Characterization of norbelladine synthase and noroxomaritidine/norcraugsodine reductase reveals a novel catalytic route for the biosynthesis of Amaryllidaceae alkaloids including the Alzheimer’s drug galanthamine
Bibliographic record
Abstract
ABSTRACT Amaryllidaceae alkaloids (AAs) are a large group of pharmacological plant-specialized metabolites. Norbelladine is the entry compound in AAs biosynthesis. Two enzymes are capable of catalyzing this reaction in-vitro , both with low-yield; 1) norbelladine synthase (NBS) condenses tyramine and 3,4-dihydroxybenzaldehyde, while 2) noroxomaritidine/norcraugsodine reductase (NR), catalyzes a reduction reaction. To clarify the mechanisms involved in this controversial step, both NBS and NR were characterized from Narcissus papyraceus and Leucojum aestivum . Assays with each enzyme suggested that NBS and NR function together for norbelladine formation. Using molecular-homology modeling and docking studies, we predicted models for the binding of substrates to NBS and NR. Moreover, NBS and NR physically interact, localize to the cell cytoplasm and nucleus and are expressed at high levels in bulbs. Our study establishes that both NBS and NR participate in the biosynthesis of norbelladine, catalyzing the first key steps involved in the biosynthesis of the Alzheimer’s drug galanthamine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".