Exploring the Structural Diversity of Novel 3-Substituted Coumarins as Potent Inhibitors of Tumor-Associated Carbonic Anhydrases: Expanding the Pharmacological Space for Anticancer Drug Discovery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Innovations in cancer chemotherapy continue to occupy the priority list of demands to ensure our health security. The vast chemical space provides a plethora of anticancer discovery opportunities, however, limited by the boundaries of synthetic feasibility. Objective Expand the established pharmacological space of tumor-associated carbonic anhydrases by exploring the synthetically feasible chemical space of 3-substituted coumarins. Method A series of 52 novel 3-substituted coumarins were randomly sketched by our team of synthetic chemists with priority given to synthetic feasibility. The pharmacological potentials of the novel coumarin series were computationally estimated using a machine-learning approach exploiting both chemical and statistical inference. 17 members of the novel series were predicted to possess cytotoxic activity against HeLa cells by interfering with the tumor-associated carbonic anhydrases IX and XII. Those 17 compounds were synthesized and biologically tested against HeLa cells, subsequently; the 3 most potent compounds were assayed against carbonic anhydrases I, II, IX, and XII employing Acetazolamide as a reference. The molecular binding mechanism of those 3 chosen compounds with the four enzyme isoforms was studied using molecular docking simulation. Result Most of the compounds exhibited competent inhibitory activity against HeLa cells. The carbonic anhydrase inhibition results unveiled the powerful but non-selective nature of those suicide inhibitors. Conclusion Novel 3-substituted coumarins have been dispatched to join the pharmacological space of tumor-associated carbonic anhydrases’ suicide inhibitors.
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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 | 0.001 |
| 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 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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 it