Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/48860
Title: A Statistical Model to Resolve High-Resolution HDX Dynamics through Isotopic Distributions of Overlapping Peptides
Authors: STANIAK, Mateusz 
CLAESEN, Jurgen 
BURZYKOWSKI, Tomasz 
Issue Date: 2026
Status: Early view
Abstract: Hydrogen/Deuterium exchange (HDX) is a versatile technique to study protein structure and protein dynamics. Hydrogen-atoms from the NH-group of peptide bonds can be replaced by deuterium. This exchange can be monitored with mass spectrometry (MS), as the exchange of a single labile H-atom with deuterium is recorded as a mass shift of approximately one dalton. To increase the spatial resolution of MS, the protein under study is enzymatically digested into peptides, resulting in (limited) peptide-level exchange information. Digestion leads to partially or fully overlapping peptides. As a consequence, overlapping peptides can be conceptually divided into smaller parts or segments, some shared between peptides others unique to a single peptide. By describing HDX at the level of these segments instead of at the peptide-level, more precise information about protein structure and dynamics can be obtained. In this paper, we propose a statistical model that connects the observed isotope distributions of overlapping peptides to the unobserved exchange dynamics of peptide segments, potentially leading to single-residue kinetic information. Our model uses a data-driven definition of a segment, and therefore does not attempt to extract single-residue kinetics without sufficient information. The model allows quantifying the uncertainty in the estimated HDX probabilities and exchange rates. The use of the isotopic distribution, instead of deuteration-values or mass shifts, makes it also possible to analyze peptides undergoing EX1 or EX1-EX2 kinetics. We evaluate the properties of the model by simulations and application to two real-life datasets.
Keywords: mass spectrometry;hydrogen-deuterium exchange;overlapping peptides;isotope distribution;statistical model
Document URI: http://hdl.handle.net/1942/48860
ISSN: 0003-2700
e-ISSN: 1520-6882
Category: O
Type: Preprint
Appears in Collections:Research publications

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