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Record W2024469844 · doi:10.1073/pnas.1310658110

RVX-208, an inhibitor of BET transcriptional regulators with selectivity for the second bromodomain

2013· article· en· W2024469844 on OpenAlexfundno aff
S. Picaud, Christopher Wells, I. Felletar, Deborah H. Brotherton, Sarah Martin, P. Savitsky, Beatriz Díez-Dacal, Martin Philpott, C. Bountra, Hannah Lingard, O. Fedorov, Susanne Müller, Paul E. Brennan, Stefan Knapp, P. Filippakopoulos

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchWellcome TrustGlaxoSmithKlinePfizer
KeywordsBromodomainSelectivityChemistryBET inhibitorBiochemistryGeneEpigenetics

Abstract

fetched live from OpenAlex

Bromodomains have emerged as attractive candidates for the development of inhibitors targeting gene transcription. Inhibitors of the bromo and extraterminal (BET) family recently showed promising activity in diverse disease models. However, the pleiotropic nature of BET proteins regulating tissue-specific transcription has raised safety concerns and suggested that attempts should be made for domain-specific targeting. Here, we report that RVX-208, a compound currently in phase II clinical trials, is a BET bromodomain inhibitor specific for second bromodomains (BD2s). Cocrystal structures revealed binding modes of RVX-208 and its synthetic precursor, and fluorescent recovery after photobleaching demonstrated that RVX-208 displaces BET proteins from chromatin. However, gene-expression data showed that BD2 inhibition only modestly affects BET-dependent gene transcription. Our data demonstrate the feasibility of specific targeting within the BET family resulting in different transcriptional outcomes and highlight the importance of BD1 in transcriptional regulation.

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)0.0010.000

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 head0.020
GPT teacher head0.264
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 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

Citations481
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicProtein Degradation and InhibitorsFrench-language works237,207