Evolution of an enzyme from a solute-binding protein
Bibliographic record
Abstract
Abstract Much of the functional diversity observed in modern enzyme superfamilies originates from molecular tinkering with existing enzymes 1 . New enzymes frequently evolve from enzymes with latent, promiscuous activities 2 , and often inherit key features of the ancestral enzyme, retaining conserved catalytic groups and stabilizing analogous intermediates or transition states 3 . While experimental evolutionary biochemistry has yielded considerable insight into the evolution of new enzymes from existing enzymes 4 , the emergence of catalytic activity de novo remains poorly understood. Although certain enzymes are thought to have evolved from non-catalytic proteins 5–7 , the mechanisms underlying these complete evolutionary transitions have not been described. Here we show how the enzyme cyclohexadienyl dehydratase (CDT) evolved from a cationic amino acid-binding protein belonging to the solute-binding protein (SBP) superfamily. Analysis of the evolutionary trajectory between reconstructed ancestors and extant proteins showed that the emergence and optimization of catalytic activity involved several distinct processes. The emergence of CDT activity was potentiated by the incorporation of a desolvated general acid into the ancestral binding site, which provided an intrinsically reactive catalytic motif, and reshaping of the ancestral binding site, which facilitated enzyme-substrate complementarity. Catalytic activity was subsequently gained via the introduction of hydrogen-bonding networks that positioned the catalytic residue precisely and contributed to transition state stabilization. Finally, catalytic activity was enhanced by remote substitutions that refined the active site structure and reduced sampling of non-catalytic states. Our work shows that the evolutionary processes that underlie the emergence of enzymes by natural selection in the wild are mirrored by recent examples of computational design and directed evolution of enzymes in the laboratory.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".