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通过多元数据分析和多信息分子网络优先发现来自 物种的脂质过氧化抑制剂。

Discovery of Lipid Peroxidation Inhibitors from Species Prioritized through Multivariate Data Analysis and Multi-Informative Molecular Networking.

机构信息

Department of Pharmaceutical Chemistry and Pharmacognosy, Faculty of Pharmaceutical Sciences and Center of Excellence for Innovation in Chemistry, Naresuan University, Phitsanulok 65000, Thailand.

School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, CMU Rue Michel Servet 1, 1211 Geneva 4, Switzerland.

出版信息

Molecules. 2019 Aug 17;24(16):2989. doi: 10.3390/molecules24162989.

DOI:10.3390/molecules24162989
PMID:31426532
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6719142/
Abstract

A major goal in the discovery of bioactive natural products is to rapidly identify active compound(s) and dereplicate known molecules from complex biological extracts. The conventional bioassay-guided fractionation process can be time consuming and often requires multi-step procedures. Herein, we apply a metabolomic strategy merging multivariate data analysis and multi-informative molecular maps to rapidly prioritize bioactive molecules directly from crude plant extracts. The strategy was applied to 59 extracts of three species (, and ), which were profiled by UHPLC-HRMS and screened for anti-lipid peroxidation activity. Using this approach, six lipid peroxidation inhibitors ‒ of three spp. were discovered, three of them being new compounds: monnieraside IV (), monnieraside V () and monnieraside VI (). The results demonstrate that this combined approach could efficiently guide the discovery of new bioactive natural products. Furthermore, the approach allowed to evidence that main semi-quantitative changes in composition linked to the anti-lipid peroxidation activity were also correlated to seasonal effects notably for .

摘要

天然生物活性产物的发现主要目标是快速鉴定活性化合物,并从复杂的生物提取物中去除已知的分子。传统的基于生物测定的分离过程可能很耗时,并且通常需要多步程序。在此,我们应用代谢组学策略,将多元数据分析和多信息分子图谱相结合,直接从粗提植物提取物中快速确定生物活性分子。该策略应用于三种(、和)的 59 种提取物,通过 UHPLC-HRMS 进行分析,并筛选出抗脂质过氧化活性。通过这种方法,发现了六种脂质过氧化抑制剂——三种 属的化合物,其中三种是新化合物:莫尼沙德 IV()、莫尼沙德 V()和莫尼沙德 VI()。结果表明,这种组合方法可以有效地指导新的生物活性天然产物的发现。此外,该方法还证明了与抗脂质过氧化活性相关的组成的主要半定量变化也与季节性效应有关,特别是对 属。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/d8a50ea038a3/molecules-24-02989-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/64765ff7f3f1/molecules-24-02989-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/eb7987b7e604/molecules-24-02989-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/2c791a96ddb8/molecules-24-02989-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/56c90e19e42a/molecules-24-02989-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/6aa844b8e447/molecules-24-02989-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/d8a50ea038a3/molecules-24-02989-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/64765ff7f3f1/molecules-24-02989-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/eb7987b7e604/molecules-24-02989-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/2c791a96ddb8/molecules-24-02989-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/56c90e19e42a/molecules-24-02989-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/6aa844b8e447/molecules-24-02989-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a62/6719142/d8a50ea038a3/molecules-24-02989-g006.jpg

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