Conformational Tinkering Drives Evolution of a Promiscuous Activity through Indirect Mutational Effects
Bibliographic record
Abstract
How remote mutations can lead to changes in enzyme function at a molecular level is a central question in evolutionary biochemistry and biophysics. Here, we combine laboratory evolution with biochemical, structural, genetic, and computational analysis to dissect the molecular basis for the functional optimization of phosphotriesterase activity in a bacterial lactonase (AiiA) from the metallo-β-lactamase (MBL) superfamily. We show that a 1000-fold increase in phosphotriesterase activity is caused by a more favorable catalytic binding position of the paraoxon substrate in the evolved enzyme that resulted from conformational tinkering of the active site through peripheral mutations. A nonmutated active site residue, Phe68, was displaced by ∼3 Å through the indirect effects of two second-shell trajectory mutations, allowing molecular interactions between the residue and paraoxon. Comparative mutational scanning, i.e., examining the effects of alanine mutagenesis on different genetic backgrounds, revealed significant changes in the functional roles of Phe68 and other nonmutated active site residues caused by the indirect effects of trajectory mutations. Our work provides a quantitative measurement of the impact of second-shell mutations on the catalytic contributions of nonmutated residues and unveils the underlying intramolecular network of strong epistatic mutational relationships between active site residues and more remote residues. Defining these long-range conformational and functional epistatic relationships has allowed us to better understand the subtle, but cumulatively significant, role of second- and third-shell mutations in evolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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".