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Record W3109714884 · doi:10.1101/2020.12.04.412569

A First-in-class, Highly Selective and Cell-active Allosteric Inhibitor of Protein Arginine Methyltransferase 6 (PRMT6)

2020· preprint· en· W3109714884 on OpenAlexafffund
Yudao Shen, Fengling Li, Magdalena M. Szewczyk, Levon Halebelian, Irene Chau, Mohammad S. Eram, Carlo dela Seña, Kwang‐Su Park, Fanye Meng, He Chen, Hong Zeng, David McLeod, Carlos Zepeda‐Velázquez, Robert M. Campbell, Mary M. Mader, Brian M. Watson, Matthieu Schapira, C.H. Arrowsmith, Rima Al‐awar, Dalia Baršytė-Lovejoy, H. Ümit Kanıskan, Peter J. Brown, Masoud Vedadi, Jian Jin

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsStructural Genomics ConsortiumOntario Institute for Cancer ResearchUniversity of Toronto
FundersOntario GenomicsNational Institutes of HealthOntario Ministry of Research, Innovation and ScienceFundação de Amparo à Pesquisa do Estado de São PauloGenome CanadaEli Lilly and CompanyIcahn School of Medicine at Mount SinaiPfizerNovartis PharmaOntario Genomics InstituteEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaA
KeywordsAllosteric regulationMethyltransferaseChemistryAllosteric modulatorEnzymeEnantiomerArginineEpigeneticsBiochemistryMethylationStereochemistryAmino acidGene

Abstract

fetched live from OpenAlex

Abstract PRMT6 catalyzes monomethylation and asymmetric dimethylation of arginine residues in various proteins, plays important roles in biological processes and is associated with multiple cancers. While there are several reported PRMT6 inhibitors, a highly selective PRMT6 inhibitor has not been reported to date. Furthermore, allosteric inhibitors of protein methyltransferases are rare. Here we report the discovery and characterization of a first-in-class, highly selective allosteric inhibitor of PRMT6, SGC6870. SGC6870 is a potent PRMT6 inhibitor (IC 50 = 77 ± 6 nM) with outstanding selectivity for PRMT6 over a broad panel of other methyltransferases and non-epigenetic targets. Notably, the crystal structure of the PRMT6–SGC6870 complex and kinetic studies revealed SGC6870 binds a unique, induced allosteric pocket. Additionally, SGC6870 engages PRMT6 and potently inhibits its methyltransferase activity in cells. Moreover, SGC6870’s enantiomer, SGC6870N, is inactive against PRMT6 and can be utilized as a negative control. Collectively, SGC6870 is a well-characterized PRMT6 chemical probe and valuable tool for further investigating PRMT6 functions 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.

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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicCancer-related gene regulationFrench-language works237,207