A structural model of latent evolutionary potentials underlying neutral networks in proteins
Bibliographic record
Abstract
A central question in molecular evolution concerns the nature of phenotypic transitions, in particular, if neutral mutations hamper or somehow facilitate adaptability of proteins to new requirements. Proteins have been found to fluctuate between different structures, with frequencies of structures being proportional to their stability. Therefore, functional promiscuity may correspond to different structures with energies close to the ground state which then represent multiple selectable traits. We here postulate that these near‐ground‐state structures facilitate smooth transitions between phenotypes. Using a biophysical heteropolymer model with exhaustive mappings of sequences onto structures, we demonstrate that this is indeed possible because of a smooth gradient of stability along which any structural phenotype can be optimized and also because of mutational proximity of similar phenotypes in genotype space. Our model provides a biophysical rationalization of the intriguing, and otherwise puzzling experimental observation that adaptation to new requirements, e.g., latent function of a promiscuous enzyme, can proceed while the “old,” phenotypically dominant function is maintained along a series of seemingly neutral mutations (see accompanying article). Thus pleiotropy may facilitate adaptation of latent traits before gene duplications and increase the effective adaptability of proteins.
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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".