Evidence map›Paper›PMID 19798437›Full record

ArticlePLoS computational biology2009

Perturbation-based Markovian transmission model for probing allosteric dynamics of large macromolecular assembling: a study of GroEL-GroES.

Hsiao-Mei Lu, Jie Liang

Abstract read
In one paragraph

Article in PLoS computational biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Machine learning and protein allostery.Trends in biochemical sciences · 2023
    Review
  3. Article
  4. Allosteric differences dictate GroEL complementation of E. coli.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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.

Hsiao-Mei LuDepartment of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA.
Jie Liang

Funding

Chicago Tri-Institutional Center for Chemical Methods and Library DevelopmentP50GM086145 · NIGMS · UNIVERSITY OF CHICAGO · PI KOZMIN, SERGEY A · 2008 to 2012
$9.9M
Computational assembly of beta-barrel membrane proteinsR01GM079804 · NIGMS · UNIVERSITY OF ILLINOIS AT CHICAGO · PI LIANG, JIE · 2007 to 2016
$2.8M
High-Accuracy Models of Proteins from Remote HomologyR01GM081682 · NIGMS · UNIVERSITY OF ILLINOIS AT CHICAGO · PI LIANG, JIE · 2007 to 2009
$824k
NIGMS NIH HHS GM079804NIGMS NIH HHS GM081682NIGMS NIH HHS GM086145NIGMS NIH HHS P50 GM086145NIGMS NIH HHS R01 GM079804NIGMS NIH HHS R01 GM081682
6 · The paper itself

Abstract

Large macromolecular assemblies are often important for biological processes in cells. Allosteric communications between different parts of these molecular machines play critical roles in cellular signaling. Although studies of the topology and fluctuation dynamics of coarse-grained residue networks can yield important insights, they do not provide characterization of the time-dependent dynamic behavior of these macromolecular assemblies. Here we develop a novel approach called Perturbation-based Markovian Transmission (PMT) model to study globally the dynamic responses of the macromolecular assemblies. By monitoring simultaneous responses of all residues (>8,000) across many (>6) decades of time spanning from the initial perturbation until reaching equilibrium using a Krylov subspace projection method, we show that this approach can yield rich information. With criteria based on quantitative measurements of relaxation half-time, flow amplitude change, and oscillation dynamics, this approach can identify pivot residues that are important for macromolecular movement, messenger residues that are key to signal mediating, and anchor residues important for binding interactions. Based on a detailed analysis of the GroEL-GroES chaperone system, we found that our predictions have an accuracy of 71-84% judged by independent experimental studies reported in the literature. This approach is general and can be applied to other large macromolecular machineries such as the virus capsid and ribosomal complex.

Indexed as

Models, ChemicalModels, StatisticalBinding SitesChaperonin 10Chaperonin 60Markov ChainsMultiprotein ComplexesProtein BindingChaperonin 10Chaperonin 60Multiprotein Complexes

Identifiers

PMID19798437
PMCPMC2741606

What OpenQuestion holds

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LicenceCC BY
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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.