Targeting Binding Function-3 of the Androgen Receptor Blocks Its Co-Chaperone Interactions, Nuclear Translocation, and Activation
Bibliographic record
Abstract
The development of new antiandrogens, such as enzalutamide, or androgen synthesis inhibitors like abiraterone has improved patient outcomes in the treatment of advanced prostate cancer. However, due to the development of drug resistance and tumor cell survival, a majority of these patients progress to the refractory state of castration-resistant prostate cancer (CRPC). Thus, newer therapeutic agents and a better understanding of their mode of action are needed for treating these CRPC patients. We demonstrated previously that targeting the Binding Function 3 (BF3) pocket of the androgen receptor (AR) has great potential for treating patients with CRPC. Here, we explore the functional activity of this site by using an advanced BF3-specific small molecule (VPC-13566) that was previously reported to effectively inhibit AR transcriptional activity and to displace the BAG1L peptide from the BF3 pocket. We show that VPC-13566 inhibits the growth of various prostate cancer cell lines, including an enzalutamide-resistant cell line, and reduces the growth of AR-dependent prostate cancer xenograft tumors in mice. Importantly, we have used this AR-BF3 binder as a chemical probe and identified a co-chaperone, small glutamine-rich tetratricopeptide repeat (TPR)-containing protein alpha (SGTA), as an important AR-BF3 interacting partner. Furthermore, we used this AR-BF3-directed small molecule to demonstrate that inhibition of AR activity through the BF3 functionality can block translocation of the receptor into the nucleus. These findings suggest that targeting the BF3 site has potential clinical importance, especially in the treatment of CRPC and provide novel insights on the functional role of the BF3 pocket. Mol Cancer Ther; 15(12); 2936-45. ©2016 AACR.
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 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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".