Reframing prosegment‐dependent folding and limits on natural protein folding landscapes from an evolutionary perspective
Bibliographic record
Abstract
In this perspective, we propose that the folding energy landscapes of model proteases including pepsin and alpha-lytic protease (αLP), which lack thermodynamic stability and fold on the order of months to millennia, respectively, should be viewed as not evolved and fundamentally distinct from their extended zymogen forms. These proteases have evolved to fold with prosegment domains and robustly self-assemble as expected. In this manner, general protein folding principles are strengthened. In support of our view, αLP and pepsin exhibit hallmarks of frustration associated with unevolved folding landscapes, such as non-cooperativity, memory effects, and substantial kinetic trapping. The evolutionary implications of this folding strategy are considered in detail. Direct applications of this folding strategy on enzyme design, finding new drug targets, and constructing tunable folding landscapes are also discussed. Together with certain proteases, growing examples of other folding "exceptions"-including protein fold switching, functional misfolding, and prevalent inability to refold-suggests a paradigm shift in which proteins may evolve to exist in a wide range of energy landscapes and structures traditionally thought to be avoided in nature.
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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 | 0.000 |
| 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 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".