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On the Effect of Sphere-Overlap on Super Coarse-Grained Models of Protein Assemblies

Degiacomi, Matteo T.

On the Effect of Sphere-Overlap on Super Coarse-Grained Models of Protein Assemblies Thumbnail


Authors



Abstract

Ion mobility mass spectrometry (IM/MS) can provide structural information on intact protein complexes. Such data, including connectivity and collision cross sections (CCS) of assemblies’ subunits, can in turn be used as a guide to produce representative super coarse-grained models. These models are constituted by ensembles of overlapping spheres, each representing a protein subunit. A model is considered plausible if the CCS and sphere-overlap levels of its subunits fall within predetermined confidence intervals. While the first is determined by experimental error, the latter is based on a statistical analysis on a range of protein dimers. Here, we first propose a new expression to describe the overlap between two spheres. Then we analyze the effect of specific overlap cutoff choices on the precision and accuracy of super coarse-grained models. Finally, we propose a method to determine overlap cutoff levels on a per-case scenario, based on collected CCS data, and show that it can be applied to the characterization of the assembly topology of symmetrical homo-multimers.

Citation

Degiacomi, M. T. (2019). On the Effect of Sphere-Overlap on Super Coarse-Grained Models of Protein Assemblies. Journal of The American Society for Mass Spectrometry, 30(1), 113-117. https://doi.org/10.1007/s13361-018-1974-2

Journal Article Type Article
Acceptance Date Apr 18, 2018
Online Publication Date May 7, 2018
Publication Date Jan 31, 2019
Deposit Date May 8, 2018
Publicly Available Date Mar 28, 2024
Journal Journal of The American Society for Mass Spectrometry
Print ISSN 1044-0305
Electronic ISSN 1879-1123
Publisher American Chemical Society
Peer Reviewed Peer Reviewed
Volume 30
Issue 1
Pages 113-117
DOI https://doi.org/10.1007/s13361-018-1974-2

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
© The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.







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