Macrocyclization of Linear Peptides Enabled by Amphoteric Molecules
Bibliographic record
Abstract
There has been enormous interest in both naturally occurring and synthetic cyclic peptides as scaffolds that preorganize a given amino acid sequence into a rigid conformation. Such molecules have been employed as nanomaterials, imaging agents, and therapeutics. Unfortunately, the laboratory synthesis of cyclic peptides directly from linear precursors is afflicted by several thermodynamic and kinetic challenges, resulting in low chemical yields and poor chemo- and stereoselectivities. Here we report that amphoteric amino aldehydes can be used for efficient syntheses of cyclic peptides in high yields and selectivities starting from alpha-amino acids or linear peptides. The cyclizations effectively operate at unusually high molar concentrations (0.2 M), while side processes such as epimerization and cyclodimerization are not observed. The products are equipped with sites that allow for a highly specific, late-stage structural modification. The overall efficiency of the macrocyclization is due to the coexistence of nucleophilic and electrophilic reaction centers in amphoteric amino aldehydes.
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) | 0.002 | 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 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".