Équipe "Pharmacognosie-chimie des substances naturelles" BioCIS, Univ. Paris-Sud, CNRS, Université Paris-Saclay , 5 rue J.-B. Clément , 92290 Châtenay-Malabry , France.
Institut de Chimie des Substances Naturelles, CNRS, ICSN UPR 2301, Université Paris-Saclay , 21 avenue de la Terrasse , 91198 , Gif-sur-Yvette , France.
Anal Chem. 2019 Sep 3;91(17):11247-11252. doi: 10.1021/acs.analchem.9b02216. Epub 2019 Aug 15.
Traditional natural products discovery workflows implying a combination of different targeting strategies, including structure- and/or bioactivity-based approaches, afford no information about new compound structures until late in the discovery pipeline. By integrating a MS/MS prediction module and a collaborative library of (bio)chemical transformations, we have developed a new platform, coined MetWork, that is capable of anticipating the structural identity of metabolites starting from any identified compound. In our quest to discover new monoterpene indole alkaloids, we demonstrate the utility of the MetWork platform by anticipating the structures of five previously undescribed sarpagine-like -oxide alkaloids that have been targeted and isolated from the leaves of using a molecular networking-based dereplication strategy fueled by computer-generated annotations. This study constitutes the first example of nonpeptidic molecular networking-based natural product discovery workflow, in which the targeted structures were initially generated, and therefore anticipated by a computer prior to their isolation.
传统的天然产物发现工作流程,包括不同的靶向策略的组合,包括基于结构和/或基于生物活性的方法,直到发现管道的后期才提供有关新化合物结构的信息。通过整合 MS/MS 预测模块和(生物)化学转化的协作库,我们开发了一个新平台,称为 MetWork,该平台能够从任何已鉴定的化合物开始预测代谢物的结构同一性。在我们发现新的单萜吲哚生物碱的过程中,我们通过使用基于分子网络的去重复策略来靶向和分离叶子中的 previously undescribed sarpagine-like -oxide alkaloids,从而展示了 MetWork 平台的实用性,该策略由计算机生成的注释提供动力。这项研究构成了基于非肽分子网络的天然产物发现工作流程的第一个示例,其中目标结构最初是由计算机生成的,因此在分离之前就已经被计算机预测到了。