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| Exploring the mechanism by which Codonopsis Radix improves hypoxia adaptation based on bioinformatics and network pharmacology |
| Hits 50 Download times 11 Received:August 27, 2024 |
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| DOI
10.11656/j.issn.1672-1519.2025.02.12 |
| Key Words
hypoxia adaptation;Codonopsis Radix;network pharmacology;GEO database;machine learning;molecular docking |
| Author Name | Affiliation | E-mail | | LIU Jinjie | Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
State Key Laboratory of Component-Based Chinese Medicine, Tianjin 301617, China
National Key Laboratory of Chinese Medicine Modernization, Tianjin 301617, China
Key Laboratory of Pharmacology of Traditional Chinese Medical Formulae, Ministry of Education, Tianjin 301617, China | | | HUANG Xianglong | Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
State Key Laboratory of Component-Based Chinese Medicine, Tianjin 301617, China
National Key Laboratory of Chinese Medicine Modernization, Tianjin 301617, China
Key Laboratory of Pharmacology of Traditional Chinese Medical Formulae, Ministry of Education, Tianjin 301617, China | | | SONG Keyan | Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
State Key Laboratory of Component-Based Chinese Medicine, Tianjin 301617, China
National Key Laboratory of Chinese Medicine Modernization, Tianjin 301617, China
Key Laboratory of Pharmacology of Traditional Chinese Medical Formulae, Ministry of Education, Tianjin 301617, China | | | ZHANG Junhua | Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
State Key Laboratory of Component-Based Chinese Medicine, Tianjin 301617, China
National Key Laboratory of Chinese Medicine Modernization, Tianjin 301617, China
Key Laboratory of Pharmacology of Traditional Chinese Medical Formulae, Ministry of Education, Tianjin 301617, China | | | LI Yuhong | Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
State Key Laboratory of Component-Based Chinese Medicine, Tianjin 301617, China
National Key Laboratory of Chinese Medicine Modernization, Tianjin 301617, China
Key Laboratory of Pharmacology of Traditional Chinese Medical Formulae, Ministry of Education, Tianjin 301617, China | | | LI Xiao | Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
State Key Laboratory of Component-Based Chinese Medicine, Tianjin 301617, China
National Key Laboratory of Chinese Medicine Modernization, Tianjin 301617, China
Key Laboratory of Pharmacology of Traditional Chinese Medical Formulae, Ministry of Education, Tianjin 301617, China | lxtcm@foxmail.com | | ZHANG Han | Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
State Key Laboratory of Component-Based Chinese Medicine, Tianjin 301617, China
National Key Laboratory of Chinese Medicine Modernization, Tianjin 301617, China
Key Laboratory of Pharmacology of Traditional Chinese Medical Formulae, Ministry of Education, Tianjin 301617, China | zhanghan0023@126.com |
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| Abstract
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| [Objective] To predict the key targets and the potential active ingredients of Codonopsis Radix on improving hypoxia adaptation using a combination of machine learning and network pharmacology screening methods. [Methods] The active components and potential targets of Codonopsis Radix were collected. Differentially expressed genes under hypoxia were obtained from the GEO database，and genes related to hypoxia adaptation were integrated from the GeneCards database. Common targets of hypoxia adaptation and active components were identified by constructing a protein-protein interaction network. Two machine learning methods were used to screen for core targets，which were validated using external datasets and the iHypoxia database. Molecular docking was used to predict the binding capacity between the main active components of Codonopsis Radix and the core targets. [Results] AA total of 19 active components of Codonopsis Radix were identified，with 338 active component targets，1 642 key targets for hypoxia adaptation，and 66 common targets. The core targets mainly involved CDK1，HIF1A，KDR，IL6，CXCR4，MMP2 and PGF. GO analysis revealed that the main biological processes were related to the response to hypoxia，angiogenesis，endothelial cell proliferation，and differentiation. KEGG pathway analysis identified 20 related signaling pathways，including the HIF-1 and PI3K-Akt pathways. Molecular docking showed that the active components Lobetyolin，Glycitein，Syringin，Codonopsine，and Tangshenoside I had good binding activity with key targets. [Conclusion] Codonopsis Radix may enhance the hypoxia adaptation ability of the human body by regulating the HIF-1 signaling pathway and its interaction with targets such as HIF1A，KDR，and CDK1. |
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