Ranking the factors that contribute to protein β‐sheet folding
Why this work is in the frame
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Bibliographic record
Abstract
The formation of beta-sheet domains in proteins involves five energetically important factors: the formation of networks of hydrogen bonds and hydrophobic faces, and the residue propensities, or preferences, to be found at the edges of the beta-sheet, to adopt the extended conformation, and to make contact with other residues. These relative energy contributions define a potential energy function. Here, we show how optimizing this potential energy function reveals the formation of hydrophobic faces as the utmost factor. The potential energy function was optimized to minimize the Z-scores of the native topologies among the exhaustive sets of over 400 different beta-sheets. These results corroborate with experimental data that showed the environment of a protein is an important modulator of beta-sheet folding. The contact propensities were found to be the least important, which could explain the poor predictive power of beta-strand alignment methods based on pair-wise contact matrices.
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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 it