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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
Mass Spectrometry: Carboxylic Acid, Ester, and Amide Fragmentation01:01

Mass Spectrometry: Carboxylic Acid, Ester, and Amide Fragmentation

The fragmentation patterns observed for compounds such as carboxylic acids, esters, and amides in the mass spectra include ⍺-cleavage and McLafferty rearrangement. Fragmentation by ⍺-cleavage preferentially occurs at the carbon-carbon bond at the ⍺-position next to the carboxylic group to generate a neutral radical and a cation. Long chain compounds with hydrogen at their γ-carbon undergo McLafferty rearrangement to give a radical cation and a neutral alkene.
For example, the fragmentation of...
Mass Spectrometry: Molecular Fragmentation Overview01:20

Mass Spectrometry: Molecular Fragmentation Overview

The ionization of a molecule into a molecular ion inside the mass spectrometer causes instability in the molecule's structure due to the loss of an electron. This eventually leads to the fragmentation or breaking of some bonds in the molecule. The fragmentation occurs predominantly at specific bonds to yield relatively stable fragments.
One type of fragmentation pattern is the cleavage of a single bond in the molecular ion. The cleavage leads to a radical and a cation. The cleavage can occur at...
Mass Spectrometry: Amine Fragmentation00:55

Mass Spectrometry: Amine Fragmentation

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 or...
MALDI-TOF Mass Spectrometry01:19

MALDI-TOF Mass Spectrometry

Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...

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Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics
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A data-mining scheme for identifying peptide structural motifs responsible for different MS/MS fragmentation

Yingying Huang1, George C Tseng, Shinsheng Yuan

  • 1Department of Chemistry, University of Arizona, Tucson, Arizona 85721, USA.

Journal of Proteome Research
|December 7, 2007
PubMed
Summary

This study uses knowledge mining to uncover peptide fragmentation patterns in tandem mass spectrometry (MS/MS) data. Understanding these patterns can improve protein identification algorithms.

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Area of Science:

  • Proteomics
  • Analytical Chemistry
  • Bioinformatics

Background:

  • Tandem mass spectrometry (MS/MS) is crucial for proteomics.
  • MS/MS spectral intensity patterns are not fully understood and underutilized in algorithms.

Purpose of the Study:

  • To discover fragmentation intensity patterns in MS/MS spectra using knowledge mining.
  • To elucidate the chemical factors driving these fragmentation patterns.
  • To improve protein identification algorithms by better understanding peptide dissociation.

Main Methods:

  • Applied unsupervised clustering (penalized K-means) to 28,330 ion trap peptide MS/MS spectra.
  • Utilized a knowledge mining approach without prior chemistry assumptions.
  • Generated a decision tree to correlate fragmentation patterns with peptide sequence and charge state.

Main Results:

  • Identified four distinct fragmentation pattern clusters.
  • Revealed correlations between peptide sequence motifs, charge states, and fragmentation patterns.
  • Demonstrated a data-mining scheme applicable to large datasets.

Conclusions:

  • The study enhances understanding of gas-phase peptide dissociation.
  • Provides a foundation for developing improved protein identification algorithms.
  • Highlights the potential of knowledge mining for spectral data analysis.