Evidence map›Paper›PMID 25319261›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2014

Dynamic architecture of a protein kinase.

Christopher L McClendon, Alexandr P Kornev, Michael K Gilson, Susan S Taylor

Erratum issuedOpen access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2014. 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 144 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
144citing papers in PubMed, 1 pooled it
6.4field-weighted citation impact, top 3% of its field
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

144 citing papers in PubMed, 1 synthesis or guideline pooled it, 263 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Tyrosine kinases sample unique activation ensembles.bioRxiv : the preprint server for biology · 2026
    Article
  4. ERK autoinhibition mechanism informs a drug combination strategy.Protein science : a publication of the Protein Society · 2026
    Article
  5. Article
  6. Article
  7. Conformational Dynamics and Allostery in the cAMP-Protein Kinase A Signalosome.Advances in experimental medicine and biology · 2026
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

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

4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Christopher L McClendonDepartment of Chemistry and Biochemistry and Skaggs School of Pharmacy and Pharmaceutical Sciences, and.
Alexandr P KornevHoward Hughes Medical Institute, University of California at San Diego, La Jolla, CA 92093 Department of Pharmacology, akornev@ucsd.edu staylor@ucsd.edu.
Michael K GilsonSkaggs School of Pharmacy and Pharmaceutical Sciences, and.
Susan S TaylorDepartment of Chemistry and Biochemistry and Howard Hughes Medical Institute, University of California at San Diego, La Jolla, CA 92093 Department of Pharmacology, akornev@ucsd.edu staylor@ucsd.edu.
University of Montana · USHoward Hughes Medical Institute · USUniversity of California, San Diego · US

Funding

TrainingP41GM103712 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SEJNOWSKI, TERRENCE J · 2012 to 2021
$16.3M
THEORY AND MODELING OF NONCOVALENT BINDINGR01GM061300 · NIGMS · UNIVERSITY OF MD BIOTECHNOLOGY INSTITUTE · PI GILSON, MICHAEL K. · 2000 to 2021
$7.2M
Mapping Allosteric Cooperativity in Protein KinasesR01GM100310 · NIGMS · UNIVERSITY OF MINNESOTA · PI VEGLIA, GIANLUIGI · 2012 to 2019
$4.3M
Mechanical and Dynamical Regulation of Protein KinasesF32GM099197 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCCLENDON, CHRISTOPHER LEE · 2011 to 2014
$131k
Howard Hughes Medical InstituteNIGMS NIH HHS F32 GM099197NIGMS NIH HHS P41 GM103712NIGMS NIH HHS P41GM103712-S1NIGMS NIH HHS R01 GM061300NIGMS NIH HHS R01 GM100310
6 · The paper itself

Abstract

Protein kinases are dynamically regulated signaling proteins that act as switches in the cell by phosphorylating target proteins. To establish a framework for analyzing linkages between structure, function, dynamics, and allostery in protein kinases, we carried out multiple microsecond-scale molecular-dynamics simulations of protein kinase A (PKA), an exemplar active kinase. We identified residue-residue correlated motions based on the concept of mutual information and used the Girvan-Newman method to partition PKA into structurally contiguous "communities." Most of these communities included 40-60 residues and were associated with a particular protein kinase function or a regulatory mechanism, and well-known motifs based on sequence and secondary structure were often split into different communities. The observed community maps were sensitive to the presence of different ligands and provide a new framework for interpreting long-distance allosteric coupling. Communication between different communities was also in agreement with the previously defined architecture of the protein kinase core based on the "hydrophobic spine" network. This finding gives us confidence in suggesting that community analyses can be used for other protein kinases and will provide an efficient tool for structural biologists. The communities also allow us to think about allosteric consequences of mutations that are linked to disease.

Indexed as

Molecular Dynamics SimulationAdenosine TriphosphateAllosteric RegulationCatalytic DomainLigandsMagnesiumMutagenesisProtein KinasesReproducibility of ResultsTemplates, GeneticAdenosine TriphosphateLigandsMagnesiumProtein Kinasescommunity analysismolecular dynamicsphosphorylation

Identifiers

PMID25319261
PMCPMC4217441
OpenAlexW2043224156

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.