Evidence map›Paper›PMID 26861881›Full record

ArticleThe Journal of biological chemistry2016

Identification of Unintuitive Features of Sumoylation through Mathematical Modeling.

Shraddha S Puntambekar, Dimpal Nyayanit, Priyanka Saxena, Chetan J Gadgil

Abstract read
In one paragraph

Article in The Journal of biological chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Shraddha S PuntambekarFrom the Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune-411008, and the Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune-411008, and.
Dimpal NyayanitFrom the Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune-411008, and the Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune-411008, and.
Priyanka Saxenathe Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune-411008, and the CSIR-Institute of Genomics and Integrative Biology, New Delhi 110020, India.
Chetan J GadgilFrom the Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune-411008, and the Academy of Scientific and Innovative Research (AcSIR), CSIR-NCL Campus, Pune-411008, and the CSIR-Institute of Genomics and Integrative Biology, New Delhi 110020, India cj.gadgil@ncl.res.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sumoylation is a multistep, multienzymatic post-translational modification in which a small ubiquitin-like modifier protein (SUMO) is attached to the target. We present the first mathematical model for sumoylation including enzyme mechanism details such as autosumoylation of E2 and multifunctional nature of SENP. Simulations and analysis reveal three nonobvious properties for the long term response, modeled as an open system: (i) the steady state sumoylation level is robust to variation in several enzyme properties; (ii) even when autosumoylation of E2 results in equal or higher activity, the target sumoylation levels are lower; and (iii) there is an optimal SENP concentration at which steady state target sumoylation level is maximum. These results are qualitatively different for a short term response modeled as a closed system, where e.g. sumoylation always decreases with increasing SENP levels. Simulations with multiple targets suggest that the available SUMO is limiting, indicating a possible explanation for the experimentally observed low fractional sumoylation. We predict qualitative differences in system responses at short post-translational and longer transcriptional time scales. We thus use this mechanism-based model to explain system properties and generate testable hypotheses for existence and mechanism of unexpected responses.

Indexed as

Models, BiologicalAnimalsHumansSumoylationautomodificationbifunctional enzymecyclic pathwayenzyme catalysisenzyme kineticsmathematical modelingpost-translational modification (PTM)sumoylation

Identifiers

PMID26861881
PMCPMC4850286

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.