Modulation of the Passive Permeability of Semipeptidic Macrocycles: N- and C-Methylations Fine-Tune Conformation and Properties
Bibliographic record
Abstract
Incorporating small modifications to peptidic macrocycles can have a major influence on their properties. For instance, N-methylation has been shown to impact permeability. A better understanding of the relationship between permeability and structure is of key importance as peptidic drugs are often associated with unfavorable pharmacokinetic profiles. Starting from a semipeptidic macrocycle backbone composed of a tripeptide tethered head-to-tail with an alkyl linker, we investigated two small changes: peptide-to-peptoid substitution and various methyl placements on the nonpeptidic linker. Implementing these changes in parallel, we created a collection of 36 compounds. Their permeability was then assessed in parallel artificial membrane permeability assay (PAMPA) and Caco-2 assays. Our results show a systematic improvement in permeability associated with one peptoid position in the cycle, while the influence of methyl substitution varies on a case-by-case basis. Using a combination of molecular dynamics simulations and NMR measurements, we offer hypotheses to explain such behavior.
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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) | 0.000 | 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) | 0.000 | 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".