Evidence map›Paper›PMID 34338940›Full record

ArticleJournal of biomolecular NMR2021

An automated iterative approach for protein structure refinement using pseudocontact shifts.

Stefano Cucuzza, Peter Güntert, Andreas Plückthun, Oliver Zerbe

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In one paragraph

Article in Journal of biomolecular NMR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Stefano CucuzzaDepartment of Chemistry, University of Zürich, Winterthurerstrasse 190, 8057, Zürich, Switzerland.ORCID http://orcid.org/0000-0002-5655-6505
Peter GüntertInstitute of Biophysical Chemistry and Center for Biomolecular Magnetic Resonance, Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany.ORCID http://orcid.org/0000-0002-2911-7574
Andreas PlückthunDepartment of Biochemistry, University of Zürich, Winterthurerstrasse 190, 8057, Zürich, Switzerland.ORCID http://orcid.org/0000-0003-4191-5306
Oliver ZerbeDepartment of Chemistry, University of Zürich, Winterthurerstrasse 190, 8057, Zürich, Switzerland. oliver.zerbe@chem.uzh.ch.ORCID http://orcid.org/0000-0003-0475-438X

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 122686
6 · The paper itself

Abstract

NMR structure calculation using NOE-derived distance restraints requires a considerable number of assignments of both backbone and sidechains resonances, often difficult or impossible to get for large or complex proteins. Pseudocontact shifts (PCSs) also play a well-established role in NMR protein structure calculation, usually to augment existing structural, mostly NOE-derived, information. Existing refinement protocols using PCSs usually either require a sizeable number of sidechain assignments or are complemented by other experimental restraints. Here, we present an automated iterative procedure to perform backbone protein structure refinements requiring only a limited amount of backbone amide PCSs. Already known structural features from a starting homology model, in this case modules of repeat proteins, are framed into a scaffold that is subsequently refined by experimental PCSs. The method produces reliable indicators that can be monitored to judge about the performance. We applied it to a system in which sidechain assignments are hardly possible, designed Armadillo repeat proteins (dArmRPs), and we calculated the solution NMR structure of YM

Indexed as

ProteinsMagnetic Resonance SpectroscopyModels, MolecularNuclear Magnetic Resonance, BiomolecularProtein ConformationProteinsArmadillo repeat proteinNMRPseudocontact shiftStructure refinement

Identifiers

PMID34338940
PMCPMC8473369

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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.