Structural and functional importance of local and global conformational fluctuations in the <scp>RN</scp>ase <scp>A</scp> superfamily
Bibliographic record
Abstract
Understanding the relationship between protein structure and flexibility is of utmost importance for deciphering the tremendous rates of reactions catalyzed by enzyme biocatalysts. It has been postulated that protein homologs have evolved similar dynamic fluctuations to promote catalytic function, a property that would presumably be encoded in their structural fold. Using one of the best-characterized enzyme systems of the past century, we explore this hypothesis by comparing the numerous and diverse flexibility reports available for a number of structural and functional homologs of the pancreatic-like RNase A superfamily. Using examples from the literature and from our own work, we cover recent and historical evidence pertaining to the highly dynamic nature of this important structural fold, as well as the presumed importance of local and global concerted motions on the ribonucleolytic function. This minireview does not pretend to cover the overwhelming RNase A literature in a comprehensive manner; rather, efforts have been made to focus on the characterization of multiple timescale motions observed in the free and/or ligand-bound structural homologs as they proceed along the reaction coordinates. Although each characterized enzyme of this architectural fold shows unique motional features on a local scale, accumulating evidence from X-ray crystallography, NMR spectroscopy and molecular dynamics simulations suggests that global dynamic fluctuations, such as the functionally relevant hinge-bending motion observed in the prototypical RNase A, are shared between homologs of the pancreatic-like RNase superfamily. These observations support the hypothesis that analogous dynamic residue clusters are evolutionarily conserved among structural and functional homologs catalyzing similar enzymatic reactions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".