## 2 Results and Discussion
### Network Pharmacology Analysis  
The current study employs network pharmacology analysis to predict the anti-neurodegenerative efficacy of spilanthol. Network pharmacology is a multidisciplinary approach that merges the fields of pharmacology and systems biology, aiming to investigate the complex interactions between bioactive compounds and multiple targets implicated in complex pathophysiologies [16]. The SMILES notation of spilanthol retrieved from the PubChem database was used for structure-based target fishing. The chemical structure of spilanthol is shown in Figure 1A. Plausible targets of the spilanthol were determined using SwissTargetPrediction, SEA SearchServer, and Super-PRED 3.0. As shown in Figure 1B, spilanthol accounted for 236 potential targets. Moreover, 2094 targets linked with NDDs were obtained from three databases: GeneCard, DisGeNET, and OMIM. The common targets of spilanthol and NDDs are identified from the intersection of a Venn diagram (Figure 1B). The STRING database was employed for the assessment of protein-protein interactions (PPI), revealing intricate relationships among the involved target proteins. Moreover, there were 690 edges and 90 nodes in the network (Figure 1C). To determine the top 10 interacting proteins, the PPI network was also investigated further for Maximal Clique Centrality (MCC) using the CytoHubba. TLR4, NF-kB1, PTGS2, MMP9, PPARG, MAPK3, HIF1A, GSK3B, STAT1, and MTOR are among the top 10 interacting proteins (Figure 1D). The anti-neurodegenerative effectiveness of spilanthol could potentially be achieved by the modulation of these targets. To gain insight into the pathways mediated by spilanthol in neurodegenerative disorders, GO and KEGG pathway enrichment studies were subsequently executed. A sum of 1732 biological processes, 124 cellular components, and 182 molecular functions were enriched in the GO enrichment analysis. Moreover, 159 pathways were significantly enriched in the KEGG enrichment analysis. Figure 2 summarizes the most significantly enriched KEGG pathways and GO terms. Chronic neuroinflammationflammation and microglial activation are pathological hallmarks in the majority of NDDs. A TLR4 signaling pathway is a predominant pathway involved in microglial activation and neuroinflammationflammation. As illustrated in Figure 3, spilanthol shows interactions with multiple targets in the TLR4 signaling pathway. Microglia, which play a crucial role in immune responses within the central nervous system (CNS), contain toll-like receptor 4 (TLR-4) as a major pattern-recognition receptor. Activation of TLR4 promotes the polarization of microglia toward the M1 phenotype which is associated with the pro-inflammatory response. M1 phenotype releases pro-inflammatory cytokines and chemokines including IL-1, IL-6, IL-12, TNF-\(\alpha\), and NO. The activation of TLR4 triggers microglial downstream signaling via TLR adapters, namely MyD88 and TRIF. Among these, the MyD88-dependent pathway is crucial for the polarization of microglia to M1 phenotype [31]. MyD88 functions as a bridge to employ and activate downstream signaling molecules. MyD88 induces autophosphorylation of interleukin-1 receptor-associated kinases (IRAK4). The phosphorylated IRAK4 then induces tumor necrosis factor receptor-associated factor 6 (TRAF6) to encounter self-ubiquitin and conjugate ubiquitin chains onto TAK1. Activated TAK1 is responsible for the activation of the IKK complex via phosphorylation. Upon activation, the IKK complex phosphorylates the NF-\(\kappa\)B inhibitor IxB\(\alpha\), leading to NF-\(\kappa\)B activation [32; 33]. The translocation of NF-\(\kappa\)B induces the transcription of proinflammatoryg genes and ultimately induces the release of proinflammatory cytokines, chemokines, and enzymes involved in inflammation. As indicated in Figure 3, spilanthol interacts with multiple proteins in the TLR-4 pathway, including TLR4, IRAK4, IKK-\(\alpha\), and NF-\(\kappa\)B, in favor of attenuating NDDs.