MétaCan
Menu
Back to cohort
Record W2156169240 · doi:10.1186/s13058-015-0529-8

In silico discovery and validation of potent small-molecule inhibitors targeting the activation function 2 site of human oestrogen receptor α

2015· article· en· W2156169240 on OpenAlexafffund
Kriti Singh, Ravi S. N. Munuganti, Eric Leblanc, Yu Lun Lin, Euphemia Leung, Nada Lallous, Miriam Butler, Artem Cherkasov, Paul S. Rennie

Bibliographic record

VenueBreast Cancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsUniversity of British Columbia
FundersFaculty of Medical and Health Sciences, University of AucklandCanadian Cancer Society Research Institute
KeywordsCoactivatorIn silicoHeLaEstrogen receptor alphaCancer researchSmall moleculeEstrogen receptorBiologyChemistryMolecular biologyIn vitroTranscription factorBiochemistryCancerGeneBreast cancerGenetics

Abstract

fetched live from OpenAlex

INTRODUCTION: Current approaches to inhibit oestrogen receptor-alpha (ERα) are focused on targeting its hormone-binding pocket and have limitations. Thus, we propose that inhibitors that bind to a coactivator-binding pocket on ERα, called activation function 2 (AF2), might overcome some of these limitations. METHODS: In silico virtual screening was used to identify small-molecule ERα AF2 inhibitors. These compounds were screened for inhibition of ERα transcriptional activity using stably transfected T47D-KBluc cell line. A direct physical interaction between the AF2 binders and the ERα protein was measured using biolayer interferometry (BLI) and an ERα coactivator displacement assay. Cell viability was assessed by MTS assay in ERα-positive MCF7 cells, tamoxifen-resistant (TamR) cell lines TamR3 and TamR6, and ERα-negative MDA-MB-453 and HeLa cell lines. In addition, ERα inhibition in TamR cells and the effect of compounds on mRNA and protein expression of oestrogen-dependent genes, pS2, cathepsin D and cell division cycle 2 (CDC2) were determined. RESULTS: Fifteen inhibitors from two chemical classes, derivatives of pyrazolidine-3,5-dione and carbohydrazide, were identified. In a series of in vitro assays, VPC-16230 of the carbohydrazide chemical class emerged as a lead ERα AF2 inhibitor that significantly downregulated ERα transcriptional activity (half-maximal inhibitory concentration = 5.81 μM). By directly binding to the ERα protein, as confirmed by BLI, VPC-16230 effectively displaced coactivator peptides from the AF2 pocket, confirming its site-specific action. VPC-16230 selectively suppressed the growth of ERα-positive breast cancer cells. Furthermore, it significantly inhibited ERα mediated transcription in TamR cells. More importantly, it reduced mRNA and protein levels of pS2, cathepsin D and CDC2, validating its ER-directed activity. CONCLUSION: We identified VPC-16230 as an ERα AF2-specific inhibitor that demonstrated promising antiproliferative effects in breast cancer cell lines, including TamR cells. VPC-16230 reduced the expression of ERα-inducible genes, including CDC2, which is involved in cell division. We anticipate that the application of ERα AF2 inhibitors will provide a novel approach that can act as a complementary therapeutic to treat ERα-positive, tamoxifen-resistant and metastatic breast cancers.

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)0.001
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 score0.012
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.315
Teacher spread0.290 · 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

Citations24
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueBreast Cancer ResearchSame topicEstrogen and related hormone effectsFrench-language works237,207