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Mass Spectrometry: Alkene Fragmentation00:59

Mass Spectrometry: Alkene Fragmentation

3.6K
Alkenes lose one electron from the unsaturated π bond upon ionization and form stable molecular ions. Further fragmentation of alkenes occurs through three different reaction pathways. The most prominent fragmentation is the cleavage at the allylic position. The resultant allylic carbocation is resonance stabilized. In the mass spectra of terminal alkenes, this fragment appears at a mass-to-charge ratio of 41. In the internal alkenes, where there are two choices of allylic cleavage, the...
3.6K
Mass Spectrometry: Amine Fragmentation00:55

Mass Spectrometry: Amine Fragmentation

2.3K
Amines can be identified using mass spectroscopy based on their characteristic fragmentation patterns. The molecular ions of amines undergo fragmentation via ⍺-cleavage. The ⍺-cleavage of the carbon-carbon bonds in amines generates an alkyl radical and resonance-stabilized nitrogen-containing cation.
In amines, the number of nitrogen atoms affects the mass of the molecular ion, which is described by the nitrogen rule of mass spectrometry. This rule states that a compound containing a single...
2.3K
Mass Spectrometry: Cycloalkane Fragmentation01:05

Mass Spectrometry: Cycloalkane Fragmentation

2.2K
In mass spectrometry, cycloalkanes exhibit distinct fragmentation patterns due to the inherent stability of their molecular ions compared to linear or branched alkanes. The ring structure of cycloalkanes provides additional stability to the molecular ions, often resulting in prominent ion peaks in the mass spectrum.
For example, cyclohexane molecular ions have a mass-to-charge ratio (m/z) of 84, which tends to produce a stronger signal than linear alkanes like hexane. This stability comes from...
2.2K
Mass Spectrometry: Cycloalkene Fragmentation00:54

Mass Spectrometry: Cycloalkene Fragmentation

1.6K
The molecular ions of cycloalkenes undergo fragmentation via a retro-Diels–Alder reaction.
1.6K
Mass Spectrometry: Alkyne Fragmentation00:53

Mass Spectrometry: Alkyne Fragmentation

2.2K
The fragmentation of alkynes preferentially occurs at the carbon–carbon bond between the α and β carbon of the alkyne bond to generate a 3-propynyl cation (or propargyl cation). In terminal alkynes, there is the only type of fragmentation that yields the 3-propynyl cation. The unsubstituted 3-propynyl cation exhibits a peak at a mass-to-charge ratio of 39. In internal alkynes, the 3-propynyl cation is substituted. For example, 2-pentyne fragments into methyl-substituted 3-propynyl cation,...
2.2K
Mass Spectrometry: Alcohol Fragmentation01:03

Mass Spectrometry: Alcohol Fragmentation

4.5K
Alcohols (R-OH) ionize to lose one non-bonded electron from the oxygen atom, forming molecular ions. Due to their tendency to fragment rapidly, the intensity of the molecular ion peak in the mass spectrum is weak or sometimes absent. The fragmentation patterns for alcohols occur in two ways, i.e. ⍺-cleavage and dehydration. During ⍺-cleavage, the bond at the ⍺-position adjacent to the hydroxyl group cleaves to give a resonance-stabilized cation and a radical. However, intramolecular...
4.5K

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Construction of Synthetic Phage Displayed Fab Library with Tailored Diversity
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Mapping Lipid Fragmentation for Tailored Mass Spectral Libraries.

Paul D Hutchins1,2, Jason D Russell2,3, Joshua J Coon4,5,6,7

  • 1Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA.

Journal of the American Society for Mass Spectrometry
|February 14, 2019
PubMed
Summary
This summary is machine-generated.

Library Forge is a new algorithm that automatically generates lipid fragmentation spectra libraries. This accelerates lipid identification in complex samples, even without reference standards.

Keywords:
In silico fragmentation modelingLipid identificationsLipidomicsMass spectrometrySpectral libraries

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Area of Science:

  • Lipidomics
  • Mass Spectrometry
  • Computational Chemistry

Background:

  • Lipid identification from complex extracts often relies on simulated fragmentation spectra libraries.
  • Current methods for generating these libraries require extensive expert annotation and are time-consuming.
  • The growing diversity of lipidomics techniques necessitates faster and more automated library generation.

Purpose of the Study:

  • To introduce Library Forge, an algorithm for automated generation of lipid fragmentation spectra libraries.
  • To reduce the time and user input required for developing lipid spectral libraries.
  • To enhance the accuracy and efficiency of lipid identification in complex samples.

Main Methods:

  • Developed Library Forge, an algorithm that derives lipid fragmentation patterns directly from experimental spectra.
  • Utilized high-resolution mass spectrometry data to learn lipid fragmentation rules.
  • Integrated Library Forge into the LipiDex lipidomics workflow for automated library generation.

Main Results:

  • Library Forge successfully generates lipid fragment mass-to-charge (m/z) and intensity patterns with minimal user input.
  • The algorithm significantly reduces spectral library development time from days to minutes.
  • Automated library generation within LipiDex streamlines the lipidomics workflow.

Conclusions:

  • Library Forge offers a rapid and automated solution for developing lipid spectral libraries.
  • This approach enhances lipid identification confidence and efficiency in complex lipidomics studies.
  • The integration with LipiDex provides a comprehensive workflow for automated lipid analysis.