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Chemical Biology of Lysine Demethylases

2011· article· en· W53169776 on OpenAlexfundno aff
Tom D. Heightman

Bibliographic record

VenueCurrent Chemical Genomics · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersKnut och Alice Wallenbergs StiftelseKarolinska InstitutetStiftelsen för Strategisk ForskningOntario Genomics InstituteOntario GenomicsGenome CanadaOntario Innovation TrustWellcome TrustGlaxoSmithKline
KeywordsBiologyHistoneEpigeneticsMethylationChromatinComputational biologyDrug discoveryDNA methylationLysinePRC2GeneGeneticsGene expressionHistone H3BioinformaticsAmino acid

Abstract

fetched live from OpenAlex

Abnormal levels of DNA methylation and/or histone modifications are observed in patients with a wide variety of chronic diseases. Methylation of lysines within histone tails is a key modification that contributes to increased gene expression or repression depending on the specific residue and degree of methylation, which is in turn controlled by the interplay of lysine methyl transferases and demethylases. Drugs that target these and other enzymes controlling chromatin modifications can modulate the expression of clusters of genes, potentially offering higher therapeutic efficacy than classical agents acting on downstream biochemical pathways that are susceptible to degeneracy. Lysine demethylases, first discovered in 2004, are the subject of increasing interest as therapeutic targets. This review provides an overview of recent findings implicating lysine demethylases in a range of therapeutic areas including oncology, immunoinflammation, metabolic disorders, neuroscience, virology and regenerative medicine, together with a summary of recent advances in structural biology and small molecule inhibitor discovery, supporting the tractability of the protein family for the development of selective druglike inhibitors.

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 score0.033
Threshold uncertainty score0.608

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 head0.043
GPT teacher head0.287
Teacher spread0.244 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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