Development of a Proton Spin Network Fingerprint Library to Support Mass Spectrometry-Based Identification of Pharmacophore-Bearing Constituents in the Botanical Supplement Centella asiatica

积雪草 质谱法 药效团 指纹(计算) 鉴定(生物学) 化学 传统医学 色谱法 立体化学 生物 植物 计算机科学 人工智能 医学
作者
Sara Neiheisel,Dmitriy Uchenik,Luke Marney,Claudia S. Maier,Nora E. Gray,Amala Soumyanath,Liva Harinantenaina
出处
期刊:Journal of Natural Products [American Chemical Society]
标识
DOI:10.1021/acs.jnatprod.4c01486
摘要

Centella asiatica (L.) Urban (Apiaceae) has been utilized for centuries in traditional medicine systems in Southeast Asia and Southern Africa, including Madagascar. Previous studies have reported evidence of the therapeutic potential of C. asiatica formulations in models of Alzheimer's Disease and other dementias. Caffeoylquinic acids (CQAs) have been identified to be among the pharmacologically relevant metabolites contributing to the botanical's cognitive enhancement and neuroprotective effects. Isomers of CQAs are, however, difficult to differentiate by commonly used LC-MS techniques, making the characterization, standardization, and batch-to-batch consistency of these formulations challenging. Individual CQAs have unique proton Spin Network Fingerprints (pSNFs) that can be used to distinguish between CQA regioisomers within complex extracts. This work describes the development of a CQA-focused pSNF library that can be used to complement LC-MS methods for the accurate metabolite identification and characterization of bioactive C. asiatica fractions and extracts. The isolation of two new (1 and 2) and four known (3-6) CQAs and CQA analogues from C. asiatica and their contribution to the pSNF library are also discussed herein.

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