Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/36237
Title: Deuteros 2.0: peptide-level significance testing of data from hydrogen deuterium exchange mass spectrometry
Authors: Lau, AM
CLAESEN, Jurgen 
Hansen, K
Politis, A
Editors: Elofsson, Arne
Issue Date: 2021
Publisher: OXFORD UNIV PRESS
Source: Bioinformatics (Oxford. Print), 37 (2) , p. 270 -272
Abstract: A Summary: Hydrogen deuterium exchange mass spectrometry (HDX-MS) is becoming increasing routine for monitoring changes in the structural dynamics of proteins. Differential HDX-MS allows comparison of protein states, such as in the absence or presence of a ligand. This can be used to attribute changes in conformation to binding events, allowing the mapping of entire conformational networks. As such, the number of necessary cross-state comparisons quickly increases as additional states are introduced to the system of study. There are currently very few software packages available that offer quick and informative comparison of HDX-MS datasets and even fewer which offer statistical analysis and advanced visualization. Following the feedback from our original software Deuteros, we present Deuteros 2.0 which has been redesigned from the ground up to fulfill a greater role in the HDX-MS analysis pipeline. Deuteros 2.0 features a repertoire of facilities for back exchange correction, data summarization, peptide-level statistical analysis and advanced data plotting features.
Document URI: http://hdl.handle.net/1942/36237
ISSN: 1367-4803
e-ISSN: 1367-4811
DOI: 10.1093/bioinformatics/btaa677
ISI #: 000649439900020
Rights: The Author(s) 2021. Published by Oxford University Press. 270 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Category: A1
Type: Journal Contribution
Validations: ecoom 2022
Appears in Collections:Research publications

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