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Accommodating protein dynamics in the modeling of chemical crosslinks

Degiacomi, Matteo T.; Schmidt, Carla; Baldwin, Andrew J.; Benesch, Justin L.P.

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Authors

Carla Schmidt

Andrew J. Baldwin

Justin L.P. Benesch



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.

Citation

Degiacomi, M. T., Schmidt, C., Baldwin, A. J., & Benesch, J. L. (2017). Accommodating protein dynamics in the modeling of chemical crosslinks. Structure, 25(11), 1751-1757.e5. https://doi.org/10.1016/j.str.2017.08.015

Journal Article Type Article
Acceptance Date Aug 28, 2017
Online Publication Date Sep 28, 2017
Publication Date Nov 7, 2017
Deposit Date Aug 17, 2017
Publicly Available Date Sep 28, 2018
Journal Structure
Print ISSN 0969-2126
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 25
Issue 11
Pages 1751-1757.e5
DOI https://doi.org/10.1016/j.str.2017.08.015

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