Evidence for an Allosteric S-Nitrosoglutathione Binding Site in S-Nitrosoglutathione Reductase (GSNOR)
Bibliographic record
Abstract
Current research has identified S-nitrosoglutathione reductase (GSNOR) as the central enzyme for regulating protein S-nitrosylation. In addition, the dysregulation of GSNOR expression is implicated in several organ system pathologies including respiratory, cardiovascular, hematologic, and neurologic, making GSNOR a primary target for pharmacological intervention. This study demonstrates the kinetic activation of GSNOR by its substrate S-nitrosoglutathione (GSNO). GSNOR kinetic analysis data resulted in nonhyperbolic behavior that was successfully accommodated by the Hill–Langmuir equation with a Hill coefficient of +1.75, indicating that the substrate, GSNO, was acting as a positive allosteric affector. Docking and molecular dynamics simulations were used to predict the location of the GSNO allosteric domain comprising the residues Asn185, Lys188, Gly321, and Lys323 in the vicinity of the structural Zn2+-binding site. GSNO binding to Lys188, Gly321, and Lys323 was further supported by hydrogen–deuterium exchange mass spectroscopy (HDXMS), as deuterium exchange significantly decreased at these residues in the presence of GSNO. The site-directed mutagenesis of Lys188Ala and Lys323Ala resulted in the loss of allosteric behavior. Ultimately, this work unambiguously demonstrates that GSNO at large concentrations activates GSNOR by binding to an allosteric site comprised of the residues Asn185, Lys188, Gly321, and Lys323. The identification of an allosteric GSNO-binding domain on GSNOR is significant, as it provides a platform for pharmacological intervention to modulate the activity of this essential enzyme.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".