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- Title
Annotation of natural product compound families using molecular networking topology and structural similarity fingerprinting.
- Authors
Morehouse, Nicholas J.; Clark, Trevor N.; McMann, Emily J.; van Santen, Jeffrey A.; Haeckl, F. P. Jake; Gray, Christopher A.; Linington, Roger G.
- Abstract
Spectral matching of MS2 fragmentation spectra has become a popular method for characterizing natural products libraries but identification remains challenging due to differences in MS2 fragmentation properties between instruments and the low coverage of current spectral reference libraries. To address this bottleneck we present Structural similarity Network Annotation Platform for Mass Spectrometry (SNAP-MS) which matches chemical similarity grouping in the Natural Products Atlas to grouping of mass spectrometry features from molecular networking. This approach assigns compound families to molecular networking subnetworks without the need for experimental or calculated reference spectra. We demonstrate SNAP-MS can accurately annotate subnetworks built from both reference spectra and an in-house microbial extract library, and correctly predict compound families from published molecular networks acquired on a range of MS instrumentation. Compound family annotations for the microbial extract library are validated by co-injection of standards or isolation and spectroscopic analysis. SNAP-MS is freely available at www.npatlas.org/discover/snapms. Comparing experimental mass spectra to reference spectra can enable natural product identification, but these spectral libraries are often incomplete and not universally applicable. Here, the authors present SNAP-MS, a tool that allows assigning compound families without experimental or calculated reference spectra.
- Subjects
NATURAL products; MASS spectrometry; ANNOTATIONS; FAMILIES; TOPOLOGY
- Publication
Nature Communications, 2023, Vol 14, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-022-35734-z