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Record W2124872173 · doi:10.1002/cbic.201402045

Protein Arginine N‐Methyltransferase Substrate Preferences for Different Nη‐Substituted Arginyl Peptides

2014· article· en· W2124872173 on OpenAlexafffund
Dylan Thomas, Ted M. Lakowski, Helmi Kreinin, Mynol I. Vhuiyan, Shona Anne Sedlock, Jennifer M. Bui, Nathaniel I. Martin, Adam Frankel

Bibliographic record

VenueChemBioChem · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsUniversity of ManitobaUniversity of British Columbia
FundersConcordia University
KeywordsGuanidineMoietyMethylationArginineMethyltransferaseChemistryStereochemistryBiochemistryAmino acidProtein arginine methyltransferase 5LysineMethionineResidue (chemistry)EnzymeDNA

Abstract

fetched live from OpenAlex

Protein arginine N-methyltransferases (PRMTs) catalyze methyl-group transfer from S-adenosyl-L-methionine onto arginine residues in proteins. In this study, modifications were introduced at the guanidine moiety of a peptidyl arginine residue to investigate how changes to the PRMT substrate can modulate enzyme activity. We found that peptides bearing Nη-hydroxy or Nη-amino substituted arginine showed higher apparent kcat values than for the monomethylated substrate when using PRMT1, whereas this catalytic preference was not observed for PRMT4 and PRMT6. Methylation by compromised PRMT1 variants E153Q and D51N further supports the finding that the N-hydroxy substitution facilitates methyl transfer by tuning the reactivity of the guanidine moiety. In contrast, Nη-nitro and Nη-canavanine substituted substrates inhibit PRMT activity. These findings demonstrate that methylation of these PRMT substrates is dependent on the nature of the modification at the guanidine moiety.

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 categoriesMeta-epidemiology (narrow)
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 score0.010
Threshold uncertainty score1.000

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 head0.012
GPT teacher head0.237
Teacher spread0.225 · 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.

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

Citations14
Published2014
Admission routes2
Has abstractyes

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