Binary and ternary crystal structure analyses of a novel inhibitor with 17β-HSD type 1: a lead compound for breast cancer therapy
Bibliographic record
Abstract
Oestradiol is a well-characterized sex hormone that stimulates breast cancer and other oestrogen-related diseases. 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) catalyses the last step in the synthesis of oestradiol and androstenediol in breast tumour tissue. The enzyme's high expression and activity after simultaneous blockade of oestrogen receptors and inhibition of aromatase in the tumour shows the necessity for its inhibition as a requirement for breast cancer therapy. In the present paper, we report structures of the binary and ternary complexes of 17beta-HSD1 with a new inhibitor E2B {3-[3',17'beta-dihydroxyestra-1',3',5'(10')-trien-16'beta-methyl]benzamide}, and the enzyme inhibition by the later. The IC50 value for E2B was determined to be 42 nM in T47D cells. Multiple interactions between E2B and the enzyme include hydrogen bonds and hydrophobic interactions, as well as pi-pi interactions. A kinetic study demonstrated that E2B inhibits the enzyme's reduction forming oestradiol from oestrone, with a Ki of 0.9+/-0.15 nM. Such strong inhibition is in agreement with its extensive interaction with the enzyme, suggesting its potential as a lead compound for breast cancer therapy. In fact, this possibility is enhanced by its capacity for cell penetration similar to natural steroids. Such inhibitors that block oestrogen synthesis to suppress the sulfatase pathway producing oestradiol can be used in adjuvant therapies with oestrogen receptor blockade, opening a new orientation of breast cancer treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".