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Record W1981652396 · doi:10.1021/jm200532b

Inhibitors of Androgen Receptor Activation Function-2 (AF2) Site Identified through Virtual Screening

2011· article· en· W1981652396 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Medicinal Chemistry · 2011
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryAndrogen receptorVirtual screeningAndrogenFunction (biology)ReceptorPharmacologyEndocrinologyInternal medicineBiochemistryCell biologyDrug discoveryHormoneProstate cancer

Abstract

fetched live from OpenAlex

The androgen receptor (AR) is one of the most studied drug targets for the treatment of prostate cancer. However, all current anti-androgens directly interact with the AR at the androgen binding site, which is prone to resistant mutations, calling for new strategies of the AR inhibition. The current study represents the first attempt to use virtual screening to identify inhibitors of activation function-2 (AF2) of the human AR. By combining large-scale docking with experimental approaches, we were able to identify several small molecules that interact with the AF2 and effectively prevent the transcriptional activation of the AR. The crystallographic structure of one of these inhibitors in complex with the AR provides critical insight into the corresponding protein-ligand interactions and suitable for future hit optimization. Taken together, our results provide a promising ground for development of novel anti-androgens that can help to address the problem of drug resistance in prostate cancer.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.044
Threshold uncertainty score1.000

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)0.0010.000

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 head0.048
GPT teacher head0.301
Teacher spread0.253 · 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