Development of Novel Herbal Compound Formulations Targeting Neuroinflammation: Network Pharmacology, Molecular Docking, and Experimental Verification

Abstract

Neuroinflammation plays an important role in the onset and progression of neurodegenerative diseases. The multicomponent and multitarget approach may provide a practical strategy to address the complex pathological mechanisms of neuroinflammation. This study aimed to develop synergistic herbal compound formulas to attenuate neuroinflammation using integrated network pharmacology, molecular docking, and experimental bioassays. Eight phytochemicals with anti-neuroinflammatory potential were selected in the present study. A compound-gene target-signaling pathway network was constructed to illustrate the mechanisms of action of each phytochemical and the interactions among them at the molecular level. Molecular docking was performed to verify the binding affinity of each phytochemical and its key gene targets. An experimental study was conducted to identify synergistic interactions among the eight phytochemicals, and the associated molecular mechanisms were examined by immunoblotting based on the findings from the network pharmacology analysis. Two paired combinations, andrographolide and 6-shogaol (AN-SG) (IC₅₀ = 2.85 μg/mL), and baicalein-6-shogaol (BA-SG) (IC₅₀ = 3.28 μg/mL), were found to synergistically (combination index <1) inhibit the lipopolysaccharides (LPS)-induced nitric oxide production in microglia N11 cells. Network pharmacology analysis suggested that MAPK14, MAPK8, and NOS3 were the top three relevant gene targets for the three phytochemicals, and molecular docking demonstrated strong binding affinities of the phytochemicals to their coded proteins. Immunoblotting suggested that the AN-SG and BA-SG both showed prominent effects in inhibiting inducible nitric oxide synthase (iNOS) (p < 0.01 and p < 0.05, respectively) and MAPKp-p38 (both p < 0.05) compared with those induced by the LPS stimulation only. The AN-SG combination exhibited greater inhibitions of the protein expressions of iNOS (p < 0.05 vs. individual components), which may partly explain the mechanisms of the synergy observed. This study established a practical approach to developing novel herbal-compound formulations using integrated network pharmacology analysis, molecular docking, and experimental bioassays. The study provides a scientific basis and new insight into the two synergistic combinations against neuroinflammation.

Figure 1

Workflow from network pharmacology analysis, molecular docking to experimental verification.

Figure 2

The compound-gene targets-signaling pathway network of the eight phytochemicals related to neuroinflammation. Orange nodes represent each phytochemical candidate, blue nodes refer to potential phytochemical's targets in neuroinflammation, and the green nodes display the signaling pathway. The size of each node represents its degree in the network. The grey connecting lines reflect that each node is interconnected.

Figure 3

Molecular docking analysis of the eight phytochemical candidates with MAPK14 (a) and NOS3 (b) analysed by CB dock.

Figure 4

The NO inhibitory activities and cell viability of (a) LU, (b) BA, (c) AN, (d) 6-SG, (e) CU, (f) HES, (g) TE, and (h) GLY in LPS-activated N11 microglial cells. Data are shown as mean ± SEM (n > 3).

Figure 5

AN-SG and BA-SG combinations exhibited synergistic inhibitory effects on LPS-induced NO production in N11 cells. (a) AN, 6-SG, and AN-SG dose-dependently inhibited LPS-induced NO in N11 cells (n ≥ 3). (b) The synergistic NO inhibitory effect of AN-SG was determined by the CI-Fa curves. CI values represent the interaction in AN-SG, with CI < 1, CI = 1, and CI > 1 referring to synergy, addition, and antagonism, respectively. Fa on the X-axis is defined as the fraction effect level, and herein it refers to the NO inhibitory effect, respectively. (c) Isobologram analysis of AN-SG in NO inhibition when the default set of Fa values at 0.50, 0.75, and 0.9. (d) BA, 6-SG, and BA-SG dose-dependently inhibited LPS-induced NO in N11 cells (n ≥ 3). (e) The synergistic NO inhibitory effect of BA-SG was determined by the CI-Fa curves. CI values represent the interaction in BA-SG, with CI < 1, CI = 1, and CI > 1 referring to synergy, addition, and antagonism, respectively. Fa on the X-axis is defined as the fraction effect level, and herein it refers to the NO inhibitory effect, respectively. (f) Isobologram analysis of BA-SG in NO inhibition when the default set of Fa values at 0.50, 0.75, and 0.9.

Figure 6

Compound-gene targets-signaling pathway networks for the AN-SG (a) and BA-SG (b). The green nodes represent the signaling pathway, the orange nodes represent the phytochemicals, and the blue nodes represent potential common compound targets in neuroinflammation. The size of each label represents its degree.

Figure 7

Cells were cultured in T75 cell flasks and were pretreated with AN, BA, 6-SG, AN-SG, and BA-SG 1 h prior to LPS (1 μg/mL) for 0.5 h or 24 h protein expression levels of p-p38/p38 (a, c), iNOS (b, d) were analysed by western blot. All results (n = 3) are expressed as the mean ± SEM, ^&&&p < 0.001, ^&&&&p < 0.0001vs. BLANK, ^∗p < 0.05, ^∗∗p < 0.01, ^∗∗∗p < 0.001, vs. LPS, ^#p < 0.05vs. combination, by one-way ANOVA analysis with the Tukey test in GraphPad prism 9.