De-novo Identification of Small Molecules from Their GC-EI-MS Spectra

Identification of experimentally acquired mass spectra of unknown compounds presents a~particular challenge because reliable spectral databases do not cover the potential chemical space with sufficient density. Therefore machine learning based \emph{de-novo} methods, which derive molecular structure...

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Bibliographic Details
Published in:arXiv.org 2023-04
Main Authors: Hájek, Adam, Starý, Michal, Jozefov, Filip, Hecht, Helge, Price, Elliott, Křenek, Aleš
Format: Article
Language:English
Subjects:
Machine learning
Mass spectra
Molecular structure
Online Access:Get full text
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Summary:Identification of experimentally acquired mass spectra of unknown compounds presents a~particular challenge because reliable spectral databases do not cover the potential chemical space with sufficient density. Therefore machine learning based \emph{de-novo} methods, which derive molecular structure directly from its mass spectrum gained attention recently. We present a~novel method in this family, addressing a~specific usecase of GC-EI-MS spectra, which is particularly hard due to lack of additional information from the first stage of MS/MS experiments, on which the previously published methods rely. We analyze strengths and drawbacks or our approach and discuss future directions.
ISSN:2331-8422