Optimal Attachment Position and Linker Length Promote Native‐like Character of Cavitand‐Based Template‐Assembled Synthetic Proteins (TASPs)
Bibliographic record
Abstract
We have designed, synthesised and characterised a series of template-assembled de novo four-helix bundles, each differing in the linker length between the template and the peptides. The helix is based on an earlier peptide sequence: EELLKKLEELLKKLG (first-generation sequence), which was designed to link the hydrophilic/hydrophobic interface of the helices. Increasing or decreasing the linker length by one glycine residue had a significant effect on the structure and properties of the template-assembled synthetic proteins (TASPs). Here, the effect of the linker length is further probed by linking the peptides closer to the hydrophobic face by using the second-generation sequence, AEELLKKLEELLKKG, in an effort to improve the packing between the helices and to better understand the helical bundles. The peptides were synthesised with 0-4 Gly linker residues and linked onto a cavitand template. The proteins were found to be alpha-helical, stable to guanidine hydrochloride (GuHCl) and to unfold cooperatively. However, their stabilities toward GuHCl, propensity to self-aggregate and structural specificity differed. The two-glycine variant of the second-generation series demonstrated the highest stability and most native-like character of all the mononeric TASPs in both the first- and second-generation series. The structural specificity of this two glycine variant is comparable to that of other known native-like de novo proteins. Molecular dynamics simulations showed that the two-glycine variant contains helices that are tilted with respect to the cavitand template and may account for its unique properties.
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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) | 0.000 | 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 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".