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Related Concept Videos

Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

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An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a low-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.
To...
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High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

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The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For...
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Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

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Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
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Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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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...
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Mass Spectrometry: Aromatic Compound Fragmentation01:23

Mass Spectrometry: Aromatic Compound Fragmentation

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Upon ionization, aromatic compounds generate a molecular ion that is observed as a prominent peak in their mass spectra. For example, the molecular ion peak for benzene appears at a mass-to-charge ratio of 78, while toluene is observed at a mass-to-charge ratio of 92. The molecular ion benzene is highly stable and does not readily undergo further fragmentation due to the significant amount of energy required to disrupt the aromatic stability of the benzene ring. In contrast, the molecular ion...
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Mass Spectrometry: Branched Alkane Fragmentation01:29

Mass Spectrometry: Branched Alkane Fragmentation

1.1K
This lesson delves into the mass spectrometry of branched alkane fragmentation. Branched alkanes possess secondary or tertiary carbon atoms, which generate relatively stable carbocations if the cleavage occurs at the branching point. The high stability of carbocations drives the instant fragmentation of branched alkanes. Accordingly, the branched alkane's molecular ion peak is very weak or invisible in the mass spectra, especially in comparison to a linear alkane.
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Updated: Jul 20, 2025

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Combining Experimental with Computational Infrared and Mass Spectra for High-Throughput Nontargeted Chemical

Erandika Karunaratne1, Dennis W Hill1, Kai Dührkop2

  • 1Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut 06269, United States.

Analytical Chemistry
|August 4, 2023
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Combining mass spectrometry and infrared spectroscopy with computational methods significantly improves the identification of unknown metabolites in nontargeted metabolomics. This approach enhances accuracy and reliability in structure elucidation for environmental and biological samples.

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Area of Science:

  • Analytical Chemistry
  • Computational Chemistry
  • Metabolomics

Background:

  • Nontargeted metabolomics struggles with metabolite structure identification, limiting its application.
  • Current methods rely on mass spectrometry and machine learning, searching vast chemical databases.
  • Orthogonal data is needed to improve identification rates and reliability.

Purpose of the Study:

  • To enhance high-throughput nontargeted chemical structure identification.
  • To evaluate the combination of experimental and computational mass and IR spectral data.
  • To improve the prioritization of candidate structures for verification.

Main Methods:

  • Acquired experimental MS/MS and gas-phase IR spectra for 148 compounds.
  • Generated candidate structures from PubChem for each compound.
  • Utilized CSI:FingerID for initial ranking, followed by DFT-IR prediction and ranking of top candidates.
  • Calculated a composite score based on both ranking methods.

Main Results:

  • Achieved correct identification for 88 out of 148 compounds (59%).
  • Ranked 129 out of 148 compounds (87%) within the top 20 candidates.
  • Reported the highest identification rates to date using PubChem candidate structures.

Conclusions:

  • Combining experimental and computational MS/MS and IR spectral data is effective for structure identification.
  • This integrated approach significantly enhances the prioritization of candidate structures.
  • The method offers a powerful strategy for advancing nontargeted metabolomics.