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Data mining and systematic pharmacology to reveal the mechanisms of traditional Chinese medicine in Mycoplasma pneumoniae pneumonia treatment

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单位: [1]Capital Med Univ, Beijing Friendship Hosp, Trop Med Res Inst, Beijing 100050, Peoples R China [2]Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Ctr Biomed Res, Wuhan, Peoples R China [3]Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Tradit Chinese Med, Beijing 100730, Peoples R China [4]Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Integrated Tradit Chinese & Western Med, Wuhan, Peoples R China
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关键词: Traditional Chinese medicine Systematic pharmacology Data mining MPP

摘要:
Traditional Chinese Medicine (TCM) is widely used in the treatment of Mycoplasma pneumoniae Pneumonia (MPP) in East Asia. However, our current understanding of the underlying molecular mechanism remains dispersive and promiscuous. In this study, a systematic pharmacological approach combined with literature data mining was applied for drug similarity evaluation, drug half-life evaluation, oral bioavailability prediction, drug target exploration, Gene Ontology (GO) analysis, KEGG pathway enrichment and network construction, thus providing the rationale for its clinical performance. Five mostly studied herbs, including Ephedra Herba, Amygdalus communis Vas, Platycodon grandiforus, Licorice and Scutellariae Radix, were selected from the literature. Total ninety-three active ingredients, which are expected to be the effective components for MPP treatment, were screened out. Interrelationship between active compounds, drug targets and signaling pathways were analyzed to reveal the therapeutic effect of TCM in detail. Of importance, we found that TNF, beta 2AR and PTGS2 play pivotal role in TCM mediated MPP inhibition. And mechanistically, epithelial apoptosis (defensive barrier function), GPCR signaling (symptom amelioration) and immune pathways (innate signaling and adaptive Th17 response) are critically involved. Our work, achieved through systematic pharmacology and data mining, enlarges the knowledge of TCM in MPP therapy, and could provide valuable insights for further drug discovery studies.

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出版当年[2019]版:
大类 | 3 区 医学
小类 | 3 区 医学:研究与实验 3 区 药学
最新[2025]版:
大类 | 2 区 医学
小类 | 2 区 医学:研究与实验 2 区 药学
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出版当年[2018]版:
Q1 PHARMACOLOGY & PHARMACY Q2 MEDICINE, RESEARCH & EXPERIMENTAL
最新[2023]版:
Q1 MEDICINE, RESEARCH & EXPERIMENTAL Q1 PHARMACOLOGY & PHARMACY

影响因子: 最新[2023版] 最新五年平均 出版当年[2018版] 出版当年五年平均 出版前一年[2017版] 出版后一年[2019版]

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第一作者单位: [1]Capital Med Univ, Beijing Friendship Hosp, Trop Med Res Inst, Beijing 100050, Peoples R China
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