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Record W2030526808 · doi:10.4161/cc.9.7.11066

Roles of “junk phosphorylation” in modulating biomolecular association of phosphorylated proteins?

2010· article· en· W2030526808 on OpenAlexaff
Chris Soon Heng Tan, Claus Jørgensen, Rune Linding

Bibliographic record

VenueCell Cycle · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersSynchrotron Light Research Institute
KeywordsPhosphorylationBiologyProtein phosphorylationConserved sequencePhosphorylation cascadeProteomeAutophagy-related protein 13Computational biologyGeneticsCell biologyProtein kinase APeptide sequenceGene

Abstract

fetched live from OpenAlex

Protein phosphorylation dynamically regulates cellular activities in response to environmental cues. Sequence conservation analysis of recent proteome-wide phosphorylation data revealed that many previously unidentified phosphorylation sites are not well-conserved leading to the proposal that many are non-functional. However, this is based on the assumption that protein phosphorylation modulates protein function through specific position on protein sequence. Based on emerging understanding on phospho-regulation of cellular activities, we argue, with examples, that non-positionally conserved phosphorylation sites can very well be functional. We previously identified phosphorylation events that need not be conserved at same positions across orthologous proteins but are likely maintained by evolutionary conserved signaling networks through orthologous kinases. We found that proteins with such conserved phosphorylation patterns are statistically over-represented with protein and DNA-binding annotation. Here, we further correlated these proteins with protein-protein interaction data from an independent systematic study and observed they indeed interact frequently with other proteins. Hence, we speculate that non-positionally conserved phosphorylation site could be modulating biomolecular association of phosphorylated proteins possibly through fine-tuning protein's bulk electrostatic charge and through creating binding sites for phospho-binding interaction domains. We, therefore, advocate the development of complementary evolutionary approaches to interpret physiological important sites.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.003
GPT teacher head0.197
Teacher spread0.194 · 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 teacher head, 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

Citations30
Published2010
Admission routes1
Has abstractyes

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