Biosynthesis of depsipeptides, <i>or</i> Depsi: The peptides with varied generations
Bibliographic record
Abstract
ionophores cereulide and valinomycin, the anticancer agent cryptophycin, and the antimicrobial kutzneride. Furthermore, database searches return hundreds of uncharacterized systems likely to produce novel depsipeptides. These compounds are made by specialized nonribosomal peptide synthetases (NRPSs). NRPSs are biosynthetic megaenzymes that use a module architecture and multi-step catalytic cycle to assemble monomer substrates into peptides, or in the case of specialized depsipeptide synthetases, depsipeptides. Two NRPS domains, the condensation domain and the thioesterase domain, catalyze ester bond formation, and ester bonds are introduced into depsipeptides in several different ways. The two most common occur during cyclization, in a reaction between a hydroxy-containing side chain and the C-terminal amino acid residue in a peptide intermediate, and during incorporation into the growing peptide chain of an α-hydroxy acyl moiety, recruited either by direct selection of an α-hydroxy acid substrate or by selection of an α-keto acid substrate that is reduced in situ. In this article, we discuss how and when these esters are introduced during depsipeptide synthesis, survey notable depsipeptide synthetases, and review insight into bacterial depsipeptide synthetases recently gained from structural studies.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".