A structural perspective on the temperature-dependent activity of enzymes
Bibliographic record
Abstract
ABSTRACT Enzymes are biomolecular catalysts whose activity varies with temperature. Unlike for small-molecule catalysts, the structural ensembles of enzymes can vary substantially with temperature, and it is in general unclear how this modulates the temperature dependence of activity. Here multi-temperature X-ray crystallography was used to record structural changes from −20°C to 40°C for a mesophilic enzyme in complex with inhibitors mimicking substrate-, intermediate-, and product-bound states, representative of major complexes underlying the kinetic constant k cat . Both inhibitors, substrates and catalytically relevant loop motifs increasingly populate catalytically competent conformations as temperature increases. These changes occur even in temperature ranges where kinetic measurements show roughly linear Arrhenius/Eyring behavior where parameters characterizing the system are assumed to be temperature independent. Simple analysis shows that linear Arrhenius/Eyring behavior can still be observed when the underlying activation energy / enthalpy values vary with temperature, e.g., due to structural changes, and that the underlying thermodynamic parameters can be far from values derived from Arrhenius/Eyring model fits. Our results indicate a critical role for temperature-dependent atomic-resolution structural data in interpreting temperature-dependent kinetic data from enzymatic systems. One-Sentence Summary Structural data spanning a 60°C temperature range for enzyme complexes mimicking the substrate-, intermediate-, and product-bound states illuminate how small temperature-dependent structural changes may modulate activity and render parameters deduced from Arrhenius/Eyring plots unreliable.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".