ArticleJournal of the American Society for Mass Spectrometry2010
Measuring internal energy deposition in collisional activation using hydrated ion nanocalorimetry to obtain peptide dissociation energies and entropies.
Article in Journal of the American Society for Mass Spectrometry, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Relative Strength of Noncovalent Interactions and Covalent Backbone Bonds in Gaseous RNA-Peptide Complexes.Analytical chemistry · 2019Article
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2 authors.
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Abstract
The internal energy deposited in both on- and off-resonance collisional activation in Fourier transform ion cyclotron resonance mass spectrometry is measured with ion nanocalorimetry and is used to obtain information about the dissociation energy and entropy of a protonated peptide. Activation of Na(+)(H(2)O)(30) results in sequential loss of water molecules, and the internal energy of the activated ion can be obtained from the abundances of the product ions. Information about internal energy deposition in on-resonance collisional activation of protonated peptides is inferred from dissociation data obtained under identical conditions for hydrated ions that have similar m/z and degrees-of-freedom. From experimental internal energy deposition curves and Rice-Ramsperger-Kassel-Marcus (RRKM) theory, dissociation data as a function of collision energy for protonated leucine enkephalin, which has a comparable m/z and degrees-of-freedom as Na(+)(H(2)O)(30), are modeled. The threshold dissociation energies and entropies are correlated for data acquired at a single time point, resulting in a relatively wide range of threshold dissociation energies (1.1 to 1.7 eV) that can fit these data. However, this range of values could be significantly reduced by fitting data acquired at different dissociation times. By measuring the internal energy of an activated ion, the number of fitting parameters necessary to obtain information about the dissociation parameters by modeling these data is reduced and could result in improved accuracy for such methods.
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