Evidence map›Paper›PMID 19690801›Full record

ReviewCellular and molecular life sciences : CMLS2009

The protein meta-structure: a novel concept for chemical and molecular biology.

Robert Konrat

Abstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Association between Predicted Effects ofInternational journal of molecular sciences · 2021
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. NMR contributions to structural dynamics studies of intrinsically disordered proteins.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2014
    Review
  15. Protonation-dependent conformational variability of intrinsically disordered proteins.Protein science : a publication of the Protein Society · 2013
    Article
  16. Review
  17. Article
  18. Article
  19. The effect of edge definition of complex networks on protein structure identification.Computational and mathematical methods in medicine · 2013
    Article
  20. 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

1 author.

Robert KonratDepartment of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna, Vienna Biocenter Campus 5, 1030, Vienna, Austria. robert.konrat@univie.ac.at

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ultimate goal of bioinformatics or computational chemical biology is the sequence-based prediction of protein functionality. However, due to the degeneracy of the primary sequence code there is no unambiguous relationship. The degeneracy can be partly lifted by going to higher levels of abstraction and, for example, incorporating 3D structural information. However, sometimes even at this conceptual level functional ambiguities often remain. Here a novel conceptual framework is described (the protein meta-structure). At this level of abstraction, the protein structure is viewed as an intricate network of interacting residues. This novel conception offers unique possibilities for chemical (molecular) biology, structural genomics and drug discovery. In this review some prototypical applications will be presented that serve to illustrate the potential of the methodology.

Indexed as

Protein ConformationAnimalsChemistry, AnalyticComputational BiologyConcept FormationHumansModels, MolecularMolecular BiologyProteinsStructure-Activity RelationshipProteins

Identifiers

PMID19690801
PMCPMC11115628

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.