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Record W3196377280 · doi:10.1021/acschembio.1c00390

Development of a Benzothiazole Scaffold-Based Androgen Receptor N-Terminal Inhibitor for Treating Androgen-Responsive Prostate Cancer

2021· article· en· W3196377280 on OpenAlexaff
Nane C. Kuznik, Valeria Solozobova, Nicole Jung, Simone Gräßle, Qing Lei, Eric M. Lewandowski, Ravi S. N. Munuganti, Amina Zoubeidi, Yu Chen, Stefan Bräse, Andrew C.B. Cato

Bibliographic record

VenueACS Chemical Biology · 2021
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British Columbia
FundersDeutsche ForschungsgemeinschaftWilhelm Sander-StiftungProstate Cancer Foundation
KeywordsAndrogen receptorBenzothiazoleProstate cancerScaffoldAndrogenTerminal (telecommunication)ProstateChemistryCancer researchCancerEndocrinologyInternal medicineMedicineHormoneBiochemistryComputer science

Abstract

fetched live from OpenAlex

All current clinically approved androgen deprivation therapies for prostate cancer target the C-terminal ligand-binding domain of the androgen receptor (AR). However, the main transactivation function of the receptor is localized at the AR N-terminal domain (NTD). Targeting the AR NTD directly is a challenge because of its intrinsically disordered structure and the lack of pockets for drugs to bind. Here, we have taken an alternative approach using the cochaperone BAG1L, which interacts with the NTD, to develop a novel AR inhibitor. We describe the identification of 2-(4-fluorophenyl)-5-(trifluoromethyl)-1,3-benzothiazole (A4B17), a small molecule that inhibits BAG1L-AR NTD interaction, attenuates BAG1L-mediated AR NTD activity, downregulates AR target gene expression, and inhibits proliferation of AR-positive prostate cancer cells. This compound represents a prototype of AR antagonists that could be key in the development of future prostate cancer therapeutics.

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 score0.538

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 head0.030
GPT teacher head0.338
Teacher spread0.308 · 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

Citations16
Published2021
Admission routes1
Has abstractyes

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