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Abstract A005: A live cell PRMT5 NanoBRET™ target engagement assay querying competitive and uncompetitive modes of inhibition

2024· article· en· W4399505093 on OpenAlexaboutno aff
Kelly A. Teske, Ani Michaud, Elisabeth M. Rothweiler, Cesear Corona, Kaitlin Dunn Hoffman, Jennifer Wilkinson, Michael Beck, James D. Vasta, K. Huber, Matthew B. Robers

Bibliographic record

VenueMolecular Cancer Therapeutics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsnot available
Fundersnot available
KeywordsProtein arginine methyltransferase 5Uncompetitive inhibitorMethylationMethyltransferaseChemistryBiochemistryNon-competitive inhibitionEnzymeCell biologyBiologyDNA

Abstract

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Abstract PRMT5 is an essential arginine methyltransferase that regulates a wide spectrum of cellular processes through the methylation of histone and non-histone substrates. In PRMT5 catalysis, SAM serves as the cofactor and methyl group donor, generating a methylated guanidinium moiety on the target substrate. In normal cells, the SAM pools are maintained through the methionine salvage pathway. In 15% of cancers, a key enzyme in this pathway (MTAP) is deleted, leading to an accumulation of the intermediate MTA, which inhibits PRMT5 activity. This genetic loss of function has therefore been pursued as a collateral vulnerability in MTAP deleted cancers. To exploit this synthetic lethality, a number of novel inhibitors (such as MRTX1719) have been developed that bind cooperatively at the PRMT5/MTA complex, offering a compelling pathway to precision medicine. Here we describe a novel, live cell NanoBRET™ Target Engagement assay that enables mechanistic studies on a variety of PRMT5 inhibitors. Using a cell-permeable NanoBRET probe directed to the substrate pocket of PRMT5, both substrate- and cofactor-competitive engagement can be quantified in cells. Moreover, this method can be used to quantify MTA-uncompetitive target engagement in cells, providing a platform to measure the potency of PRMT5-MTA-drug ternary complex formation. This method serves as a first-in-class method to quantify uncompetitive target engagement in live cells, which can be applied to other model systems. Citation Format: Kelly A. Teske, Ani Michaud, Elisabeth Rothweiler, Cesear Corona, Kaitlin Dunn Hoffman, Jennifer Wilkinson, Michael Beck, James Vasta, Kilian Huber, Matthew Robers. A live cell PRMT5 NanoBRET™ target engagement assay querying competitive and uncompetitive modes of inhibition [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr A005.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.014
GPT teacher head0.265
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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