Prediction of Misfolding-Specific Epitopes in SOD1 Using Collective Coordinates
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Bibliographic record
Abstract
We introduce a global, collective coordinate bias into molecular dynamics simulations that partially unfolds a protein, in order to predict misfolding-specific epitopes based on the regions that locally unfold. Several metrics are used to measure local disorder, including solvent exposed surface area (SASA), native contacts ( Q), and root mean squared fluctuations (RMSF). The method is applied to Cu, Zn superoxide dismutase (SOD1). For this protein, the processes of monomerization, metal loss, and conformational unfolding due to microenvironmental stresses are all separately taken into account. Several misfolding-specific epitopes are predicted, and consensus epitopes are calculated. These predicted epitopes are consistent with the "lower-resolution" peptide sequences used to raise disease-specific antibodies, but the epitopes derived from collective coordinates contain shorter, more refined sequences for the key residues constituting the epitope.
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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