A Novel Benzopyrane Derivative Targeting Cancer Cell Metabolic and Survival Pathways
Bibliographic record
Abstract
(1) Background: Today, the discovery of novel anticancer agents with multitarget effects and high safety margins represents a high challenge. Drug discovery efforts indicated that benzopyrane scaffolds possess a wide range of pharmacological activities. This spurs on building a skeletally diverse library of benzopyranes to identify an anticancer lead drug candidate. Here, we aim to characterize the anticancer effect of a novel benzopyrane derivative, aiming to develop a promising clinical anticancer candidate. (2) Methods: The anticancer effect of SIMR1281 against a panel of cancer cell lines was tested. In vitro assays were performed to determine the effect of SIMR1281 on GSHR, TrxR, mitochondrial metabolism, DNA damage, cell cycle progression, and the induction of apoptosis. Additionally, SIMR1281 was evaluated in vivo for its safety and in a xenograft mice model. (3) Results: SIMR1281 strongly inhibits GSHR while it moderately inhibits TrxR and modulates the mitochondrial metabolism. SIMR1281 inhibits the cell proliferation of various cancers. The antiproliferative activity of SIMR1281 was mediated through the induction of DNA damage, perturbations in the cell cycle, and the inactivation of Ras/ERK and PI3K/Akt pathways. Furthermore, SIMR1281 induced apoptosis and attenuated cell survival machinery. In addition, SIMR1281 reduced the tumor volume in a xenograft model while maintaining a high in vivo safety profile at a high dose. (4) Conclusions: Our findings demonstrate the anticancer multitarget effect of SIMR1281, including the dual inhibition of glutathione and thioredoxin reductases. These findings support the development of SIMR1281 in preclinical and clinical settings, as it represents a potential lead compound for the treatment of cancer.
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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 | 0.000 |
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 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".