Quantum Mechanical/Molecular Mechanical investigation of the reduction mechanism of Cysteine Sulfinic acid of Peroxiredoxin via Sulfiredoxin
Bibliographic record
Abstract
The formation of the overoxidized cysteine sulfinic acid in proteins has been connected to be associated with various diseases including cancer and age-related diseases. This post-transitional modification of proteins under oxi- dative stress has been known to be irreversible. However, in eukaryotic, the overoxidation of typical 2-Cys perxoiredoxins (Prxs) to sulfinic acid is reversible via a repair enzyme known as sulfiredoxin (Srx) leading to the regulation of both per- oxide signaling and Prxs chaperon activity. In this study, the molecular modeling techniques including molecular dynam- ics simulations (MD) and the hybrid quantum mechanical/molecular mechanical (QM/MM) approach were used to eluci- date the atomistic details of this unique reaction in sulfur chemistry. Our results support the previous experimentally pro- posed mechanism in which the sulfinic acid oxygen perform an in line direct nucleophilic attack on the γ-phosphate of ATP forming sulfinic acid phosphoryl ester intermediate and ADP, via a low barrier of 16.3 kJ mol-1. Subsequently, the formed intermediate is directly reduced via an SN2 mechanism by the Srx-Cys99 forming thiosulfinate. Our results suggest that the rate-limiting step of the reduction mechanism is associated with the reduction step of the thiosulfinate intermedi- ate. This work significantly improves the current knowledge of this unique reaction, which could contribute to the discov- ery of new groups of antioxidants capable of reducing this irreversible overoxidized state in other 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".