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Insights into the Molecular Mechanisms of Liuwei Dihuang Decoction via Network Pharmacology.
Chen, Jianhui; Teng, Dan; Wu, Zengrui; Li, Weihua; Feng, Yuqian; Tang, Yun; Liu, Guixia.
Afiliação
  • Chen J; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Teng D; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Wu Z; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Li W; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Feng Y; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Tang Y; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Liu G; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
Chem Res Toxicol ; 34(1): 91-102, 2021 01 18.
Article em En | MEDLINE | ID: mdl-33332098
ABSTRACT
The traditional Chinese medicines (TCMs) have been used to treat diseases over a long history, but it is still a great challenge to uncover the underlying mechanisms for their therapeutic effects due to the complexity of their ingredients. Based on a novel network pharmacology-based approach, we explored in this study the potential therapeutic targets of Liuwei Dihuang (LWDH) decoction in its neuroendocrine immunomodulation (NIM) function. We not only collected the known targets of the compounds in LWDH but also predicted the targets for these compounds using the balanced substructure-drug-target network-based inference (bSDTNBI), which is a target prediction method based on network inferring developed by our laboratory. A "target-(pathway)-target" (TPT) network, in which targets of LWDH were connected by relevant pathways, was constructed and divided into several separate modules with strong internal connections. Then the target module that contributes the most to NIM function was determined through a contribution scoring algorithm. Finally, the targets with the highest contribution score to NIM-related diseases in this target module were recommended as potential therapeutic targets of LWDH.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medicamentos de Ervas Chinesas Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Chem Res Toxicol Assunto da revista: TOXICOLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medicamentos de Ervas Chinesas Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Chem Res Toxicol Assunto da revista: TOXICOLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China