Evidence map›Paper›PMID 26032515›Full record

ArticleProtein science : a publication of the Protein Society2015

Residue-level global and local ensemble-ensemble comparisons of protein domains.

Sarah A Clark, Dale E Tronrud, P Andrew Karplus

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Protein science : a publication of the Protein Society, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Sarah A ClarkDepartment of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon, 97331.
Dale E TronrudDepartment of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon, 97331.
P Andrew KarplusDepartment of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon, 97331.
Oregon State University · US

Funding

Improving Modeling by Learning from Details of High Accuracy Protein StructuresR01GM083136 · NIGMS · OREGON STATE UNIVERSITY · PI KARPLUS, PAUL ANDREW · 2008 to 2015
$1.7M
NIGMS NIH HHS R01 GM083136NIGMS NIH HHS R01-GM083136
6 · The paper itself

Abstract

Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a "consistency check" of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons.

Indexed as

Computational BiologyCrystallography, X-RayMagnetic Resonance SpectroscopyModels, MolecularProtein ConformationProteinsProtein Structure, TertiaryProteinsforce field optimizationhomology modelingNMR ensembleprotein comparisonsRosettastructure predictionstructure validationsuperpositiontemplate-based modeling

Identifiers

PMID26032515
PMCPMC4570546
OpenAlexW2141725740

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.