Équipe Chimie des Substances Naturelles, BioCIS, Université Paris-Saclay, CNRS, Châtenay-Malabry, France.
Methods Mol Biol. 2022;2505:87-100. doi: 10.1007/978-1-0716-2349-7_7.
In less than 10 years, molecular networking (MN) strategy has revolutionized the art of Natural Products (NP) isolation to enter a rational workflow greatly increasing the probabilities of isolating new chemical entities. To pinpoint and streamline the isolation of new Monoterpene Indole Alkaloids (MIAs) in producing plants, we rendered publicly available the MIA database (MIADB), comprising MS data for ca. 200 structurally diverse MIA, by uploading it to the Global Natural Products Social Molecular Networking (GNPS) platform. Here, we describe the key experimental aspects underlying data collection, data curation, and their subsequent upload to the GNPS libraries as a database. Practical tips are also provided at the end of this chapter to help optimizing the efficiency of the dereplication of MIA-containing plants against the MIADB-implemented GNPS library.
在不到 10 年的时间里,分子网络(MN)策略彻底改变了天然产物(NP)分离的艺术,进入了一个大大增加分离新化学实体概率的合理工作流程。为了精确定位和简化产生植物中新单萜吲哚生物碱(MIAs)的分离,我们将 MIA 数据库(MIADB)公开发布,该数据库包含约 200 种结构多样的 MIA 的 MS 数据,通过将其上传到全球天然产物社会分子网络(GNPS)平台。在这里,我们描述了数据收集、数据管理以及随后将其上传到 GNPS 库作为数据库的关键实验方面。本章末尾还提供了一些实用技巧,以帮助优化针对 MIADB 实施的 GNPS 库对含 MIA 植物的去重复效率。