NATURAL PRODUCT RESEARCH AND DEVELOPMENT ›› 2024, Vol. 36 ›› Issue (10): 1800-1812.doi: 10.16333/j.1001-6880.2024.10.016

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Prediction of Q-Marker in Perilla frutescens(L.) Britt based on UPLC fingerprint and network pharmacology

ZHANG Liang-qi1,2,CHEN Fan1,2,ZHANG Zi-an1,2,LIN Yun1,ZHOU Chun-jiao1,TANG Zhuo-han1,JIANG Xing-ming1 *,XIAO Mei-feng1,2,3*   

  1. 1 College of Pharmacy,Hunan University of Chinese Medicine;2 Hunan Key Laboratory of Druggability and Preparation Modification for Traditional Chinese Medicine(TCM);3Property and Pharmacodaynamic Key Laboratory of TCM,National Administration of TCM,Changsha 410208,China
  • Online:2024-10-28 Published:2024-10-28

Abstract:

This study aims to analyze and predict the potential quality markers of different parts of Perilla frutescens(L.) Britt based on UPLC fingerprint analysis method and network pharmacology.The fingerprints of 15 batches of P. frutescens leaves and 14 batches of P. frutescens stems were established,and the components and contents of P. frutescens leaves and P. frutescens stems from different places of origin and batches were compared,and the common peaks and non-common peaks of different parts of P. frutescens were calibrated.Through network pharmacology to construct the visualization of ′target-protein′ interaction network in P. frutescens,a ′component-target′ network diagram was constructed to predict Q-Marker in P. frutescens.In this study,a total of five components were detected in the fingerprints of different parts of P. frutescens,among which rosmarinic acid,caffeic acid,luteolin-7-O-glucuronide and luteolinl-7-O-diglucuronide were common components of P. frutescens leaves and P. frutescens stems,and apigenin-7-O-glucuronide were unique components of P. frutescens leaves.Fourteen core targets including MAPK1, PIK3CA were screened by network pharmacology. GO and KEGG functional analysis of these targets showed that TNF, COVID-19, lipid and atherosclerosis signaling pathway were involved, and “component-target-pathway”' network was finally constructed.  The top four target proteins and four components were selected for molecular docking verification,The results showed that there was a very good binding performance between the components and the proteins.Based on UPLC fingerprint analysis and network pharmacology,rosmarinic acid,caffeic acid,luteolin-7-O-glucuronide and luteolinl-7-O-diglucuronide were predicted to be potential Q-Marker for different parts of P. frutescens.highlighting the synergistic interactions of ‘multi-component multi-target multi-pathway’ in P. frutescens,which provided a theoretical framework for the quality control of P. frutescens,and also provided a robust foundation for the subsequent material basis and mechanism of P. frutescens.

Key words: Perilla frutescens(L.)Britt, UPLC fingerprint, quality marker, network pharmacology, chemical composition

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