Exploring the mechanism of Sendeng‐4 against rheumacid arthritis through integrated serum pharmacochemistry, transcriptomics, and network pharmacology

Abstract Mongolian medicine Sendeng‐4 (SD‐4) has demonstrated satisfactory clinical treatment outcomes for rheumatoid arthritis (RA); nevertheless, its bioactive components and the related mechanisms have not yet been clearly elucidated. To explore the bioactive chemical components of SD‐4 in the treatment of RA and its possible mechanisms, an High Performance Liquid Chromatography–tandem mass spectrometry (HPLC–MS/MS) method was established to simultaneously quantify the main components in SD‐4, and ultraperformance LC‐Q‐Exactive‐MS/MS (UPLC‐Q‐Exactive‐MS/MS) was used to identify the phytochemicals absorbed in the serum. Then, using network pharmacology methods, these components were constructed into a compound–target network of RA to predict possible biological targets of SD‐4 as well as potential signaling pathways. Transcriptomics analysis and molecular docking were used to validate the results of network pharmacology. Subsequently, we established a complete Freund's adjuvant–induced RA rat model and observed the anti‐RA effects of SD‐4 through assessments of foot swelling, ankle diameter, arthritis score, morphology, serum inflammatory factors, and histopathological analysis of synovial tissue. Specifically, reverse transcription‐quantitative polymerase chain reaction, Western blot, and immunohistochemical analysis were used in animal experiments to validate the pathways of serum phytochemistry, network pharmacology, and transcriptomics. Tannic acid, gallic acid, corilagin, crocin I, gardenoside, ferulic acid, quercetin, limonin, rutin, chlorogenic acid, verbascoside, catechin, epicatechin, myricetin, and dihydromyricetin in SD‐4 showed good linearity within their respective concentration ranges ( r ≥ 0.9991); the average recovery rate was 93.77%–109.17% (relative standard deviation < 2%). A total of 37 compounds were identified in serum samples. Based on this, network pharmacology methods collected 739 genes related to these identified compounds in SD‐4 and 3807 genes related to RA. Network pharmacology and transcriptomic analysis demonstrated that the phosphatidylinositol 3‐kinase (PI3K)–protein kinase B (Akt) signaling pathway is the most relevant pathway affected by SD‐4 in RA. In the experiments, SD‐4 treatment reduced ankle swelling and arthritis scores in RA rats, improved symptoms, and reduced the production of inflammatory factors. Compared with the RA model group, SD‐4 treatment significantly reduced the expression of PI3K–Akt pathway–related messenger RNA and proteins. In addition, immunohistochemical analysis confirmed these results. This study combined serum phytochemistry, network pharmacology, and transcriptomics to demonstrate that SD‐4 can alleviate RA by regulating the PI3K–Akt signaling pathway. This research provides a theoretical basis for the clinical application of SD‐4 and offers an effective strategy for the identification of bioactive substances in traditional Chinese medicine formulas and the study of their potential mechanisms.