Uncovering the mechanism of Radix Paeoniae Alba in the treatment of restless legs syndrome based on network pharmacology and molecular docking. Issue 46 (18th November 2022)

• Record Type: Journal Article
• Authors: Liu, Jun; Liu, Suxian; Hao, Liansheng; Liu, Fangfang; Mu, Shengkai; Wang, Tengteng
• Is Part Of: Medicine. Volume 101:Issue 46(2022)
• Page Start: e31791
• Publication Date: 2022-11-18
• Subjects: mechanism -- molecular docking -- network pharmacology -- Radix Paeoniae Alba -- restless legs syndrome; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000031791
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Restless legs syndrome (RLS) is a neurological motor disorder with a high prevalence. The treatment efficacy of RLS is unsatisfactory. Radix Paeoniae Alba (RPA) can effectively treat RLS symptoms such as the discomfort of the legs. RPA has great potential for the development of new medications for RLS. Hence, we explored the mechanism of RPA in the treatment of RLS using network pharmacology and molecular docking. The active components and targets of RPA were obtained from the Traditional Chinese Medicine System Pharmacology database and analysis platform and PharmMapper platform. The RLS-related targets were found in GeneCards, OMIM, DrugBank, and DisGeNET databases. The overlapping targets of RPA and RLS were then collected. The "active components-overlapping targets" network was built, and network topology analysis was performed. Furthermore, Cytoscape 3.9.1 software was used to screen the key components of RPA in the treatment of RLS. Protein-protein interaction was performed using the Search Tool for the Retrieval of Interacting Genes. The gene ontology functions and Kyoto Encyclopedia of Genes and Genomes signaling pathways were analyzed using ClusterProfiler, PathView, and other R packages to reveal the main mechanism of RPA in treating RLS. Component and protein structures were downloaded from the Traditional Chinese Medicine System Pharmacology and Protein Data Bank databases, respectively. The AutoDock 4.2.6 software was used for molecular docking. A total of 12 active components and 109 targets of RPA, as well as 2387 RLS-related targets, were collected. Following that, 47 overlapping targets were obtained. Furthermore, 5 key components and 12 core targets were screened. The results of gene ontology functions were as follows: 2368 biological processes, 264 molecular functions, and 164 cellular components. A total of 207 Kyoto Encyclopedia of Genes and Genomes signaling pathways were obtained, including the lipid and atherosclerosis pathway, the endocrine resistance pathway, the prolactin signaling pathway, and the IL-17 signaling pathway. The components and the core targets completed molecular docking stably. RPA has multi-component, multi-target, and multi-pathway characteristics in treating RLS, which could provide a basis for future research and improve clinical efficacy.