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Record W2900804033 · doi:10.1002/anie.201810179

Design, Synthesis and Characterization of Covalent KDM5 Inhibitors

2018· article· en· W2900804033 on OpenAlexfundno aff
Saleta Vázquez-Rodríguez, Miranda Wright, Catherine Rogers, Adam P. Cribbs, Srikannathasan Velupillai, Martin Philpott, Henry Lee, James E. Dunford, K. Huber, Matthew B. Robers, James D. Vasta, Marie‐Laetitia Thezenas, Sarah Bonham, Benedikt M. Kessler, James M. Bennett, Oleg Fedorov, Florence I. Raynaud, Adam Donovan, Julian Blagg, Vassilios Bavetsias, Udo Oppermann, C. Bountra, Akane Kawamura, Paul E. Brennan

Bibliographic record

VenueAngewandte Chemie International Edition · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersFP7 People: Marie-Curie ActionsH2020 Marie Skłodowska-Curie ActionsEngineering and Physical Sciences Research CouncilInnovative Medicines InitiativeArthritis Research UKRosetrees TrustVersus ArthritisMinistero dello Sviluppo EconomicoGenome CanadaFundação de Amparo à Pesquisa do Estado de São PauloCancer Research UKWellcome TrustEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaANational Institute for Health and Care ResearchPfizer
KeywordsChemistryH3K4me3Covalent bondHistoneBiochemistryCysteineGene expressionLysineGeneCell biologyBiologyEnzymePromoterAmino acid

Abstract

fetched live from OpenAlex

Histone lysine demethylases (KDMs) are involved in the dynamic regulation of gene expression and they play a critical role in several biological processes. Achieving selectivity over the different KDMs has been a major challenge for KDM inhibitor development. Here we report potent and selective KDM5 covalent inhibitors designed to target cysteine residues only present in the KDM5 sub-family. The covalent binding to the targeted proteins was confirmed by MS and time-dependent inhibition. Additional competition assays show that compounds were non 2-OG competitive. Target engagement and ChIP-seq analysis showed that the compounds inhibited the KDM5 members in cells at nano- to micromolar levels and induce a global increase of the H3K4me3 mark at transcriptional start sites.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.015
GPT teacher head0.253
Teacher spread0.238 · 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
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

Citations31
Published2018
Admission routes1
Has abstractyes

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