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Record W3025143058 · doi:10.1038/s41467-020-16271-z

Pharmacological inhibition of PRMT7 links arginine monomethylation to the cellular stress response

2020· article· en· W3025143058 on OpenAlexafffund
Magdalena M. Szewczyk, Yoshinori Ishikawa, Shawna Organ, Nozomu Sakai, Fengling Li, Levon Halabelian, Suzanne Ackloo, Amber L. Couzens, Mohammad S. Eram, David Dilworth, Hideto Fukushi, Rachel Harding, Carlo C. dela Seña, Tsukasa Sugo, Kôzô Hayashi, David McLeod, Carlos Zepeda, Ahmed Aman, María Sánchez‐Osuna, Éric Bonneil, Shinji Takagi, Rima Al‐awar, Mike Tyers, Stéphane Richard, Masayuki Takizawa, Anne‐Claude Gingras, C.H. Arrowsmith, Masoud Vedadi, Peter J. Brown, Hiroshi Nara, Dalia Baršytė-Lovejoy

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsPrincess Margaret Cancer CentreMcGill UniversityUniversité de MontréalInstitute for Research in Immunology and CancerLunenfeld-Tanenbaum Research InstituteStructural Genomics ConsortiumOntario Institute for Cancer ResearchUniversity of Toronto
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchOffice of ScienceStand Up To CancerNovartis PharmaOntario Genomics InstituteGovernment of CanadaOntario Institute for Cancer ResearchWellcome TrustNational Institutes of HealthOntario Ministry of Research, Innovation and ScienceOntario GenomicsOffice of Research Infrastructure Programs, National Institutes of HealthFundação de Amparo à Pesquisa do Estado de São PauloGenome CanadaPfizerGovernment of OntarioAmerican Association for Cancer ResearchEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAArgonne National LaboratoryU.S. Department of Energy
KeywordsProtein arginine methyltransferase 5MethylationArginineHsp70MethyltransferaseCell biologyProteostasisHeat shock proteinBiologyIn vitroProdrugChemistryBiochemistryAmino acidDNAGene

Abstract

fetched live from OpenAlex

Protein arginine methyltransferases (PRMTs) regulate diverse biological processes and are increasingly being recognized for their potential as drug targets. Here we report the discovery of a potent, selective, and cell-active chemical probe for PRMT7. SGC3027 is a cell permeable prodrug, which in cells is converted to SGC8158, a potent, SAM-competitive PRMT7 inhibitor. Inhibition or knockout of cellular PRMT7 results in drastically reduced levels of arginine monomethylated HSP70 family stress-associated proteins. Structural and biochemical analyses reveal that PRMT7-driven in vitro methylation of HSP70 at R469 requires an ATP-bound, open conformation of HSP70. In cells, SGC3027 inhibits methylation of both constitutive and inducible forms of HSP70, and leads to decreased tolerance for perturbations of proteostasis including heat shock and proteasome inhibitors. These results demonstrate a role for PRMT7 and arginine methylation in stress response.

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 score0.158
Threshold uncertainty score0.303

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 integrity0.0000.001
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 head0.022
GPT teacher head0.306
Teacher spread0.284 · 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

Citations108
Published2020
Admission routes2
Has abstractyes

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