Chemical Synthesis and Biological Evaluation of 3-Substituted Estrone/Estradiol Derivatives as 17β-Hydroxysteroid Dehydrogenase Type 1 Inhibitors Acting via a Reverse Orientation of the Natural Substrate Estrone
Bibliographic record
Abstract
Estradiol (E2) plays an important role in the progression of diseases such as breast cancer and endometriosis. Inhibition of 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1), the enzyme that catalyzes the last step in the biosynthesis of the estrogenic hormone E2, therefore constitutes an interesting approach for the treatment of these two estrogen-dependent diseases. In order to obtain new inhibitors of 17β-HSD1, the impact of a m-carbamoylphenyloxy group at position three of an estrane nucleus was evaluated by preparing three derivatives of estrone (E1) and E2 using a microwave-assisted synthesis of diaryl ethers. Their inhibitory activity was addressed on two cell lines (T-47D and Z-12) representative of breast cancer and endometriosis, respectively, but unlike T-47D cells, Z-12 cells were not found suitable for testing potential 17β-HSD1 inhibitors. Thus, the addition of the m-carbamoylphenyl group at C3 of E1 (compound 5) did not increase the inhibition of E1 to E2 transformation by 17β-HSD1 present in T-47D cells (IC50 = 0.31 and 0.21 μM for 5 and E1, respectively), and this negative effect was more obvious for E2 derivatives 6 and 10 (IC50 = 1.2 and 1.3 μM, respectively). Molecular docking allowed us to identify key interactions with 17β-HSD1 and to highlight these new inhibitors’ actions through an opposite orientation than natural enzyme substrate E1′s classical one. Furthermore, molecular modeling experiments explain the better inhibitory activity of E1-ether derivative 5, as opposed to the E2-ether derivatives 6 and 10. Finally, when tested on T-47D and Z-12 cells, compounds 5, 6 and 10 did not stimulate the proliferation of these two estrogen-dependent cell lines. In fact, they reduced it.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".