Evidence map›Paper›PMID 24516371›Full record

ArticlePLoS computational biology2014

Compact modeling of allosteric multisite proteins: application to a cell size checkpoint.

Germán Enciso, Douglas R Kellogg, Arturo Vargas

Abstract 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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Germán EncisoDepartment of Mathematics, Department of Developmental and Cell Biology, University of California Irvine, Irvine, California, United States of America.
Douglas R KelloggDepartment of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, California, United States of America.
Arturo VargasComputational and Applied Mathematics Department, Rice University, Houston, Texas, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We explore a framework to model the dose response of allosteric multisite phosphorylation proteins using a single auxiliary variable. This reduction can closely replicate the steady state behavior of detailed multisite systems such as the Monod-Wyman-Changeux allosteric model or rule-based models. Optimal ultrasensitivity is obtained when the activation of an allosteric protein by its individual sites is concerted and redundant. The reduction makes this framework useful for modeling and analyzing biochemical systems in practical applications, where several multisite proteins may interact simultaneously. As an application we analyze a newly discovered checkpoint signaling pathway in budding yeast, which has been proposed to measure cell growth by monitoring signals generated at sites of plasma membrane growth. We show that the known components of this pathway can form a robust hysteretic switch. In particular, this system incorporates a signal proportional to bud growth or size, a mechanism to read the signal, and an all-or-none response triggered only when the signal reaches a threshold indicating that sufficient growth has occurred.

Indexed as

Models, BiologicalAdaptor Proteins, Signal TransducingAllosteric SiteCell Growth ProcessesComputational BiologyModels, MolecularPhosphorylationProtein Kinase CProtein Phosphatase 2Protein Processing, Post-TranslationalProteinsrho GTP-Binding ProteinsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSignal TransductionAdaptor Proteins, Signal TransducingPKC1 protein, S cerevisiaeProtein Kinase CProtein Phosphatase 2ProteinsRHO1 protein, S cerevisiaerho GTP-Binding ProteinsSaccharomyces cerevisiae ProteinsZDS1 protein, S cerevisiae

Identifiers

PMID24516371
PMCPMC3916233

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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.