Extending compound identification for molecular network using the LipidXplorer database independent method: A proof of concept using glycoalkaloids from Solanum pseudoquina A. St.‐Hil.

Phytochemical Analysis
2019.0

Abstract

INTRODUCTION: Molecular networks are now established as the method of choice for tandem mass spectrometry dereplication and similarity-based structure elucidation. Node identification can be used to start the propagation of the structure elucidation of unknown compounds progressively. OBJECTIVE: To demonstrate the capabilities of using the LipidXplorer data results along with molecular networking to identify nodes and aid sequential structure elucidation of unknown compounds. MATERIAL AND METHODS: Molecular fragmentation query language (MFQL) files were written to identify glycoalkaloids based on known structures described for Solanum species. A dataset generated from liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis of Solanum pseudoquina sample were submitted to dereplication on both LipidXplorer software and Global Natural Products Social Molecular Network (GNPS) online system. The resulting attribute table from GNPS calculations was merged with the LipidXplorer results and this merged file was used for network visualisation in Cytoscape. Nodes in the molecular network were labelled using the LipidXplorer identifiers, thus assisting the structure elucidation of unidentified compounds. RESULTS: The combination of the LipidXplorer glycoalkaloids list and GNPS analysis was used in Cytoscape to label nodes in the molecular network. The analysis of the network using these labelled starting points triggered the structure elucidation of closely related nodes leading to the identification of 30 compounds using the LipidXplorer output and four purified and structure elucidated compounds, including a new glycoalkaloids identified as 3-O-(beta-d-xylopyranosyl)-(20R,25S)-22,26-epimino-16-acetyl-cholesta-5,22(N)-diene. CONCLUSION: A significant compound identification completely based on molecular formula and fragmentation queries was achieved. This new and effective approach could help researches to expand the identification rate of compounds in dereplication studies using molecular networks. CI - (c) 2018 John Wiley & Sons, Ltd.

Knowledge Graph

Similar Paper

Extending compound identification for molecular network using the LipidXplorer database independent method: A proof of concept using glycoalkaloids from <scp>Solanum pseudoquina</scp> A. St.‐Hil.
Phytochemical Analysis 2019.0
Diagnostic fragmentation‐assisted mass spectral networking coupled with in silico dereplication for deep annotation of steroidal alkaloids in medicinal Fritillariae Bulbus
Journal of Mass Spectrometry 2020.0
Molecular Networks as Strategy for Dereplication of Steroidal Alkaloids of Herbarium Samples of Solanum jabrense Agra and M. Nee, an Endemic and Unexplored Species
Chemistry &amp; Biodiversity 2025.0
Molecular Network-Guided Alkaloid Profiling of Aerial Parts of Papaver nudicaule L. Using LC-HRMS
Molecules 2020.0
Implementation of an MS/MS Spectral Library for Monoterpene Indole Alkaloids
Methods in Molecular Biology 2022.0
Molecular networking‐based dereplication of strictosidine‐derived monoterpene indole alkaloids from the curare ingredient Strychnos peckii
Rapid Communications in Mass Spectrometry 2020.0
Combining multidimensional chromatography-mass spectrometry and feature-based molecular networking methods for the systematic characterization of compounds in the supercritical fluid extract of Tripterygium wilfordii Hook F
The Analyst 2022.0
Classification of diterpenoid alkaloids from Aconitum kusnezoffii Reichb. by liquid chromatography‐tandem mass spectrometry‐based on molecular networking
Journal of Separation Science 2022.0
Identification and comparison of compounds in commercial Tripterygium wilfordii genus preparations with HPLC-QTOF/MS based on molecular networking and multivariate statistical analysis
Journal of Pharmaceutical and Biomedical Analysis 2022.0
Implementation of a MS/MS database for isoquinoline alkaloids and other annonaceous metabolites
Scientific Data 2022.0