Evidence map›Paper›PMID 26474790›Full record

ArticleJournal of biomolecular NMR2015

Ensembles of a small number of conformations with relative populations.

Vijay Vammi, Guang Song

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of biomolecular NMR, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Vijay VammiBioinformatics and Computational Biology Program, Department of Computer Science, Iowa State University, 226 Atanasoff Hall, Ames, IA, 50011, USA. vsvammi@iastate.edu.
Guang SongBioinformatics and Computational Biology Program, Department of Computer Science, Iowa State University, 226 Atanasoff Hall, Ames, IA, 50011, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In our previous work, we proposed a new way to represent protein native states, using ensembles of a small number of conformations with relative Populations, or ESP in short. Using Ubiquitin as an example, we showed that using a small number of conformations could greatly reduce the potential of overfitting and assigning relative populations to protein ensembles could significantly improve their quality. To demonstrate that ESP indeed is an excellent alternative to represent protein native states, in this work we compare the quality of two ESP ensembles of Ubiquitin with several well-known regular ensembles or average structure representations. Extensive amount of significant experimental data are employed to achieve a thorough assessment. Our results demonstrate that ESP ensembles, though much smaller in size comparing to regular ensembles, perform equally or even better sometimes in all four different types of experimental data used in the assessment, namely, the residual dipolar couplings, residual chemical shift anisotropy, hydrogen exchange rates, and solution scattering profiles. This work further underlines the significance of having relative populations in describing the native states.

Indexed as

Models, MolecularAmidesAnisotropyNuclear Magnetic Resonance, BiomolecularProtein ConformationScattering, Small AngleSolutionsUbiquitinX-Ray DiffractionAmidesSolutionsUbiquitinHydrogen exchange ratesNMROverfittingResidual chemical shift anisotropyResidual dipolar couplingsSAXSUbiquitinWAXS

Identifiers

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.