Evidence map›Paper›PMID 30598552›Full record

ReviewNature structural & molecular biology2019

Understanding molecular mechanisms in cell signaling through natural and artificial sequence variation.

Neel H Shah, John Kuriyan

Abstract readReview
In one paragraph

Review in Nature structural & molecular biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Deciphering the Molecular Interplay Between RXLR-EncodedInternational journal of molecular sciences · 2025
    Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. 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

2 authors.

Neel H ShahDepartment of Chemistry, Columbia University, New York, NY, USA. neel.shah@columbia.edu.ORCID http://orcid.org/0000-0002-1186-0626
John KuriyanDepartment of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA. kuriyan@berkeley.edu.ORCID http://orcid.org/0000-0002-4414-5477

Funding

Understand the metabolic fitness of naïve T cellsP01AI091580 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JEROEN ROOSE · 2011 to 2026
$31.1M
NIAID NIH HHS P01 AI091580
6 · The paper itself

Abstract

The functionally tolerated sequence space of proteins can now be explored in an unprecedented way, owing to the expansion of genomic databases and the development of high-throughput methods to interrogate protein function. For signaling proteins, several recent studies have shown how the analysis of sequence variation leverages the available protein-structure information to provide new insights into specificity and allosteric regulation. In this Review, we discuss recent work that illustrates how this emerging approach is providing a deeper understanding of signaling proteins.

Indexed as

AnimalsHumansModels, BiologicalProtein BindingProteinsProtein Structure, SecondarySignal TransductionSubstrate SpecificityProteins

Identifiers

PMID30598552
PMCPMC6463301

What Socratic holds

Textmetadata
LicenceTDM
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.