Stofella, M., Grimaldi, A., Smit, J.H. et al. (3 more authors) (2024) Computational Tools for Hydrogen–Deuterium Exchange Mass Spectrometry Data Analysis. Chemical Reviews, 124 (21). pp. 11639-12390. ISSN 0009-2665
Abstract
Hydrogen-deuterium exchange (HDX) has become a pivotal method for investigating the structural and dynamic properties of proteins. The versatility and sensitivity of mass spectrometry (MS) made the technique the ideal companion for HDX, and today HDX-MS is addressing a growing number of applications in both academic research and industrial settings. The prolific generation of experimental data has spurred the concurrent development of numerous computational tools, designed to automate parts of the workflow while employing different strategies to achieve common objectives. Various computational methods are available to perform automated peptide searches and identification; different statistical tests have been implemented to quantify differences in the exchange pattern between two or more experimental conditions; alternative strategies have been developed to deconvolve and analyze peptides showing multimodal behavior; and different algorithms have been proposed to computationally increase the resolution of HDX-MS data, with the ultimate aim to provide information at the level of the single residue. This review delves into a comprehensive examination of the merits and drawbacks associated with the diverse strategies implemented by software tools for the analysis of HDX-MS data.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Molecular and Cellular Biology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Nov 2024 16:23 |
Last Modified: | 18 Nov 2024 16:23 |
Status: | Published |
Publisher: | American Chemical Society |
Identification Number: | 10.1021/acs.chemrev.4c00438 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:219727 |