Multi -Target Drug Discovery for Rheumatoid Arthritis: A Comprehensive Computational Approach Using Bioactive Compounds

Rheumatoid arthritis (RA) is one of the most common autoimmune inflammatory diseases in the world. Due to this importance, several drugs have been designed and produced against effective targets in the pathogenesis of the disease. Considering various inflammatory pathways involved in RA, targeting each of these pathways alone cannot achieve sufficient improvement of the patients. Therefore, this study aimed to introduce safe natural product drug candidates screened in silico against several important protein targets (multi-targets) in the pathogenesis of RA. Tyrosine kinase ۲ is a member of the Janus Kinase family, and due to its role in the signaling of numerous cytokines, its inhibition is considered an effective treatment option in inflammatory diseases. IL-۶ is one of the most important innate immune cytokines that is secreted from activated macrophages in RA, and its level is directly related to the severity of joint destruction. Therefore, its inhibition plays an important role in improving the pathological symptoms of RA. In addition to the level of IL-۶, the severity of the disease is directly related to the level of ACPA in the serum and synovial fluid of patients. Therefore, inhibiting its production by precluding the differentiation of B lymphocytes into plasma cells can effectively improve the disease. In this study, after Virtual Screening, Molecular Docking, and Molecular Dynamics, our results introduced ۴ compounds including Rutaecarpine, Hecogenin, Angustine, and Vomicine as new drug candidates for the treatment of RA. Rutaecarpine, Hecogenin, and Angustine inhibit all three targets with high affinity and stability, while Vomicine inhibits both TYK۲ and IL-۶ but not CD۲۰. Future experimental studies can verify these findings.

کلیدواژه ها:

rheumatoid arthritis ، MD Simulation ، bioactive compounds ، anti-inflammation ، multi-target drugs