Predictive analysis of quality marker of Acorus tatarinowii based on fingerprint combined with chemical pattern recognition and network pharmacology
LI Peng-hui
SUN Yu
FENG Xiao-long
TAO Xin-ru
GONG Nian-chun
CAI Yuan
PENG Yan-mei
Abstract：Objective:Using fingerprint combined with chemical pattern recognition technology and network pharmacology to analyze and predict potential differential quality markers(Q-markers)in wild Acorus tatarinowii from different origins.Methods:Fingerprint of Acorus tatarinowii was established by HPLC,and common peaks were confirmed and identified.Through principal component analysis(PCA)and orthogonal partial least squares-discriminant analysis(OPLS-DA),the main characteristic chemical components that caused differences in origins were screened."Active ingredient-target-pathway network"was constructed by network pharmacology to predicted Q-markers.Results:Fingerprints of 18 batches Acorus tatarinowii from 4 origins were established.The selection of common peaks showed significant differences in the intrinsic quality of Acorus tatarinowii from different origins.PCA and OPLS-DA showed that Acorus tatarinowii from the same origin were grouped together,and the designated peak 3(β-asarone)was the main characteristic chemical component that caused differences in origins.Six potential Q-markers were identified through network pharmacology.Combined with the Five Element Principles of Q-markers,it was further clarified that β-asarone can be used as a potential Q-marker for Acorus tatarinowii.Conclusion:The research results analyzed and predicted β-asarone can be used as a differential Q-marker for different origins of Acorus tatarinowii,providing ideas and reference for the selection of quality control indicators for Acorus tatarinowii.
Keywords：Acorus tatarinowii Schottfingerprintchemical pattern recognitionnetwork pharmacologydifferential quality markerbeta-asarone
Publication Date：2024-06-15
Online Publishing Date：2026-08-14(First online date of this platform, not the publication date of the document)
Pages：11( 1174-1184 )