BackgroundRheumatoid Arthritis (RA) is an acute autoimmune disease leading to critical joint damage and bone destruction, weakening extra-articular organs over time. The pathogenesis of RA is complex and still undiscovered. This study aims to identify immune response, microRNA-hub genes network (miRNA), and drug candidates against RA via bioinformatics analysis.MethodologyThree Gene Expression Omnibus (GEO) datasets were obtained from the NCBI database and classified into upregulated and downregulated differentially expressed genes (DEGs) using GEO2R tool. Gene enrichment analysis, protein-protein interaction network analysis, top 10 hub genes identification, miRNA-hub genes network analysis, and immune response identification were performed using various bioinformatic tools. Moreover,Celastrus paniculatusphytochemical compounds were retrieved and subjected to autodocking with upregulated and downregulated hub genes that are closely associated with RA. The drug-likeness and PreADMET analysis were performed.ResultsGSE30662, GSE766, GSE72100 datasets revealed 243 upregulated DEGs and 285 downregulated DEGs which exhibited RPS27A, UBB, UBC, UBA52, PSMD4, PSMD1, PSMD7, PSMB7, PSMD8, PSMA7 as top 10 upregulated hub genes and ACTB, TP53, AKT1, GAPDH, CTNNB1, EGFR, TNF, IL6, MYC, ANXA5 as top 10 downregulated hub genes. The miRNA network disclosed hsa-mir-23b-3p, as highly associated with upregulated hub genes whereas hsa-mir-34a-5p and hsa-mir-155-5p with downregulated hub genes. Additionally, immune responses of specific hub genes of RA were revealed while the docking analysis showed oleic acid and zeylasterone as novel drug candidates against RA.ConclusionThus, hsa-mir-23b-3p, hsa-mir-34a-5p, and hsa-mir-155-5p can serve as therapeutic targets of RA while oleic acid and zeylasterone become potential drug candidates against RA.