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Record W4406971399 · doi:10.1021/acs.jmedchem.4c02225

Discovery, Optimization, and Preclinical Pharmacology of EP652, a METTL3 Inhibitor with Efficacy in Liquid and Solid Tumor Models

2025· article· en· W4406971399 on OpenAlexaff
Guillaume Dutheuil, Killian Oukoloff, Julien Korac, François Lenoir, Mohamed El Bousmaqui, Nicolas Probst, Alexey Lapin, Galina Nakhabina, Catherine Sorlet, Nicolas Parmentier, Delphine Karila, Nugzar Ghavtadze, Paméla Casault, Stephen Claridge, Selma Sapmaz, Martin J. Slater, Graeme L. Fraser

Bibliographic record

VenueJournal of Medicinal Chemistry · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsParaza Pharma (Canada)
FundersWaalse Gewest
KeywordsChemistryPharmacologySolid tumorInternal medicineCancerMedicine

Abstract

fetched live from OpenAlex

METTL3 is the RNA methyltransferase predominantly responsible for the addition of N 6 -methyladenosine (m 6 A), the most abundant modification to mRNA. The prevalence of m 6 A and the activity and expression of METTL3 have been linked to the appearance and progression of acute myeloid leukemia (AML), thereby making METTL3 an attractive target for cancer therapeutics. We report herein the discovery and optimization of small-molecule inhibitors of METTL3, culminating in the selection of EP652 as an in vivo proof-of-concept compound. EP652 potently inhibits the enzymatic activity of METTL3, has favorable PK parameters, and demonstrates efficacy in preclinical oncology models, indicating that pharmacological inhibition of METTL3 is a viable strategy for the treatment of liquid and solid tumors.

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 score0.009
Threshold uncertainty score0.274

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 head0.010
GPT teacher head0.310
Teacher spread0.300 · 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

Citations22
Published2025
Admission routes1
Has abstractyes

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