Alkaloid Synthesis: Penaresidin A (Subba Reddy), Allokainic Acid (Saicic), Sedacryptine (Rutjes), Lepistine (Yokoshima/Fukuyama), Septicine (Hanessian), Lyconadin C (Dai)
Bibliographic record
Abstract
Penaresidin A 3, isolated from the Okinawan marine sponge Penares sp., is a potent activator of actomyosin ATPase. B. V. Subba Reddy of the Indian Institute of Chemical Technology prepared (Tetrahedron Lett. 2014, 55, 49) the azetidine ring of 3 by mesylation of the hydroxy sulfonamide 2, derived from 1, followed by cyclization. Allokainic acid 6 has become a useful tool for neurological studies. Radomir N. Saicic of the University of Belgrade found (Org. Lett. 2014, 16, 34) that the Tsuji–Trost cyclization of 4 to 5 proceeded with high diastereoselectivity, presumably by way of the enamine of the aldehyde. Floris P. J. T. Rutjes of Radboud University Nijmegen prepared (Org. Lett. 2014, 16, 2038) the starting material 7 for (−)-sedacryptine 9 via an enantioselective Mannich addition. The reagent of choice for the Aza–Achmatowicz rearrangement of 7 to 8 proved to be mCPBA. The intriguing tricyclic alkaloid (−)-lepistine 12 was isolated from the mushroom Clitocybe fasciculate. En route to the first-ever synthesis of 12, Satoshi Yokoshima and Tohru Fukuyama of Nagoya University cyclized (Org. Lett. 2014, 16, 2862) the glycidol-derived sulfonamide 10 to the azacycle 11. (+)-Septicine 15 is the biogenetic precursor to the phenanthrene alkaloid (+)-tylophorine. Stephen Hanessian of the Université de Montréal prepared (Org. Lett. 2014, 16, 232) 15 by condensing the proline-derived ketone 13 with the aldehyde 14. Mingji Dai of Purdue University elaborated (Angew. Chem. Int. Ed. 2014, 53, 3922) the amine 16 to the enone 17 by intramolecular Mannich alkylation followed by methylenation and allylic oxidation. Condensation with the sulfoxide 18 then delivered lyconadin C 19.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.011 |
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".