The Toll-like Receptor-2/4 Antagonist, Sparstolonin B, and Inflammatory Diseases: A Literature Mining and Network Analysis

Background Sparstolonin B (SsnB) is characterized as a new toll-like receptor (TLR)-2/4 antagonist. However, the effects of SsnB on different inflammatory diseases have not been systemically reviewed. Methods We investigated the effects of SsnB on inflammatory diseases with data mining and network analysis of literature, including frequency description, cluster analysis, association rule mining, functional enrichment, and protein–protein interaction (PPI) mining. Results A total of 27 experimental reports were included. The ARRIVE 2.0 guidelines were used to evaluate the quality of animal studies. Frequency analysis revealed 13 different diseases (cardio-cerebrovascular system diseases account for 23.53%), 12 pharmacological effects (anti-inflammatory effect accounts for 53.85%), and 67 therapeutic targets. The overview of investigation sequence of SsnB studies was depicted by Sankey diagram. Cluster analysis classified the therapeutic targets for SsnB into four main categories: (1) NF-κB; (2) IL-1β, IL-6, and TNF-α; (3) TLR2, TLR4, and MyD88; (4) the other targets. Moreover, the Apriori association discovered two main association pairs: (1) TNF-α, IL-1β, and IL-6 and (2) TLR2, TLR4, and MyD88 (support range 33.33-50%, confidence range 83.33-88.89%). Functional enrichment of the therapeutic targets for SsnB showed that the top enriched items in the biological process were mainly the response to lipopolysaccharide (LPS)/bacterial origin and regulation of cytokine production. Finally, the PPI network and hub gene selection by maximal clique centrality (MCC) algorithm indicated the top ranked proteins were TNF-α, IL-1β, IL-6, AKT1, PPAR-γ, TLR4, CCL2, and TLR2. Conclusion These results emphasized the importance of TLR2/TLR4-MyD88-NF-κB-IL-1β/IL-6/TNF-α pathways as therapeutic targets of SsnB in inflammatory diseases.