Identification of Novel Androgen Receptor Antagonists Using Structure- and Ligand-Based Methods
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.
Bibliographic record
Abstract
Androgen receptor (AR) plays a critical role in the development and progression of prostate cancer (PCa). The AR hormone-binding site (HBS) is intensively studied and represents the target area for current antiandrogens including Bicalutamide and structurally related Enzalutamide. As resistance to antiandrogens invariably emerges in advanced prostate cancer, there exists a high medical need for the identification and development of novel AR antagonists of different chemotypes. Given the wealth of structural information on the AR in complex with a variety of ligands, we have applied an integrated structure- and ligand-based virtual screening methodology to identify novel AR antagonists. Virtual hits generated by a consensus voting approach were experimentally evaluated and resulted in the discovery of a number of structurally diverse submicromolar antagonists of the AR. In particular, one identified compound demonstrated anti-AR potency in vitro that is comparable to the clinically used Bicalutamide. These results set a ground for the development of novel classes of PCa drugs that are structurally different from current AR antagonists.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it