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Systems Pharmacology and Molecular Docking Reveals the Mechanisms of Nux Vomica for the Prevention of Myasthenia Gravis

BACKGROUND: Myasthenia gravis (MG) is a rare autoimmune disease with clinical symptoms of fluctuating muscle weakness. Due to the side effects of current therapies, there is an urgent need for a new medication for MG treatment. Nux vomica is a traditional Chinese medicine used in various diseases. H...

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Detalles Bibliográficos
Autores principales: Qiu, Chao, Chen, Qiang, Hou, Qun, Qi, Guanshu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9251099/
https://www.ncbi.nlm.nih.gov/pubmed/35795289
http://dx.doi.org/10.1155/2022/9043822
Descripción
Sumario:BACKGROUND: Myasthenia gravis (MG) is a rare autoimmune disease with clinical symptoms of fluctuating muscle weakness. Due to the side effects of current therapies, there is an urgent need for a new medication for MG treatment. Nux vomica is a traditional Chinese medicine used in various diseases. However, the mechanism of action of Nux vomica against MG remains unclear. METHODS: Network pharmacology was used to explore the underlying mechanisms of Nux vomica in MG treatment, which was validated using molecular docking and in vivo experiments in mice. RESULTS: Twelve bioactive compounds and 72 targets in Nux vomica were screened. Seventy-nine myasthenia-related targets were obtained from the GENECARD and DisGeNET databases. PPI networks of Nux vomica- and myasthenia-related targets were constructed using Bisogenet, and these two networks were subsequently merged into an intersection to establish a core-target PPI network that consisted of 204 nodes and 4,668 edges. KEGG enrichment analysis indicated that 132 pathways were enriched in 204 core targets. In addition, we obtained 50 docking pairs via molecular docking. In vivo experiments revealed that Nux vomica can improve the symptoms of MG. CONCLUSION: Nux vomica is involved in the pathogenesis of MG through the “multicomponent-target-pathway” mechanism.