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An in silico MS/MS library for automatic annotation of novel FAHFA lipids.

Journal of cheminformatics | 2015

A new lipid class named 'fatty acid esters of hydroxyl fatty acids' (FAHFA) was recently discovered in mammalian adipose tissue and in blood plasma and some FAHFAs were found to be associated with type 2 diabetes. To facilitate the automatic annotation of FAHFAs in biological specimens, a tandem mass spectra (MS/MS) library is needed. Due to the limitation of the commercial available standard compounds, we proposed building an in silico MS/MS library to extend the coverage of molecules.

Pubmed ID: 26579213 RIS Download

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Associated grants

  • Agency: NCRR NIH HHS, United States
    Id: S10 RR031630
  • Agency: NIDDK NIH HHS, United States
    Id: U24 DK097154

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ChemAxon (tool)

RRID:SCR_004111

Commercial organization that provides cheminformatics software platforms, applications and services to optimize the value of chemistry information in life science and other R&D. This software enables structure visualization and management, property predictions and calculations, virtual synthesis, screening, clustering and drug design.

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METLIN (tool)

RRID:SCR_010500

A public repository of metabolite information as well as tandem mass spectrometry data is provided to facilitate metabolomics experiments. It contains structures and represents a data management system designed to assist in a broad array of metabolite research and metabolite identification. An annotated list of known metabolites and their mass, chemical formula, and structure are available. Each metabolite is linked to outside resources for further reference and inquiry. MS/MS data is also available on many of the metabolites.

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Agilent MassHunter WorkStation - Qualitative Analysis for GC/MS (tool)

RRID:SCR_016657

Software tools for compound-centric data mining and navigation. Used to identify compounds in overlapping and co-eluting peaks with feature extraction and correlation algorithms for chromatographic separation. Used for separating true signals from noise.

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