2′,4′-Dihydroxy-6′‑methoxy-3′,5′-dimethylchalcone and its amino acid-conjugated derivatives induce G0/G1 cell cycle arrest and apoptosis via BAX/BCL2 ratio upregulation and in silico insight in SiHa cell lines
Bibliographic record
Abstract
We modified the chemical structure of 2′,4′-dihydroxy-6′‑methoxy-3′,5′-dimethylchalcone (DMC, 1), a phytochemical found in the seed of Syzygium nervosum A.Cunn. ex DC., by conjugation with the amino acid L-alanine (compound 3a) or L-valine (compound 3b) to enhance anticancer activity and water solubility. Compounds 3a and 3b had antiproliferative activity in human cervical cancer cell lines (C-33A, SiHa and HeLa), with half-maximal inhibitory concentrations (IC50) of 7.56 ± 0.27 and 8.24 ± 0.14 µM, respectively in SiHa cells; these values were approximately two-fold greater than DMC. We investigated the biological activities of compounds 3a and 3b based on a wound healing assay, a cell cycle assay and messenger RNA (mRNA) expression analysis to determine the possible mechanism of anticancer activity. Compounds 3a and 3b inhibited SiHa cell migration in the wound healing assay. After treatment with compounds 3a and 3b, there was an increase in SiHa cells in the G1 phase, indicative of cell cycle arrest. Moreover, compound 3a showed potential anticancer activity by upregulating TP53 and CDKN1A that resulted in upregulation of BAX and downregulation of CDK2 and BCL2, leading to apoptosis and cell cycle arrest. The BAX/BCL2 expression ratio was increased after treatment with compound 3a via the intrinsic apoptotic pathway. In silico molecular dynamics simulation and binding free energy calculation shed light on how these DMC derivatives interact with the HPV16 E6 protein, a viral oncoprotein associated with cervical cancer. Our findings suggest that compound 3a is a potential candidate for anti-cervical cancer drug development.
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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) | 0.001 | 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".