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Article details
Title
Comparison of protein solution structures refined by molecular dynamics simulation in vacuum, with a generalized Born model, and with explicit water
Published in
Journal of Biomolecular NMR, April 2002
DOI 10.1023/a:1014929925008
Pubmed ID
Authors
Abstract

The inclusion of explicit solvent water in molecular dynamics refinement of NMR structures ought to provide the most physically meaningful accounting for the effects of solvent on structure, but is computationally expensive. In order to evaluate the validity of commonly used vacuum refinements and of recently developed continuum solvent model methods, we have used three different methods to refine a set of NMR solution structures of a medium sized protein, Escherichia coli glutaredoxin 2, from starting structures calculated using the program DYANA. The three different refinement protocols used molecular dynamics simulated annealing with the program AMBER in vacuum (VAC), including a generalized Born (GB) solvent model, and a full calculation including explicit solvent water (WAT). The structures obtained using the three methods of refinements were very similar, a reflection of their generally well-determined nature. However, the structures refined with the generalized Born model were more similar to those from explicit water refinement than those refined in vacuum. Significant improvement was seen in the percentage of backbone dihedral angles in the most favored regions of phi, psi space and in hydrogen bond pattern for structures refined with the GB and WAT models, compared with the structures refined in vacuum. The explicit water calculation took an average of 200 h of CPU time per structure on an SGI cluster, compared to 15-90 h for the GB calculation (depending on the parameters used) and 2 h for the vacuum calculation. The generalized Born solvent model proved to be an excellent compromise between the vacuum and explicit water refinements, giving results comparable to those of the explicit water calculation. Some improvement for phi and psi angle distribution and hydrogen bond pattern can also be achieved by energy minimizing the vacuum structures with the GB model, which takes a much shorter time than MD simulations with the GB model.

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Mendeley demographics

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The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 1%
Russia 1 1%
Norway 1 1%
Italy 1 1%
Brazil 1 1%
Australia 1 1%
Unknown 69 92%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 26 35%
Researcher 22 29%
Professor 6 8%
Student > Master 4 5%
Other 2 3%
Other 6 8%
Unknown 9 12%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 22 29%
Chemistry 22 29%
Biochemistry, Genetics and Molecular Biology 11 15%
Physics and Astronomy 3 4%
Computer Science 2 3%
Other 1 1%
Unknown 14 19%
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 02 November 2014.
All research outputs
#30,991,015
of 34,187,751 outputs
Outputs from Journal of Biomolecular NMR
#724
of 787 outputs
Outputs of similar age
#175,845
of 179,097 outputs
Outputs of similar age from Journal of Biomolecular NMR
#5
of 5 outputs
Altmetric has tracked 34,187,751 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 787 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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