A Challenge for Medicinal Chemistry by the 17β-hydroxysteroid Dehydrogenase Superfamily: An Integrated Biological Function and Inhibition Study
Bibliographic record
Abstract
Members of the 17β-hydroxysteroid dehydrogenase (17β-HSD) superfamily perform distinct multiple catalyses by the same enzyme, apparently contradictory to the long-held beliefs regarding the high specificity of enzymes. Surprisingly, these multi-catalyses can combine synergistically in vitro and in vivo and their dysfunction may result in the stimulation of breast or prostate cancer. 17β-HSD1 possesses high estrogen activation activity, while its androgen inactivation is significant for decreasing the week concentration of dihydrotestosterone (DHT) in breast cancer cells, an important factor for cell proliferation. 17β-HSD5 can also carry out multiple catalyses in hormone-dependent cancer cells. In addition to 17β-HSDs 1 and 5 some other family members possess such dual-activity as well, and their inhibition decreases hormone- dependent cancer proliferation. The multi-specificity of 17β-HSD1 is structurally based on the pseudo-symmetric androgens that can accommodate the narrow enzyme substrate tunnel by both normal and alternative binding. The atypical family member 17β-HSD5 possesses a spacious binding site, which is accessible to several substrates. Expression of 17β- HSD1 can also control other estrogen-responsive elements such as pS2, and can regulate steroid-hormone receptors. The fundamental involvement of 17β-HSD1 in catalysis and gene regulation underlies its close relationship to breast cancer, attributable to its long evolutionary process. These observations stimulated detailed study of steroid-converting enzyme inhibition. The most significant efforts in designing 17β-HSD1 inhibitors in decades have progressed through structure activity relationship studies supported by the availability of both small and protein molecule structures, with the elimination of residual estrogenic activity in the inhibitors. The first non-estrogenic inhibitors of 17β-HSD1 to show activity in vivo (breast cancer animal model) are now reported.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".