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Profiling and Authentication of Herbal Products
Author(s) -
Huang Jiayi,
Wong Ka Ho,
Tam James P
Publication year - 2017
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.31.1_supplement.lb121
Subject(s) - traditional medicine , fabaceae , traditional chinese medicine , astragalus , medicine , authentication (law) , biology , alternative medicine , botany , computer science , computer security , pathology
Traditional Chinese medicine (TCM) is gaining popularity as an alternative medicine. A central element of TCM is the use of herbal medicine, which could be benefited by a novel authentication method. Astragalus membranaceus , belongs to the Fabaceae family, is a flowering plant native to China. Its root, commonly known as Huang Qi, is a traditional Chinese medicine used for treating diabetes, promoting Qi and boosting immune system. However, there is another medicinal herb, Hedysarum polybotrys , which also belongs to Fabaceae family, sharing the similar Chinese name (Hong Qi) and morphological characteristics with A. membranaceus , making it difficult to differentiate these two species. Here, we report the use of hyper‐constrained, heat‐stable and enzyme‐resistant peptides as a biologic fingerprint for the identification and authentication of herbal medicines. In particular, we use proteomics fingerprints to differentiate 20 samples from each species profiled by MALDI‐TOF MS analysis. Our results showed that A. membranaceus and H. polybotrys are divided into two clusters in a scores plot, suggesting that these two species had distinct proteomic profiles and can be successfully distinguished from each other. Together, the ability to authenticate provides confidence for customers to use herbal medicine and in TCM treatments. Support or Funding Information Acknowledgements This research was supported by a Competitive Grant from the National Research Foundation in Singapore (NRF‐CRP8‐2011‐05) and an NTU iFood Research Grant (M4081467.080)