Proline Periodicity Modulates the Self-assembly Properties of Elastin-like Polypeptides
Bibliographic record
Abstract
Elastin is a self-assembling protein of the extracellular matrix that provides tissues with elastic extensibility and recoil. The monomeric precursor, tropoelastin, is highly hydrophobic yet remains substantially disordered and flexible in solution, due in large part to a high combined threshold of proline and glycine residues within hydrophobic sequences. In fact, proline-poor elastin-like sequences are known to form amyloid-like fibrils, rich in β-structure, from solution. On this basis, it is clear that hydrophobic elastin sequences are in general optimized to avoid an amyloid fate. However, a small number of hydrophobic domains near the C terminus of tropoelastin are substantially depleted of proline residues. Here we investigated the specific contribution of proline number and spacing to the structure and self-assembly propensities of elastin-like polypeptides. Increasing the spacing between proline residues significantly decreased the ability of polypeptides to reversibly self-associate. Real-time imaging of the assembly process revealed the presence of smaller colloidal droplets that displayed enhanced propensity to cluster into dense networks. Structural characterization showed that these aggregates were enriched in β-structure but unable to bind thioflavin-T. These data strongly support a model where proline-poor regions of the elastin monomer provide a unique contribution to assembly and suggest a role for localized β-sheet in mediating self-assembly interactions.
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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 | 0.001 |
| 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".