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Durham Research Online
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Accommodating protein dynamics in the modeling of chemical crosslinks.

Degiacomi, Matteo T. and Schmidt, Carla and Baldwin, Andrew J. and Benesch, Justin L.P. (2017) 'Accommodating protein dynamics in the modeling of chemical crosslinks.', Structure., 25 (11). 1751-1757.e5.

Abstract

Chemical crosslinking can identify the neighborhood relationships between specific amino-acid residues in proteins. The interpretation of crosslinking data is typically performed using single, static atomic structures. However, proteins are dynamic, undergoing motions spanning from local fluctuations of individual residues to global motions of protein assemblies. Here we demonstrate that failure to explicitly accommodate dynamics when interpreting crosslinks structurally can lead to considerable errors. We present a method and associated software, DynamXL, which is able to account directly for flexibility in the context of crosslinking modeling. Our benchmarking on a large dataset of model structures demonstrates significantly improved rationalization of experimental crosslinking data, and enhanced performance in a protein-protein docking protocol. These advances will provide a considerable increase in the structural insights attainable using chemical crosslinking coupled to mass spectrometry.

Item Type:Article
Full text:(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1016/j.str.2017.08.015
Publisher statement:© 2017 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Date accepted:28 August 2017
Date deposited:17 August 2017
Date of first online publication:28 September 2017
Date first made open access:28 September 2018

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