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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/22640

Title: COMPUTATIONAL METHODS AND CHALLENGES IN HYDROGEN/DEUTERIUM EXCHANGE MASS SPECTROMETRY
Other Titles: Computational methods in HDXMS
Authors: Claesen, Jürgen
Burzykowski, Tomasz
Issue Date: 2016
Citation: MASS SPECTROMETRY REVIEWS, 36 (5), p. 649-667
Status: Early View
Abstract: Hydrogen/Deuterium exchange (HDX) has been applied, since the 1930s, as an analytical tool to study the structure and dynamics of (small) biomolecules. The popularity of using HDX to study proteins increased drastically in the last two decades due to the successful combination with mass spectrometry (MS). Together with this growth in popularity, several technological advances have been made, such as improved quenching and fragmentation. As a consequence of these experimental improvements and the increased use of protein-HDXMS, large amounts of complex data are generated, which require appropriate analysis. Computational analysis of HDXMS requires several steps. A typical workflow for proteins consists of identification of (non-)deuterated peptides or fragments of the protein under study (local analysis), or identification of the deuterated protein as a whole (global analysis); determination of the deuteration level; estimation of the protection extent or exchange rates of the labile backbone amide hydrogen atoms; and a statistically sound interpretation of the estimated protection extent or exchange rates. Several algorithms, specifically designed for HDX analysis, have been proposed. They range from procedures that focus on one specific step in the analysis of HDX data to complete HDX workflow analysis tools. In this review, we provide an overview of the computational methods and discuss outstanding challenges.
Notes: Claesen, J (reprint author), Hasselt Univ, I BioStat, Campus Diepenbeek,Agoralaan Gebouw D, B-3590 Diepenbeek, Belgium. jurgen.claesen@uhasselt.be
URI: http://hdl.handle.net/1942/22640
DOI: 10.1002/mas.21519
ISI #: 000407931000007
ISSN: 0277-7037
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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