Using dissociation energies to predict observability of b- and y-peaks in mass spectra of short peptides. II. Results for hexapeptides with non-polar side chains.

RAPID COMMUNICATIONS IN MASS SPECTROMETRY(2013)

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摘要
RATIONALE:The hypothesis that dissociation energies can serve as a predictor of observability of b- and y-peaks is tested for seven hexapeptides. If the hypothesis holds true for large classes of peptides, one would be able to improve the scoring accuracy of peptide identification tools by excluding theoretical peaks that cannot be observed in practical product ion spectra due to various physical, chemical or thermodynamic considerations. METHODS:Product ion m/z spectra of hexapeptides AAAAAA, AAAFAA, AAAVAA, AAFAAA, AAVAAA, AAFFAA and AAVVAA have been acquired on a Finnigan LTQ XL mass spectrometer in the collision-induced dissociation (CID) activation mode on a grid of activation times 0.05 to 100 ms and normalized collision energy 10 to 35%. Dissociation energies were calculated for all fragmentation channels leading to b- and y-fragments at the TPSS/6-31G(d,p) level of the density functional theory. RESULTS:It was demonstrated that the m/z peaks observed in the product ion spectra correspond to the fragmentation channels with dissociation energies below a certain threshold value. However, there is no direct correlation between the most intense m/z peaks and the lowest dissociation energies. Using the dissociation energies, it was predicted that out of 63 theoretically possible peaks in the b- and y-series of the seven hexapeptides, 19 should not be observable in practical spectra. In the experiments, 24 peaks were not observed, including all 19 predicted. CONCLUSIONS:Dissociation energies alone are not sufficient for predicting ion intensity relationships in product ion m/z spectra. Nevertheless, the present data suggest that dissociation energies appear to be good predictors of observability of b- and y-peaks and potentially very useful for filtering theoretical peaks of each candidate peptide in peptide identification tools. Published 2012. This article is a US Government work and is in the public domain in the USA.
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