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Peptide Identification Using Tandem Mass Spectrometry01:33

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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.
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Mass Spectrometry: Overview01:19

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Mass spectrometry is an analytical technique used to determine the molecular mass and molecular formula of a compound. The basic principle of mass spectrometry is to generate ions from the analyte molecule and measure these ion abundances against their molecular mass.  One common type of ionization, known as electrospray ionization or EI, bombards the analyte molecules in the gas phase with high-energy electron beams. The electron beams displace an electron from the molecule and leave...
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Mass Spectrum: Interpretation01:24

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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.
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Mass Spectrometry: Molecular Fragmentation Overview01:20

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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.
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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.
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High-Resolution Mass Spectrometry (HRMS)01:15

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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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Updated: Oct 14, 2025

Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry
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Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry

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Protein Structure Prediction with Mass Spectrometry Data.

Sarah E Biehn1, Steffen Lindert1

  • 1Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA;

Annual Review of Physical Chemistry
|November 1, 2021
PubMed
Summary
This summary is machine-generated.

Structural mass spectrometry (MS) provides rapid protein structure insights, overcoming experimental limitations. This review highlights computational methods for building accurate protein models from sparse MS data.

Keywords:
computational methodsmass spectrometryprotein structure predictionsparse experimental data

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Area of Science:

  • Biochemistry and Structural Biology
  • Computational Biology and Bioinformatics

Background:

  • Understanding protein structure is vital for biological function and drug discovery.
  • High-resolution protein structure determination methods face experimental challenges (sample quantity, size, efficiency).
  • Structural mass spectrometry (MS) offers a rapid and accessible approach to protein structure elucidation.

Purpose of the Study:

  • To review cutting-edge computational methods for predicting protein structure from sparse MS data.
  • To discuss various MS-based techniques used for structural analysis.
  • To explore future directions in computational protein structure prediction using MS.

Main Methods:

  • Review of computational techniques that integrate sparse MS data into protein models.
  • Analysis of MS-based structural biology methods including chemical cross-linking, hydrogen-deuterium exchange, hydroxyl radical protein footprinting, limited proteolysis, ion mobility, and surface-induced dissociation.

Main Results:

  • Identification and discussion of advanced computational strategies for translating MS data into structural models.
  • Demonstration of the utility of diverse MS techniques in probing protein structure.
  • Highlighting the need for computational methods to bridge the gap between sparse MS data and detailed structural information.

Conclusions:

  • Computational methods are essential for deriving protein structure models from sparse MS data.
  • Structural mass spectrometry, coupled with advanced computation, presents a powerful alternative to traditional methods.
  • Future research should focus on refining these computational approaches for enhanced protein structure prediction.