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The Role of Mass Spectrometry in Structural Studies of Flavin-Based Electron Bifurcating Enzymes

Overview of attention for article published in Frontiers in Microbiology, July 2018
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Title
The Role of Mass Spectrometry in Structural Studies of Flavin-Based Electron Bifurcating Enzymes
Published in
Frontiers in Microbiology, July 2018
DOI 10.3389/fmicb.2018.01397
Pubmed ID
Authors

Monika Tokmina-Lukaszewska, Angela Patterson, Luke Berry, Liam Scott, Narayanaganesh Balasubramanian, Brian Bothner

Abstract

For decades, biologists and biochemists have taken advantage of atomic resolution structural models of proteins from X-ray crystallography, nuclear magnetic resonance spectroscopy, and more recently cryo-electron microscopy. However, not all proteins relent to structural analyses using these approaches, and as the depth of knowledge increases, additional data elucidating a mechanistic understanding of protein function is desired. Flavin-based electron bifurcating enzymes, which are responsible for producing high energy compounds through the simultaneous endergonic and exergonic reduction of two intercellular electron carriers (i.e., NAD+ and ferredoxin) are one class of proteins that have challenged structural biologists and in which there is great interest to understand the mechanism behind electron gating. A limited number of X-ray crystallography projects have been successful; however, it is clear that to understand how these enzymes function, techniques that can reveal detailed in solution information about protein structure, dynamics, and interactions involved in the bifurcating reaction are needed. In this review, we cover a general set of mass spectrometry-based techniques that, combined with protein modeling, are capable of providing information on both protein structure and dynamics. Techniques discussed include surface labeling, covalent cross-linking, native mass spectrometry, and hydrogen/deuterium exchange. We cover how biophysical data can be used to validate computationally generated protein models and develop mechanistic explanations for regulation and performance of enzymes and protein complexes. Our focus will be on flavin-based electron bifurcating enzymes, but the broad applicability of the techniques will be showcased.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 33%
Student > Bachelor 5 17%
Student > Doctoral Student 3 10%
Student > Master 3 10%
Researcher 2 7%
Other 3 10%
Unknown 4 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 53%
Chemistry 5 17%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Agricultural and Biological Sciences 1 3%
Environmental Science 1 3%
Other 0 0%
Unknown 6 20%
Attention Score in Context

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 05 July 2018.
All research outputs
#18,641,800
of 23,094,276 outputs
Outputs from Frontiers in Microbiology
#19,659
of 25,264 outputs
Outputs of similar age
#252,940
of 327,553 outputs
Outputs of similar age from Frontiers in Microbiology
#535
of 721 outputs
Altmetric has tracked 23,094,276 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 25,264 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,553 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 721 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.