A Robust, Gram-Scale and High-Yield Synthesis of MDP Congeners for Activation of the NOD2 Receptor and Vaccine Adjuvantation
Bibliographic record
Abstract
Abstract The bacterial peptidoglycan (PGN) constituent muramyl dipeptide (MDP) and its congeners possess immuno-adjuvant activity, and find applications in vaccines to potentiate the immune response of antigens. It confers non-specific resistance towards pathogenic infections and defense against tumors. In this work, the parent MDP molecule is re-designed by replacing its carbohydrate moiety with an immunoregulatory xanthine scaffold, while conserving the l-d configuration of the pharmacophore. Alkyl chains are introduced at the C-terminus of d-isoglutamine to help the molecules access cytoplasmic NOD2 receptors and activate the innate immune system. Lipophilic MDP congeners are thus obtained by adopting a direct or indirect convergent synthetic route with overall yields of >50%. We found that an indirect approach can reliably be implemented on gram scale, thereby unlocking access to substantial amounts of pathogen-associated molecular patterns for in vivo studies, which will accelerate the development of NOD2 immuno-adjuvants against viral and bacterial infections.
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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".