CHEN Lu, XU Wenjia, ZHANG Xiaomeng, YANG Meng, WANG Xiachang, ZHANG Haifang, CAI Shanying. Analysis of Antioxidant Components in Pongamia pinnata (L.) Pierre and the Mechanism of Action Based on GC-MS Fingerprint and Network Pharmacology[J]. Chinese Journal of Modern Applied Pharmacy. DOI: 10.13748/j.cnki.issn1007-7693.20250880
    Citation: CHEN Lu, XU Wenjia, ZHANG Xiaomeng, YANG Meng, WANG Xiachang, ZHANG Haifang, CAI Shanying. Analysis of Antioxidant Components in Pongamia pinnata (L.) Pierre and the Mechanism of Action Based on GC-MS Fingerprint and Network Pharmacology[J]. Chinese Journal of Modern Applied Pharmacy. DOI: 10.13748/j.cnki.issn1007-7693.20250880

    Analysis of Antioxidant Components in Pongamia pinnata (L.) Pierre and the Mechanism of Action Based on GC-MS Fingerprint and Network Pharmacology

    • OBJECTIVE  To establish GC-MS fingerprint of Pongamia pinnata (L.) Pierre and analysis the antioxidant components and their mechanism of action by chemometrics and network pharmacology.
      METHODS  The volatile oil of Pongamia pinnata (L.) Pierre was analyzed and identified by GC-MS. The fingerprints of 18 batches of samples were established, the common peaks were defined and the similarities were calculated. The differences of samples were compared by principal component analysis and cluster analysis. The “component-target-pathway” network diagram was constructed to analyze the antioxidant components in Pongamia pinnata (L.) Pierre and their mechanism of action by network pharmacology.
      RESULTS  Sixty-one components were respectively identified from the volatile oil of Pongamia pinnata (L.) Pierre and twenty common peaks were identified. The similarities between 18 batches of samples and standardized characteristics fingerprint were between 0.89 and 1.00. The samples could be divided into three categories by cluster analysis. Four main components were extracted by principal component analysis and the cumulative variance contribution rate was 87.71%. The result of principal component analysis and cluster analysis were basically consistent. The quality of Pongamia pinnata (L.) Pierre has a certain correlation with the harvesting location, and the samples collected in Wenchang and Lingao areas were better. The predictive antioxidant components in Pongamia pinnata (L.) Pierre obtained from the “component-target-pathway” network diagram included 6,10-dimethyl-5,9-undecadien-2-one, 3-carene, α-cadinol, β-caryophyllene, β-ionone epoxide, estra-1,3,5(10)-trien-17-ol, β-caryophyllene oxide and alpha-ionone. There were key targets involved such as AR, MAPK8, MAPK9, MAPK10, RELA, AKT1 and MAPK14. The main signaling pathways were chemical carcinogenesis-reactive oxygen species pathway and lipid and atherosclerosis pathway.
      CONCLUSION  In this study the components in the volatile oil of Pongamia pinnata (L.) Pierre are identified by GC-MS, and a rapid and reliable fingerprint analysis method is established. The antioxidant components in Pongamia pinnata (L.) Pierre and its mechanism of action were predictive analyzed by network pharmacology, which provides a scientific basis for the quality control and evaluation of Pongamia pinnata (L.) Pierre and further development of tropical medicinal plant resources.
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