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Record W2515987897 · doi:10.1039/c6md00373g

Chemical probes and inhibitors of bromodomains outside the BET family

2016· review· en· W2515987897 on OpenAlexafffund
Moses Moustakim, Peter G. K. Clark, Duncan A. Hay, Darren J. Dixon, Paul E. Brennan

Bibliographic record

VenueMedChemComm · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsBurnaby HospitalSimon Fraser University
FundersNovartis PharmaWoolf Fisher TrustMinistero dello Sviluppo EconomicoGenome CanadaFundação de Amparo à Pesquisa do Estado de São PauloUniversity of CambridgeUniversity of OxfordOntario Ministry of Economic Development and InnovationWellcome TrustEuropean Federation of Pharmaceutical Industries and AssociationsWellcomeSimon Fraser UniversityEngineering and Physical Sciences Research CouncilAstraZenecaPfizer
KeywordsBromodomainAcetylationEpigeneticsLysineComputational biologyChemistryBiologyBiochemistryAmino acidGene

Abstract

fetched live from OpenAlex

In the last five years, the development of inhibitors of bromodomains has emerged as an area of intensive worldwide research. Emerging evidence has implicated a number of non-BET bromodomains in the onset and progression of diseases such as cancer, HIV infection and inflammation. The development and use of small molecule chemical probes has been fundamental to pre-clinical evaluation of bromodomains as targets. Recent efforts are described highlighting the development of potent, selective and cell active non-BET bromodomain inhibitors and their therapeutic potential. Over half of typical bromodomains now have reported ligands, but those with atypical binding site residues remain resistant to chemical probe discovery efforts.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.023
GPT teacher head0.292
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations57
Published2016
Admission routes2
Has abstractyes

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