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Record W2885078229 · doi:10.1371/journal.pone.0202036

Conservation of kinase-phosphorylation site pairings: Evidence for an evolutionarily dynamic phosphoproteome

2018· article· en· W2885078229 on OpenAlexafffund
Megan McDonald, Brett Trost, Scott Napper

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKinomePhosphorylationBiologyProtein phosphorylationPhosphorylation cascadeContext (archaeology)KinaseCell biologyProtein kinase A

Abstract

fetched live from OpenAlex

Kinase-mediated protein phosphorylation is a central mechanism for regulation of cellular responses and phenotypes. While considerable information is available regarding the evolutionary relationships within the kinase family, as well as the evolutionary conservation of phosphorylation sites, each aspect of this partnership is typically considered in isolation, despite their clear functional relationship. Here, to offer a more holistic perspective on the evolution of protein phosphorylation, the conservation of protein phosphorylation sites is considered in the context of the conservation of the corresponding modifying kinases. Specifically, conservation of defined kinase-phosphorylation site pairings (KPSPs), as well as of each of the component parts (the kinase and the phosphorylation site), were examined across a range of species. As expected, greater evolutionary distance between species was generally associated with lower probability of KPSP conservation, and only a small fraction of KPSPs were maintained across all species, with the vast majority of KPSP losses due to the absence of the phosphorylation site. This supports a model in which a relatively stable kinome promotes the emergence of functional substrates from an evolutionarily malleable phosphoproteome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.305
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2018
Admission routes2
Has abstractyes

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