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采用 HRLC-MS 结合 MPP 和 GNPS 数据分析鉴定 SK 抑制提取物的主要成分。

Combination of HRLC-MS with MPP and GNPS data analysis to identify major constituents of SK inhibitory extract.

机构信息

Department of Drug Discovery and Development, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA.

College of Science and Mathematics, Auburn University, Auburn, AL, USA.

出版信息

Nat Prod Res. 2022 Oct;36(19):5064-5068. doi: 10.1080/14786419.2021.1916015. Epub 2021 May 6.

DOI:10.1080/14786419.2021.1916015
PMID:33951985
Abstract

(L.) Willd. (Zingiberaceae), or galangal, has been previously reported as active against (TB) . The present study assessed a novel antitubercular mechanism of of galangal through shikimate kinase (SK) inhibitory assays. Sequential extractions of nonpolar solvents hexane and dichloromethane (DCM) were performed on galangal and screened in SK inhibitory assays to identify potential activity. Samples were then subjected to high resolution (HR) LC-MS chemical fingerprinting and analysis. Additionally, a novel approach was undertaken for galangal using methods such as mass professional profiler (MPP) and global natural products social (GNPS) molecular networking for structure elucidation.[Formula: see text].

摘要

(L.) 姜科山柰属(Zingiberaceae),或山柰,先前被报道具有抗结核(TB)活性。本研究通过测定莽草酸激酶(SK)抑制实验评估了山柰的一种新型抗结核机制。对山柰进行了非极性溶剂正己烷和二氯甲烷(DCM)的连续提取,并在 SK 抑制实验中进行了筛选,以鉴定潜在的活性。然后对样品进行高分辨(HR)LC-MS 化学指纹图谱分析。此外,还采用质量专业剖析器(MPP)和全球天然产物社交网络(GNPS)分子网络等方法对山柰进行了一种新的研究。

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