A New Class of BRCA1 Mimetics for ERα-Positive Breast Cancer Therapy: Design, Synthesis, In Silico Screening, In Vitro Assay, and Gene Expression Analysis
Bibliographic record
Abstract
Breast Cancer Gene 1 (BRCA1) offers a potential approach for ERα repression by blocking cyclin D1’s interaction with ERα, which prevents cells from growing and dividing too rapidly or uncontrollably. When BRCA1 levels are low, BRCA1 mimetics fit into the BRCA1-binding pocket within ERα, mimicking the ability of BRCA1 to inhibit ERα activity. This study aims to identify a novel class of lead molecules for BRCA1 mimetics for ER-positive breast cancer, distinct from conventional antiestrogen therapies in their mechanism of action. In this article, coumarin thiosemicarbazone hybrids were synthesized from 7-hydroxy 4-methyl coumarin/4-hydroxy coumarin and thiosemicarbazide with different aldehydes and evaluated for their ERα repression activity. The most active compounds in the series, 9b, 9l, and 9m, exhibited significant potency with an IC50 value of 14.49 µM, 35.08 µM and 42.12 µM, respectively, compared to raloxifene (reported) as the positive control with an IC50 value of 13.7 µM. The gene expression study confirmed the downregulation of the cyclin D1 gene for the compounds 9l (−0.217) and 9m (−0.214). Similarly, the downregulation of the BCL2 gene for the compounds 9b (−0.373), 9l (−0.320), and 9m (−0.376). Also, molecular docking studies and MMGBSA were performed to determine key interactions between compounds and ERα at the BRCA1 binding pocket (AA 338–387). In silico, ADMET properties were executed to illustrate the druggability and safety of the novel derivatives. In silico, in vitro, and gene expression studies revealed that among all the compounds, 9b, 9l, and 9m are promising candidates for the development of lead molecules targeting ERα inhibitors for breast cancer treatment. Moreover, the concept of ERα repression with small molecules as BRCA1 mimetics is novel. In general, it can be concluded that these compounds can serve as promising leads to the design of potential BRCA1 mimetics.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".