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Analysis of overlapped and noisy hydrogen/deuterium exchange mass spectra.


ABSTRACT: Noisy and overlapped mass spectrometry data hinder the sequence coverage that can be obtained from hydrogen deuterium exchange analysis, and places a limit on the complexity of the samples that can be studied by this technique. Advances in instrumentation have addressed these limits, but as the complexity of the biological samples under investigation increases, these problems are re-encountered. Here we describe the use of binomial distribution fitting with asymmetric linear squares regression for calculating the accurate deuterium content for mass envelopes of low signal or that contain significant overlap. The approach is demonstrated with a test data set of HIV Env gp140 wherein inclusion of the new analysis regime resulted in obtaining exchange data for 42 additional peptides, improving the sequence coverage by 11%. At the same time, the precision of deuterium uptake measurements was improved for nearly every peptide examined. The improved processing algorithms also provide an efficient method for deconvolution of bimodal mass envelopes and EX1 kinetic signatures. All these functions and visualization tools have been implemented in the new version of the freely available software, HX-Express v2.

SUBMITTER: Guttman M 

PROVIDER: S-EPMC3855366 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Analysis of overlapped and noisy hydrogen/deuterium exchange mass spectra.

Guttman Miklos M   Weis David D DD   Engen John R JR   Lee Kelly K KK  

Journal of the American Society for Mass Spectrometry 20130910 12


Noisy and overlapped mass spectrometry data hinder the sequence coverage that can be obtained from hydrogen deuterium exchange analysis, and places a limit on the complexity of the samples that can be studied by this technique. Advances in instrumentation have addressed these limits, but as the complexity of the biological samples under investigation increases, these problems are re-encountered. Here we describe the use of binomial distribution fitting with asymmetric linear squares regression f  ...[more]

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