• Med. Sci. Monit. · Feb 2020

    A Network Pharmacology Approach to Estimate the Active Ingredients and Potential Targets of Cuscutae semen in the Treatment of Osteoporosis.

    • Weiran Dai, Yue Sun, and Guoqiang Zhong.
    • Department of Cardiology Ward 1, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland).
    • Med. Sci. Monit. 2020 Feb 21; 26: e920485.

    AbstractBACKGROUND Osteoporosis is a metabolic osteopathy characterized by abnormal bone mass and microstructure that has become a public health problem worldwide. Cuscutae semen (CS) is a traditional Chinese medicine (TCM) that has a positive effect on the prevention and treatment of osteoporosis. However, the mechanism of CS is unclear. Therefore, this study aimed to reveal the possible molecular mechanism involved in the effects of CS on osteoporosis based on a network pharmacology approach. MATERIAL AND METHODS The inactive and active ingredients of CS were identified by searching the pharmacology analysis platform of the Chinese medicine system (TCMSP), and the targets of osteoporosis were screened in the relevant databases, such as GeneCards, PubMed, and the Comparative Toxicogenomics Database (CTD). The network of "medicine-ingredients-disease-targets (M-I-D-T)" was established by means of network pharmacology, and the key targets and core pathways were determined by R analysis. Molecular docking methods were used to evaluate the binding activity between the target and the active ingredients of CS. RESULTS Eleven active ingredients were identified in CS, and 175 potential targets of the active ingredients were also identified from the TCMSP. Moreover, we revealed 22 539 targets related to osteoporosis in the 3 well-established databases, and we determined the intersection of the disease targets and the potential targets of the active ingredients; 107 common targets were identified and used in further analysis. Additionally, biological processes and signaling pathways involved in target action, such as fluid shear stress, atherosclerosis, cancer pathways, and the TNF signaling pathway, were determined. Finally, we chose the top 5 common targets, CCND1, EGFR, IL6, MAPK8, and VEGFA, for molecular docking with the 11 active ingredients of CS. CONCLUSIONS This study suggested that CS has multiple ingredients and multiple targets relevant to the treatment of osteoporosis. We determined that the active ingredient, sesamin, may be the most crucial ingredient of CS for the treatment of osteoporosis. Additionally, the network pharmacology method provided a novel research approach to analyze the function of complex ingredients.

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