Cytotoxic and Anti-Plasmodial Activities of Stephania dielsiana Y.C. Wu Extracts and the Isolated Compounds
Bibliographic record
Abstract
Natural products remain a viable source of novel therapeutics, and as detection and extraction techniques improve, we can identify more molecules from a broader set of plant tissues. The aim of this study was an investigation of the cytotoxic and anti-plasmodial activities of the methanol extract from Stephania dielsiana Y.C. Wu leaves and its isolated compounds. Our study led to the isolation of seven alkaloids, among which oxostephanine (1) is the most active against several cancer cell lines including HeLa, MDA-MB231, MDA-MB-468, MCF-7, and non-cancer cell lines, such as 184B5 and MCF10A, with IC50 values ranging from 1.66 to 4.35 μM. Morever, oxostephanine (1) is on average two-fold more active against cancer cells than stephanine (3), having a similar chemical structure. Cells treated with oxostephanine (1) are arrested at G2/M cell cycle, followed by the formation of aneuploidy and apoptotic cell death. The G2/M arrest appears to be due, at least in part, to the inactivation of Aurora kinases, which is implicated in the onset and progression of many forms of human cancer. An in-silico molecular modeling study suggests that oxostephanine (1) binds to the ATP binding pocket of Aurora kinases to inactivate their activities. Unlike oxostephanine (1), thailandine (2) is highly effective against only the triple-negative MDA-MB-468 breast cancer cells. However, it showed excellent selectivity against the cancer cell line when compared to its effects on non-cancer cells. Furthermore, thailandine (2) showed excellent anti-plasmodial activity against both chloroquine-susceptible 3D7 and chloroquine-resistant W2 Plasmodium falciparum strains. The structure–activity relationship of isolated compound was also discussed in this study. The results of this study support the traditional use of Stephania dielsiana Y.C. Wu and the lead molecules identified can be further optimized for the development of highly effective and safe anti-cancer and anti-plasmodial drugs.
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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 | 0.000 | 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) | 0.000 | 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".