Evidence map›Paper›PMID 24922508›Full record

ArticlePLoS computational biology2014

Computational modeling of allosteric regulation in the hsp90 chaperones: a statistical ensemble analysis of protein structure networks and allosteric communications.

Kristin Blacklock, Gennady M Verkhivker

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
4.6field-weighted citation impact, top 5% 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

39 citing papers in PubMed, 1 synthesis or guideline pooled it, 94 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Temperature induces a shift from insulin dihexamer to hexamer in collective dynamics.Protein science : a publication of the Protein Society · 2025
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  5. Review
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  7. Article
  8. Article
  9. Mapping allosteric pathway in NIa-Pro using computational approach.Quantitative biology (Beijing, China) · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Community Network Analysis of Allosteric Proteins.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  17. Article
  18. Integrated Computational Approaches and Tools forAllosteric Drug Discovery.International journal of molecular sciences · 2020
    Review
  19. 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

2 authors at 2 institutions in 1 country.

Kristin BlacklockSchool of Computational Sciences and Crean School of Health and Life Sciences, Schmid College of Science and Technology, Chapman University, Orange, California, United States of America.
Gennady M VerkhivkerSchool of Computational Sciences and Crean School of Health and Life Sciences, Schmid College of Science and Technology, Chapman University, Orange, California, United States of America; Department of Pharmacology, University of California San Diego, La Jolla, California, United States of America.
Chapman University · USUniversity of California, San Diego · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks.

Indexed as

Molecular Dynamics SimulationAdenosine TriphosphatasesAdenosine TriphosphateAllosteric RegulationBacterial ProteinsFungal ProteinsHSP90 Heat-Shock ProteinsMolecular ChaperonesProtein BindingProtein ConformationThermodynamicsAdenosine TriphosphatasesAdenosine TriphosphateBacterial ProteinsFungal ProteinsHSP90 Heat-Shock ProteinsMolecular Chaperones

Identifiers

PMID24922508
PMCPMC4055421
OpenAlexW2005490060

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.