Mitsunobu Reaction on Solid Support for Peptide N-terminal Farnesylation
Bibliographic record
Abstract
Prenylation is an important post-translational modification of peptide structures. For example, farnesylated and geranylgeranylated peptides and proteins bind to cell membranes by way of the prenyl subunit. Prenylation is involved in a wide variety of biological process and diseases, including cancer [1,2] and Alzeimer’s disease [2]. Prenylated peptides have been shown to be generally non-toxic and to exhibit cell permeable properties [3]. Prenylated protein libraries have been used to study various biochemical mechanisms that involve posttranslational prenylation [4]. Prenylated peptides have also been used as prenyltransferase inhibitors [5]. Prenylated peptides may exhibit ability to localize in membranes, which may enhance their metabolic stability and biological presentation. The conventional way to introduce a prenyl group onto a peptide chain involves nucleophilic displacement by a cysteine residue thiol side chain on a proper prenyl bromide [3]. Prenyl bromides are relatively expensive and unstable. Prenylation on nitrogen has been less well studied, but may offer an alternative way for introducing the lipid moiety onto peptides. In an effort to explore N-terminal prenylation, we have explored the Mitsunobu reaction in order to employ the relatively more stable alcohols instead of their prenyl halide counterparts. For this study, the L-enantiomer (L-PDC-31, Ile-Leu-Gly-His-Cit-Asp-Tyr-Lys) of the D-peptide PDC-31 was chosen [6], in part because this prostaglandin F2α receptor modulator has completed successfully phase 1b clinical trials in which toxicity was assessed in women suffering from primary desmenorea [7]. Hypothesizing that the L-isomer may be active, yet rapidly degraded in biological tissues, a farnesyl chain at the N-terminal nitrogen has been examined to increase metabolic stability of the peptide. Herein, the Mistunobu reaction has been employed to farnesylate a solid supported peptide using farnesol as a shelf stable and relatively inexpensive reagent in order to prepare farnesyl peptide 4.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".