Evidence map›Paper›PMID 18784977›Full record

ArticleJournal of biomolecular NMR2008

Automatic assignment of protein backbone resonances by direct spectrum inspection in targeted acquisition of NMR data.

Leo E Wong, James E Masse, Victor Jaravine, Vladislav Orekhov, Konstantin Pervushin

Open access · bronzeAbstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Journal of biomolecular NMR, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 4 institutions in 7 countries.

Leo E WongSchool of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore.
James E Masse
Victor Jaravine
Vladislav Orekhov
Konstantin Pervushin
Nanyang Technological University · SGGoethe University Frankfurt · DENational Institutes of Health · USUniversity of Gothenburg · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The necessity to acquire large multidimensional datasets, a basis for assignment of NMR resonances, results in long data acquisition times during which substantial degradation of a protein sample might occur. Here we propose a method applicable for such a protein for automatic assignment of backbone resonances by direct inspection of multidimensional NMR spectra. In order to establish an optimal balance between completeness of resonance assignment and losses of cross-peaks due to dynamic processes/degradation of protein, assignment of backbone resonances is set as a stirring criterion for dynamically controlled targeted nonlinear NMR data acquisition. The result is demonstrated with the 12 kDa (13)C,(15) N-labeled apo-form of heme chaperone protein CcmE, where hydrolytic cleavage of 29 C-terminal amino acids is detected. For this protein, 90 and 98% of manually assignable resonances are automatically assigned within 10 and 40 h of nonlinear sampling of five 3D NMR spectra, respectively, instead of 600 h needed to complete the full time domain grid. In addition, resonances stemming from degradation products are identified. This study indicates that automatic resonance assignment might serve as a guiding criterion for optimal run-time allocation of NMR resources in applications to proteins prone to degradation.

Indexed as

Amino Acid SequenceBacterial Outer Membrane ProteinsEscherichia coli ProteinsHemeproteinsMolecular Sequence DataNuclear Magnetic Resonance, BiomolecularProtein ConformationBacterial Outer Membrane ProteinsCcmE protein, E coliEscherichia coli ProteinsHemeproteins

Identifiers

PMID18784977
OpenAlexW1987135285

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.