Evidence map›Paper›PMID 36257955›Full record

ArticleNature communications2022

Rapid protein assignments and structures from raw NMR spectra with the deep learning technique ARTINA.

Piotr Klukowski, Roland Riek, Peter Güntert

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

68 citing papers in PubMed.

  1. NMR Studies on Protein-Ligand Interactions.International journal of molecular sciences · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. The NMR Exchange Format (NEF): Specification and Applications.bioRxiv : the preprint server for biology · 2026
    Article
  9. Article
  10. AMIGO - Guided assignment ofJournal of biomolecular NMR · 2026
    Article
  11. Article
  12. Deep Learning Assisted Proton Pure Shift NMR Spectroscopy.Journal of the American Chemical Society · 2026
    Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Biomolecular NMR assignments · 2025
    Article
  20. Article

8 more citing papers are in PubMed but not listed here.

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.

Piotr KlukowskiLaboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland. piotr.klukowski@phys.chem.ethz.ch.ORCID 0000-0003-1045-3487
Roland RiekLaboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland. roland.riek@phys.chem.ethz.ch.ORCID 0000-0002-6333-066X
Peter GüntertLaboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland. peter.guentert@phys.chem.ethz.ch.ORCID 0000-0002-2911-7574

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nuclear Magnetic Resonance (NMR) spectroscopy is a major technique in structural biology with over 11,800 protein structures deposited in the Protein Data Bank. NMR can elucidate structures and dynamics of small and medium size proteins in solution, living cells, and solids, but has been limited by the tedious data analysis process. It typically requires weeks or months of manual work of a trained expert to turn NMR measurements into a protein structure. Automation of this process is an open problem, formulated in the field over 30 years ago. We present a solution to this challenge that enables the completely automated analysis of protein NMR data within hours after completing the measurements. Using only NMR spectra and the protein sequence as input, our machine learning-based method, ARTINA, delivers signal positions, resonance assignments, and structures strictly without human intervention. Tested on a 100-protein benchmark comprising 1329 multidimensional NMR spectra, ARTINA demonstrated its ability to solve structures with 1.44 Å median RMSD to the PDB reference and to identify 91.36% correct NMR resonance assignments. ARTINA can be used by non-experts, reducing the effort for a protein assignment or structure determination by NMR essentially to the preparation of the sample and the spectra measurements.

Indexed as

Deep LearningAlgorithmsHumansMagnetic Resonance SpectroscopyNuclear Magnetic Resonance, BiomolecularProteinsProteins

Identifiers

PMID36257955
PMCPMC9579175

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.