Discovery of Small-Molecule Inhibitors Selectively Targeting the DNA-Binding Domain of the Human Androgen Receptor
Bibliographic record
Abstract
The human androgen receptor (AR) is considered as a master regulator in the development and progression of prostate cancer (PCa). As resistance to clinically used anti-AR drugs remains a major challenge for the treatment of advanced PCa, there is a pressing need for new anti-AR therapeutic avenues. In this study, we identified a binding site on the DNA binding domain (DBD) of the receptor and utilized virtual screening to discover a set of micromolar hits for the target. Through further exploration of the most potent hit (1), a structural analogue (6) was identified demonstrating 10-fold improved anti-AR potency. Further optimization resulted in a more potent synthetic analogue (25) with anti-AR potency comparable to a newly FDA-approved drug Enzalutamide. Site-directed mutagenesis demonstrated that the developed inhibitors do interact with the intended target site. Importantly, the AR DBD inhibitors could effectively inhibit the growth of Enzalutamide-resistant cells as well as block the transcriptional activity of constitutively active AR splice variants, such as V7.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".