Origin of Pressure Resistance in Deep-Sea Lactate Dehydrogenase
Bibliographic record
Abstract
High hydrostatic pressure has a dramatic effect on biochemical systems, as exposure to high pressure can result in structural perturbations ranging from dissociation of protein complexes to complete denaturation. The deep ocean presents an interesting paradox since it is teeming with life despite the high-pressure environment. This is due to evolutionary adaptations in deep-sea organisms, such as amino acid substitutions in their proteins, which aid in resisting the denaturing effects of pressure. However, the physicochemical mechanism by which these substitutions can induce pressure resistance remains unknown. Here, we use molecular dynamics simulations to study pressure-adapted lactate dehydrogenase from the deep-sea abyssal grenadier ( Coryphaenoides armatus ), in comparison with that of the shallow-water Atlantic cod ( Gadus morhua ). We examined structural, thermodynamic and volumetric contributions to pressure resistance, and report that the amino acid substitutions result in a decrease in volume of the deep-sea protein accompanied by a decrease in thermodynamic stability of the native protein. Our simulations at high pressure also suggest that differences in compressibility may be important for understanding pressure resistance in deep-sea proteins.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".