Evidence map›Paper›PMID 32751110›Full record

ReviewMolecules (Basel, Switzerland)2020

Moonlighting Proteins in the Fuzzy Logic of Cellular Metabolism.

Haipeng Liu, Constance J Jeffery

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Molecular Identification and Bioinformatics Analysis ofPathogens (Basel, Switzerland) · 2024
    Article
  5. Article
  6. Lipoic acid attachment to proteins: stimulating new developments.Microbiology and molecular biology reviews : MMBR · 2024
    Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Moonlighting enzymes: when cellular context defines specificity.Cellular and molecular life sciences : CMLS · 2023
    Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Moonlighting in Rickettsiales: Expanding Virulence Landscape.Tropical medicine and infectious disease · 2022
    Review
  19. Review
  20. Review
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.

Haipeng LiuCenter for Biomolecular Sciences, College of Pharmacy, University of Illinois at Chicago, 900 South Ashland Avenue, Chicago, IL 60607, USA.
Constance J JefferyDepartment of Biological Sciences, University of Illinois at Chicago, 900 South Ashland Avenue, Chicago, IL 60607, USA.ORCID 0000-0002-2147-3638

Funding

University of Illinois Cancer Center Pilot Project Grant Award
6 · The paper itself

Abstract

The numerous interconnected biochemical pathways that make up the metabolism of a living cell comprise a fuzzy logic system because of its high level of complexity and our inability to fully understand, predict, and model the many activities, how they interact, and their regulation. Each cell contains thousands of proteins with changing levels of expression, levels of activity, and patterns of interactions. Adding more layers of complexity is the number of proteins that have multiple functions. Moonlighting proteins include a wide variety of proteins where two or more functions are performed by one polypeptide chain. In this article, we discuss examples of proteins with variable functions that contribute to the fuzziness of cellular metabolism.

Indexed as

Energy MetabolismFuzzy LogicMetabolic Networks and PathwaysModels, BiologicalAnimalsHumansProtein BindingProteinsProteinsfuzzy logicintrinsically disordered proteinsmetamorphic proteinsmoonlighting proteinsmorpheeins

Identifiers

PMID32751110
PMCPMC7435893

What OpenQuestion 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 OpenQuestion graph.