Chemical Synthesis and Biological Activities of Amaryllidaceae Alkaloid Norbelladine Derivatives and Precursors
Bibliographic record
Abstract
Amaryllidaceae alkaloids (AAs) are a structurally diverse family of alkaloids recognized for their many therapeutic properties, such as antiviral, anti-cholinesterase, and anticancer properties. Norbelladine and its derivatives, whose biological properties are poorly studied, are key intermediates required for the biosynthesis of all ~650 reported AAs. To gain insight into their therapeutic potential, we synthesized a series of O-methylated norbelladine-type alkaloids and evaluated their cytotoxic effects on two types of cancer cell lines, their antiviral effects against the dengue virus (DENV) and the human immunodeficiency virus 1 (HIV-1), and their anti-Alzheimer’s disease (anti-cholinesterase and -prolyl oligopeptidase) properties. In monocytic leukemia cells, norcraugsodine was highly cytotoxic (CC50 = 27.0 μM), while norbelladine was the most cytotoxic to hepatocarcinoma cells (CC50 = 72.6 μM). HIV-1 infection was impaired only at cytotoxic concentrations of the compounds. The 3,4-dihydroxybenzaldehyde (selectivity index (SI) = 7.2), 3′,4′-O-dimethylnorbelladine (SI = 4.8), 4′-O-methylnorbelladine (SI > 4.9), 3′-O-methylnorbelladine (SI > 4.5), and norcraugsodine (SI = 3.2) reduced the number of DENV-infected cells with EC50 values ranging from 24.1 to 44.9 μM. The O-methylation of norcraugsodine abolished its anti-DENV potential. Norbelladine and its O-methylated forms also displayed butyrylcholinesterase-inhibition properties (IC50 values ranging from 26.1 to 91.6 μM). Altogether, the results provided hints of the structure−activity relationship of norbelladine-type alkaloids, which is important knowledge for the development of new inhibitors of DENV and butyrylcholinesterase.
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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) | 0.001 | 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 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".