A residue in helical conformation in the native state adopts a β‐strand conformation in the folding transition state despite its high and canonical ϕ‐value
Bibliographic record
Abstract
Delineating structures of the transition states in protein folding reactions has provided great insight into the mechanisms by which proteins fold. The most common method for obtaining this information is Φ-value analysis, which is carried out by measuring the changes in the folding and unfolding rates caused by single amino acid substitutions at various positions within a given protein. Canonical Φ-values range between 0 and 1, and residues displaying high values within this range are interpreted to be important in stabilizing the transition state structure, and to elicit this stabilization through native-like interactions. Although very successful in defining the general features of transition state structures, Φ-value analysis can be confounded when non-native interactions stabilize this state. In addition, direct information on backbone conformation within the transition state is not provided. In the work described here, we have investigated structure formation at a conserved β-bulge (with helical conformation) in the Fyn SH3 domain by characterizing the effects of substituting all natural amino acids at one position within this structural motif. By comparing the effects on folding rates of these substitutions with database-derived local structure propensity values, we have determined that this position adopts a non-native backbone conformation in the folding transition state. This result is surprising because this position displays a high and canonical Φ-value of 0.7. This work emphasizes the potential role of non-native conformations in folding pathways and demonstrates that even positions displaying high and canonical Φ-values may, nevertheless, adopt a non-native conformation in the transition state.
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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) | 0.001 | 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".