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Record W2764046222 · doi:10.1002/anie.201706788

Discovery of a Highly Selective Cell‐Active Inhibitor of the Histone Lysine Demethylases KDM2/7

2017· article· en· W2764046222 on OpenAlexaff
Philip A. Gerken, Stephen Wolstenhulme, Anthony Tumber, Stephanie B. Hatch, Yijia Zhang, Susanne Müller, Shane A. Chandler, Barbara Mair, Fengling Li, Sebastian Nijman, Rebecca Konietzny, Tamás Szommer, Clarence Yapp, Oleg Fedorov, Justin L. P. Benesch, Masoud Vedadi, Benedikt M. Kessler, Akane Kawamura, Paul E. Brennan, Martin D. Smith

Bibliographic record

VenueAngewandte Chemie International Edition · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsStructural Genomics ConsortiumUniversity of Toronto
FundersBiotechnology and Biological Sciences Research CouncilEngineering and Physical Sciences Research CouncilNational Institute of General Medical SciencesWellcomeRoyal SocietyEuropean Research CouncilCancer Research UKWellcome Trust
KeywordsHistoneEpigeneticsChemical spaceLysineBiochemistrySmall moleculeChemical biologyChemistryDrug discoveryEnzymeBiologyGeneAmino acid

Abstract

fetched live from OpenAlex

Histone lysine demethylases (KDMs) are of critical importance in the epigenetic regulation of gene expression, yet there are few selective, cell-permeable inhibitors or suitable tool compounds for these enzymes. We describe the discovery of a new class of inhibitor that is highly potent towards the histone lysine demethylases KDM2A/7A. A modular synthetic approach was used to explore the chemical space and accelerate the investigation of key structure-activity relationships, leading to the development of a small molecule with around 75-fold selectivity towards KDM2A/7A versus other KDMs, as well as cellular activity at low micromolar concentrations.

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 score0.002

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.273
Teacher spread0.263 · 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

Citations43
Published2017
Admission routes1
Has abstractyes

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