Analysis of the pharmacological mechanism of Roucongrong in treating osteoporosis based on a biological network module

被引:0
|
作者
Lin, De-Min [1 ]
Xie, Xing-Wen [2 ,3 ]
Li, Ding-Peng [2 ,3 ]
Xu, Wei [4 ]
Li, Jing [4 ]
Lu, He-Zhong [5 ]
Huang, Rui [1 ]
机构
[1] Gansu Univ Tradit Chinese Med, Lanzhou 730000, Gansu, Peoples R China
[2] Affiliated Hosp Northwest Minzu Univ, 1 Hezheng West Rd, Lanzhou 730000, Gansu, Peoples R China
[3] Second Peoples Hosp Gansu Prov, Lanzhou 730000, Gansu, Peoples R China
[4] Gansu Prov Hosp Tradit Chinese Med, Lanzhou 730000, Gansu, Peoples R China
[5] Huaying Second Peoples Hosp, Guangan 835000, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Roncongrong; osteoporosis; network pharmacology; signal pathway; target; module analysis; OSTEOBLAST; OSTEOCLASTOGENESIS; DIFFERENTIATION; SUPPRESSION; EXPRESSION; CYTOKINES; ACTIVATOR; PROMOTES; GENE; AKT1;
D O I
暂无
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Background: The network pharmacology method can be used to predict the active components, targets, and key signal transduction pathways of Roucongrong. This method has been explored in the treatment of osteoporosis. Methods: The effective ingredients and targets of Roucongrong were obtained by searching the TCMSP database. By combining OMIM, and the GeneCards database, the disease targets of osteoporosis were obtained. We determined the common goals of drugs and diseases and performed PPI network analysis on the STRING platform. The obtained data was constructed using Cytoscape software to construct a network module to perform functional annotation of GO terminology and analysis of the KEGG signal path. Results: A total of 6 active ingredients were screened and identified from Roucongrong, and 223 potential targets of the active ingredients were identified from traditional Chinese medicine. In addition, we found 1086 osteoporosis-related targets in two complete databases, and determined the intersection of disease targets and potential targets of the active ingredients; a total of 59 common targets were identified. The results show that the mechanism of Roucongrong in the treatment of osteoporosis is related to aging, response to drug, angiogenesis, positive regulation of gene expression, extracellular space, extracellular region, cytokine activity, and enzyme binding, mainly through Rheumatoid arthritis, Chagas disease (American trypanosomiasis) and Pathways in cancer to achieve the therapeutic effect. Conclusions: The mechanism of Roucongrong in the treatment of osteoporosis is directly or indirectly related to multiple signaling pathways, mainly involving aging and cytokine activity, as well as response to drug, angiogenesis, positive regulation of gene expression, extracellular space, extracellular region, and enzyme binding, etc. Systematic comprehensive intervention is used to achieve the effect of treating osteoporosis. It provides a theoretical reference for further research on the material basis and mechanism of action of Roucongrong on anti-osteoporosis.
引用
收藏
页码:2359 / 2368
页数:10
相关论文
共 50 条
  • [21] Artificial intelligence and network pharmacology based investigation of pharmacological mechanism and substance basis of Xiaokewan in treating diabetes
    Zhu, Chunyan
    Cai, Tingting
    Jin, Ying
    Chen, Jiayun
    Liu, Guoqiang
    Xu, Niusheng
    Shen, Rong
    Chen, Yuhong
    Han, Luying
    Wang, Suping
    Wu, Caisheng
    Zhu, Mingshe
    PHARMACOLOGICAL RESEARCH, 2020, 159
  • [22] A network pharmacology approach to reveal the pharmacological targets and biological mechanism of compound kushen injection for treating pancreatic cancer based on WGCNA and in vitro experiment validation
    Chao Wu
    Zhi-Hong Huang
    Zi-Qi Meng
    Xiao-Tian Fan
    Shan Lu
    Ying-Ying Tan
    Lei-Ming You
    Jia-Qi Huang
    Antony Stalin
    Pei-Zhi Ye
    Zhi-Shan Wu
    Jing-Yuan Zhang
    Xin-Kui Liu
    Wei Zhou
    Xiao-Meng Zhang
    Jia-Rui Wu
    Chinese Medicine, 16
  • [23] A network pharmacology approach to reveal the pharmacological targets and biological mechanism of compound kushen injection for treating pancreatic cancer based on WGCNA and in vitro experiment validation
    Wu, Chao
    Huang, Zhi-Hong
    Meng, Zi-Qi
    Fan, Xiao-Tian
    Lu, Shan
    Tan, Ying-Ying
    You, Lei-Ming
    Huang, Jia-Qi
    Stalin, Antony
    Ye, Pei-Zhi
    Wu, Zhi-Shan
    Zhang, Jing-Yuan
    Liu, Xin-Kui
    Zhou, Wei
    Zhang, Xiao-Meng
    Wu, Jia-Rui
    CHINESE MEDICINE, 2021, 16 (01)
  • [24] Research on the Mechanism of Kaempferol for Treating Senile Osteoporosis by Network Pharmacology and Molecular Docking
    Tang, Fuyu
    Zhang, Peng
    Zhao, Wenhua
    Zhu, Guangye
    Shen, Gengyang
    Chen, Honglin
    Yu, Xiang
    Zhang, Zhida
    Shang, Qi
    Liang, De
    Jiang, Xiaobing
    Ren, Hui
    EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE, 2022, 2022
  • [25] Exploring the mechanism of cordycepin combined with doxorubicin in treating glioblastoma based on network pharmacology and biological verification
    Chen, Jing
    Zhuang, Yuan-Dong
    Zhang, Qiang
    Liu, Shuang
    Zhuang, Bing-Bo
    Wang, Chun-Hua
    Liang, Ri-Sheng
    PEERJ, 2022, 10
  • [26] Mechanism of action of Salvianolic Acid B by module-based network analysis
    Ren, Zhenzhen
    Wang, Xing
    Wang, Shifeng
    Zhai, Chenxi
    He, Yusu
    Zhang, Yanling
    Qiao, Yanjiang
    BIO-MEDICAL MATERIALS AND ENGINEERING, 2014, 24 (01) : 1333 - 1340
  • [27] Network Pharmacology-Based Strategy and Molecular Docking to Explore the Potential Mechanism of Jintiange Capsule for Treating Osteoporosis
    Yang, Zhao
    Yuan, Zhen-Zhen
    Ma, Xin-Long
    EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE, 2021, 2021
  • [28] Network pharmacology-based strategy to investigate pharmacological mechanism of Liuwei Dihuang Pill against postmenopausal osteoporosis
    Wang, Qingchan
    Huang, Ping
    Xia, Chenjie
    Fu, Danqing
    MEDICINE, 2022, 101 (47) : E31387
  • [29] Exploring the pharmacological mechanism of Xianlingubao against diabetic osteoporosis based on network pharmacology and molecular docking: An observational study
    Yan, Huili
    Li, Zongying
    Zhang, Zhongwen
    MEDICINE, 2024, 103 (31)
  • [30] Decoding the Mechanism of Magnolol in Treating Asthma Based on Network Pharmacology and Transcriptomic Analysis
    Luo, L.
    Wang, J. Y.
    Xiong, A. Y.
    Liu, J. L.
    Liu, Y.
    Liu, S. B.
    Xiong, Y.
    He, X.
    Li, G. P.
    INDIAN JOURNAL OF PHARMACEUTICAL SCIENCES, 2023, 85 (05) : 1373 - 1387