified the top 14 targets, which included TNF, MTOR, MAPK3, SRC, ALB, CASP3, AKT1, APP, MAPK1, GRIN2B, PRKCA, NOS3, HSP90A1, and IL6 (Figure 3C). These 14 targets were considered the core targets of DF in the treatment of NeP.

GO and KEGG enrichment analyses were conducted using the Metascape database for the 51 targets of DF against NeP. GO enrichment indicated that these targets are involved in processes such as modulation of chemical synaptic transmission, neuron death and positive regulation of synaptic transmission in biological process (BP); asymmetric synapse, neuron spine and synaptic membrane in cellular component (CC); and neurotransmitter receptor activity, phosphoprotein binding and protein serine/threonine/tyrosine kinase activity in molecular function (MF; Figures 4A–C). KEGG analysis revealed that the 51 targets were primarily associated with pathways such as the PI3K-AKT signaling pathway, TNF signaling pathway, calcium signaling pathway, glutamatergic synapse, inflammatory mediator regulation of TRP channels and pathways of neurodegeneration-multiple diseases (Figure 4D), all of which were closely related to NeP. Notably, the PI3K-AKT and TNF signaling pathways showed the most significant enrichment (Figure 4D), suggesting their potential central roles in DF's mechanisms of action.

To investigate the anti-inflammatory effects of DF, levels of IL-1β, IL-6, and TNF-α in the spinal cord were assessed using ELISA. The medium-dose DF granules were selected due to their significant impact on hyperalgesia following CCI surgery. Results indicated that DF significantly reduced the elevated levels of IL-1β, IL-6, and TNF-α in the spinal cord caused by CCI surgery (P < 0.01), highlighting DF's inhibitory effects on neuroinflammation in NeP (Figures 5A–C).

Based on KEGG enrichment analysis and inflammatory cytokine measurements, it was clear that the TNF-α and PI3K-AKT signaling pathways played crucial roles in DF's mechanism for treating NeP. To further examine this, the expression levels of key molecules involved in these pathway were evaluated in the spinal cord tissue. Results showed elevated levels of TNF-α, TNFR1, and phosphorylated PI3K, AKT, IKKα/β, IKBα, and NF-κB in the model group compared to the sham group (P < 0.01, Figure 6). In contrast, the DF-M group exhibited lower levels of TNF-α, TNFR1, and phosphorylated proteins compared to the model group (P < 0.01, Figure 6). These findings suggested that DF effectively suppressed the TNF-α and PI3K-AKT signaling pathway in CCI rat spinal cords. Additionally, immunofluorescence results indicated that expressions of the astrocyte marker GFAP, the microglia marker IBA, TNF-α, TNFR1, and phosphorylated AKT and NF-κB were significantly elevated in the model group relative to the sham group, while levels in the DF-M group were markedly reduced compared to the model group (Figure 7). Collectively, these results demonstrate that DF mediates its analgesic effects through the inhibition of the TNF-α and PI3K-AKT signaling pathways.

To further investigate the direct interactions between DF ingredients and TNF-α, PI3K, and AKT, molecular docking was performed to predict their binding affinities. The results indicated that aconitine, chrysophanol, rhein, sesamin, and toralactone exhibited strong binding capabilities with both TNF-α and PI3K (Figure 8). Nodakenin, daidzein, and physcion showed significant binding affinity with TNF-α, while daidzein, obtusifolin, and beta-sitosterol demonstrated good binding potential with PI3K (Figure 8). These findings suggest that the diverse ingredients of DF can directly interact with specific targets, indicating that individual DF components may engage multiple targets associated with NeP.