| Title |
On the Effect of Sphere-Overlap on Super Coarse-Grained Models of Protein Assemblies
|
|---|---|
| Published in |
Journal of the American Society for Mass Spectrometry, May 2018
|
| DOI | 10.1007/s13361-018-1974-2 |
| Pubmed ID | |
| Authors |
Matteo T. Degiacomi |
| 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. Graphical Abstract. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Scientists | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 69% |
| Researcher | 2 | 15% |
| Lecturer | 1 | 8% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 7 | 54% |
| Biochemistry, Genetics and Molecular Biology | 2 | 15% |
| Physics and Astronomy | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Sports and Recreations | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 January 2019.
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#20,167,676
of 25,655,374 outputs
Outputs from Journal of the American Society for Mass Spectrometry
#2,981
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#251,967
of 342,314 outputs
Outputs of similar age from Journal of the American Society for Mass Spectrometry
#56
of 86 outputs
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