The ups and downs of amino acid co-evolution: evolutionary Stokes and anti-Stokes shifts
Bibliographic record
Abstract
Abstract The most fundamental form of epistasis occurs between residues within a protein. Epistatic interactions can have significant consequences for evolutionary dynamics. For example, a substitution to a deleterious amino acid may be compensated for by replacements at other sites which increase its propensity (a function of its average fitness) over time - this is the evolutionary Stokes shift. We discovered that an opposite trend -the decrease in amino acid propensity with time- can also occur via the same epistatic dynamics. We define this novel and pervasive phenomenon as the evolutionary anti-Stokes shift. Our extensive simulations of three natural proteins show that evolutionary Stokes and anti-Stokes shifts occur with similar frequencies and magnitudes across the protein. This highlights that decreasing amino acid propensities, on their own, are not conclusive evidence of adaptive responses to a changing environment. We find that stabilizing substitutions are often permissive (i.e., expand potential evolutionary paths) whereas destabilizing substitutions are restrictive. We show how these dynamics explain the variations in amino acid propensities associated with both evolutionary shifts in propensities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".