The synergy of ChemMatrix resin® and pseudoproline building blocks renders Rantes, a complex aggregated chemokine
Bibliographic record
Abstract
Abstract Traditionally, solid‐phase synthesis has relied on polystyrene‐based resins for the synthesis of all kinds of peptides. However, due to their high hydrophobicity, these resins have certain limitations, particularly in the synthesis of complex peptides, and in such cases, poly(ethylene glycol) (PEG)‐based resins are often found to give superior results. Another powerful strategy for expediting the assembly of complex peptides is to employ pseudoproline dipeptides. These derivatives disrupt the interactions among chains that are usually the cause of poor coupling yields in aggregated sequences. Here we report on an efficient stepwise solid‐phase synthesis of RANTES (1–68) by combining the advantages of the totally PEG‐based ChemMatrix® resin and pseudoproline dipeptides. © 2006 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 84: 566–575, 2006 This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com
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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) | 0.002 | 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".