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开发质子自旋网络指纹图谱库以支持基于质谱法鉴定植物性补充剂中含药效基团的成分。

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

作者信息

Neiheisel Sara, Uchenik Dmitriy, Marney Luke, Maier Claudia S, Gray Nora E, Soumyanath Amala, Rakotondraibe Harinantenaina L

机构信息

Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States.

College of Pharmacy Shared Instrumentation Facility, The Ohio State University, Columbus, Ohio 43210, United States.

出版信息

J Nat Prod. 2025 Apr 25;88(4):975-984. doi: 10.1021/acs.jnatprod.4c01486. Epub 2025 Mar 28.

Abstract

(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 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 fractions and extracts. The isolation of two new ( and ) and four known (-) CQAs and CQA analogues from and their contribution to the pSNF library are also discussed herein.

摘要

伞形科的刺芹(L. Urban)在东南亚和南部非洲(包括马达加斯加)的传统医学体系中已被使用了几个世纪。先前的研究报告了其制剂在阿尔茨海默病和其他痴呆症模型中具有治疗潜力的证据。咖啡酰奎宁酸(CQAs)已被确定为有助于该植物认知增强和神经保护作用的药理相关代谢物之一。然而,通过常用的液相色谱 - 质谱技术难以区分CQAs的异构体,这使得这些制剂的表征、标准化以及批次间的一致性具有挑战性。单个CQAs具有独特的质子自旋网络指纹(pSNFs),可用于区分复杂提取物中的CQAs区域异构体。这项工作描述了一个以CQAs为重点的pSNF库的开发,该库可用于补充液相色谱 - 质谱方法,以准确鉴定生物活性馏分和提取物中的代谢物并进行表征。本文还讨论了从刺芹中分离出两种新的(和)以及四种已知的( - )CQAs和CQAs类似物及其对pSNF库的贡献。

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