Evidence map›Paper›PMID 7811949›Full record

ArticleBiophysical journal1994

A Monte Carlo study of the dynamics of G-protein activation.

P A Mahama, J J Linderman

Abstract read
In one paragraph

Article in Biophysical journal, 1994. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

29 citing papers in PubMed.

  1. Article
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  5. The G protein GThe Journal of biological chemistry · 2017
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  19. Computational modeling reveals how interplay between components of a GTPase-cycle module regulates signal transduction.Proceedings of the National Academy of Sciences of the United States of America · 2004
    Article
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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.

P A MahamaDepartment of Chemical Engineering, University of Michigan, Ann Arbor 48109-2136.
J J Linderman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To link quantitatively the cell surface binding of ligand to receptor with the production of cellular responses, it may be necessary to explore early events in signal transduction such as G-protein activation. Two different model frameworks relating receptor/ligand binding to G-protein activation are examined. In the first framework, a simple ordinary differential equation model is used to describe receptor/ligand binding and G-protein activation. In the second framework, the events leading to G-protein activation are simulated using a dynamic Monte Carlo model. In both models, reactions between ligand-bound receptors and G-proteins are assumed to be diffusion-limited. The Monte Carlo model predicts two regimes of G-protein activation, depending upon whether the lifetime of a receptor/ligand complex is long or short compared with the time needed for diffusional encounters of complexes and G-proteins. When the lifetime of a complex is relatively short compared with the diffusion time, the movement of ligand among free receptors by binding and unbinding ("switching") significantly enhances G-protein activation. Receptor antagonists dramatically reduce G-protein activation and, thus, signal transduction in this case, and significant clustering of active G-proteins near receptor/ligand complexes results. The simple ordinary differential equation model poorly predicts G-protein activation for this situation. In the alternative case, when diffusion is relatively fast, ligand movement among receptors is less important and the simple ordinary differential equation model and Monte Carlo model results are similar. In this case, there is little clustering of active G-proteins near receptor/ligand complexes. Results also indicate that as the GTPase activity of the alpha-subunit decreases, the steady-state level of alpha-GTP increases, although temporal sensitivity is compromised.

Indexed as

Models, BiologicalAnimalsBiophysical PhenomenaBiophysicsCell MembraneDiffusionGTP-Binding ProteinsGTP PhosphohydrolasesGuanosine DiphosphateGuanosine TriphosphateHumansKineticsLigandsMonte Carlo MethodReceptors, Cell SurfaceSignal TransductionGTP-Binding ProteinsGTP PhosphohydrolasesGuanosine DiphosphateGuanosine TriphosphateLigandsReceptors, Cell Surface

Identifiers

PMID7811949
PMCPMC1225491

What OpenQuestion holds

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Registered trials

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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.