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Related Concept Videos

¹H NMR of Labile Protons: Deuterium (²H) Substitution00:48

¹H NMR of Labile Protons: Deuterium (²H) Substitution

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This lesson illustrates the role of deuterium substitution in simplifying the NMR spectrum of compounds comprising labile protons. One method employed is the use of deuterium. Amongst the three isotopes of hydrogen, deuterium (2H) has a nucleus composed of one proton and one neutron. When the D2O solvent is added to a pure dry ethanol solution, its labile proton is substituted with deuterium.
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¹H NMR of Labile Protons: Temporal Resolution01:10

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Protons bonded to heteroatoms such as nitrogen and oxygen exhibit a range of chemical shift values. This is due to the varying degree of hydrogen bonding between the proton and the heteroatom in other molecules. The extent of hydrogen bonding affects the electron density around the proton, thereby giving different chemical shift values for the protons in the proton NMR spectrum.
The –OH proton in alcohols typically appears in the range of δ 2 to 5 ppm but can vary depending on the specific...
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Chemical Shift: Internal References and Solvent Effects01:17

Chemical Shift: Internal References and Solvent Effects

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In an NMR sample, precise measurement of the absolute absorption frequencies of nuclei is difficult. A standard internal reference compound is added, and the frequency difference between the reference signal and sample signals is measured.
The internal reference compound generally used in NMR spectroscopy is tetramethylsilane (TMS). TMS is preferred because it is chemically inert, soluble in NMR solvents, and easily removable. Also, the highly shielded methyl protons in TMS yield an intense...
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A Computational Model for Determining Labeling Duration in Protein Turnover Studies Using a Single Deuterated Water Labeled Sample.

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Related Experiment Video

Updated: Sep 16, 2025

Analyzing Protein Dynamics Using Hydrogen Exchange Mass Spectrometry
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Turnover Rates and Numbers of Exchangeable Hydrogens in Deuterated Water Labeled Samples.

Henock M Deberneh1, Ali Bagherinia1, Rovshan G Sadygov1

  • 1Department of Biochemistry and Molecular Biology, The University of Texas Medical Branch, 301 University of Blvd, Galveston, TX 77555, USA.

International Journal of Molecular Sciences
|July 12, 2025
PubMed
Summary
This summary is machine-generated.

Metabolic labeling quantifies protein turnover rates in vivo. A new computational method corrects for hydrogen count variations, improving accuracy for biological insights.

Keywords:
deuterated water labelingprotein turnoverthe number of exchangeable hydrogens

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Area of Science:

  • Proteomics and Systems Biology
  • Biochemistry and Molecular Biology

Background:

  • Metabolic labeling with deuterated water and mass spectrometry quantifies protein turnover rates in vivo.
  • Protein turnover rates are dynamic, changing with growth, environment, and diet, impacting biological interpretation.
  • Variability in peptide turnover rates, influenced by exchangeable hydrogen count, reduces statistical power and biological interpretability.

Purpose of the Study:

  • To develop a computational approach to eliminate the dependence of protein turnover rates on the number of exchangeable hydrogens.
  • To enhance the accuracy of protein turnover rate estimation.
  • To improve the biological interpretability of proteomic data.

Main Methods:

  • Utilizing liquid chromatography-mass spectrometry for high-throughput protein turnover analysis.
  • Applying bioinformatics tools for data analysis and quantification of thousands of proteins.
  • Developing and implementing a novel computational method to adjust for hydrogen exchange variability.

Main Results:

  • The proposed computational approach successfully eliminates the systematic dependence of turnover rates on the number of exchangeable hydrogens.
  • Enhanced accuracy in estimating protein turnover rates was achieved.
  • Reduced variability in turnover rate data, leading to increased statistical power.

Conclusions:

  • The developed computational method significantly improves the accuracy of protein turnover rate determination.
  • This approach enhances the biological interpretability of proteomic studies.
  • The method has the potential to support more accurate assessments of biological dynamics and disease mechanisms.