Application of feature-based molecular networking and MassQL for the MS/MS fragmentation study of depsipeptides.

ABSTRACT: The Feature-based Molecular Networking (FBMN) is a well-known approach for mapping and identifying structures and analogues. However, in the absence of prior knowledge about the molecular class, assessing specific fragments and clusters requires time-consuming manual validation. This study demonstrates that combining FBMN and Mass Spec Query Language (MassQL) is an effective strategy for accelerating the decoding mass fragmentation pathways and identifying molecules with comparable fragmentation patterns, such as beauvericin and its analogues. To accomplish this objective, a spectral similarity network was built from ESI-MS/MS experiments of Fusarium oxysporum at various collision energies (CIDs) and paired with a MassQL search query for conserved beauvericin ions. FBMN analysis rev

SUBMITTER: Selegato DM 

PROVIDER: S-EPMC10427501 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature