Conformational plasticity surrounding the active site of NADH oxidase from <i>Thermus thermophilus</i>
Bibliographic record
Abstract
Biotechnological applications of enzymes can involve the use of these molecules under nonphysiological conditions. Thus, it is of interest to understand how environmental variables affect protein structure and dynamics and how this ultimately modulates enzyme function. NADH oxidase (NOX) from Thermus thermophilus exemplifies how enzyme activity can be tuned by reaction conditions, such as temperature, cofactor substitution, and the addition of cosolutes. This enzyme catalyzes the oxidation of reduced NAD(P)H to NAD(P)(+) with the concurrent reduction of O2 to H2O2, with relevance to biosensing applications. It is thermophilic, with an optimum temperature of approximately 65°C and sevenfold lower activity at 25°C. Moderate concentrations (≈1M) of urea and other chaotropes increase NOX activity by up to a factor of 2.5 at room temperature. Furthermore, it is a flavoprotein that accepts either FMN or the much larger FAD as cofactor. We have used nuclear magnetic resonance (NMR) titration and (15)N spin relaxation experiments together with isothermal titration calorimetry to study how NOX structure and dynamics are affected by changes in temperature, the addition of urea and the substitution of the FMN cofactor with FAD. The majority of signals from NOX are quite insensitive to changes in temperature, cosolute addition, and cofactor substitution. However, a small cluster of residues surrounding the active site shows significant changes. These residues are implicated in coupling changes in the solution conditions of the enzyme to changes in catalytic activity.
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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".