Abstract
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
structure 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 able 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 N-oxide alkaloids that have been targeted and isolated from the
leaves of Alstonia balansae using a molecular
networking-based dereplication strategy fueled by computer-generated
annotations. This study constitutes the first example of non peptidic
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.