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Record W2510334948 · doi:10.1021/acs.jmedchem.6b01033

Discovery of a Potent, Selective, and Cell-Active Dual Inhibitor of Protein Arginine Methyltransferase 4 and Protein Arginine Methyltransferase 6

2016· article· en· W2510334948 on OpenAlex
Yudao Shen, Magdalena M. Szewczyk, Mohammad S. Eram, David Smil, H. Ümit Kanıskan, Renato Ferreira de Freitas, Guillermo Senisterra, Fengling Li, Matthieu Schapira, Peter J. Brown, C.H. Arrowsmith, Dalia Baršytė-Lovejoy, Jing Liu, Masoud Vedadi, Jian Jin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Medicinal Chemistry · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsPrincess Margaret Cancer CentreStructural Genomics ConsortiumUniversity of Toronto
FundersStructural Genomics ConsortiumNational Institute of General Medical SciencesWellcome TrustWellcomeHoward Hughes Medical Institute
KeywordsChemistryArginineProtein arginine methyltransferase 5MethyltransferaseBiochemistryCell cultureEnzymeChemical biologyEpigeneticsEnzyme inhibitorStructure–activity relationshipIn vitroAmino acidMethylationBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Well-characterized selective inhibitors of protein arginine methyltransferases (PRMTs) are invaluable chemical tools for testing biological and therapeutic hypotheses. Based on 4, a fragment-like inhibitor of type I PRMTs, we conducted structure-activity relationship (SAR) studies and explored three regions of this scaffold. The studies led to the discovery of a potent, selective, and cell-active dual inhibitor of PRMT4 and PRMT6, 17 (MS049). As compared to 4, 17 displayed much improved potency for PRMT4 and PRMT6 in both biochemical and cellular assays. It was selective for PRMT4 and PRMT6 over other PRMTs and a broad range of other epigenetic modifiers and nonepigenetic targets. We also developed 46 (MS049N), which was inactive in biochemical and cellular assays, as a negative control for chemical biology studies. Considering possible overlapping substrate specificity of PRMTs, 17 and 46 are valuable chemical tools for dissecting specific biological functions and dysregulation of PRMT4 and PRMT6 in health and disease.

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.

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 score0.005
Threshold uncertainty score0.664

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 head0.005
GPT teacher head0.220
Teacher spread0.216 · 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