Glycomimetics: A Programmed Approach toward Neoglycopeptide Libraries<sup>1a</sup>
Bibliographic record
Abstract
A programmed synthesis of neoglycopeptides has been developed in which two, similar or different, glycoside moieties could be attached either (i) at the N-terminal of short peptides or (ii) one at the N-internal and the other(s) at the N-terminal site, in a highly flexible and controlled manner. A stepwise branching of N-terminal peptides has been achieved by glycoside aldehyde reductive amination followed by the glycoside carboxylic acid coupling (model 1). In another approach, after N-alkylation with glycoside aldehyde, the N-glycosylated derivative is subjected to peptide synthesis. This is then followed by the attachment of the second glycoside moiety at the N-terminal using either glycoside aldehyde or glycoside carboxylic acid derivative (model 2). Alternatively, the attachment of second and third glycoside derivatives could be achieved simultaneously, by reductive amination/carboxylic acid couplings (model 3). The methodologies presented here are highly versatile and combine diversity in both peptides/pseudopeptides and glycoside moieties.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".