Effect of cysteine oxidation in SARS-CoV-2 Spike protein on its conformational changes: insights from atomistic simulations
Bibliographic record
Abstract
This study investigates the effect of cysteine (Cys) oxidation on the conformational changes of the SARS-CoV-2 Spike (S) protein, a critical factor in viral attachment and entry into host cells. Using targeted molecular dynamics (TMD) simulations, we explore the conformational transitions between the down (inaccessible) and up (accessible) states of the SARS-CoV-2 S protein in both its native and oxidized forms. Our findings reveal that oxidation significantly increases the energy barrier for these transitions, as indicated by the work required to move from the down to the up conformation and vice versa. Specifically, in the oxidized system compared to the native system, the energy required to transition from the down to the up conformation increases by approximately 131 ± 1 kJ.mol -1 , while the energy required for the reverse transition increases by about 223 ± 6 kJ.mol -1 . This is due to the stabilizing effect of oxidation on the conformation of the SARS-CoV-2 S protein. Analysis of hydrogen bond and salt bridge formation before and after oxidation provides additional insights into the stabilization mechanisms, showing an increase in salt bridge formation that contributes to conformational stabilization. These results underscore the potential of targeting translational modifications to hamper viral entry or enhance susceptibility to neutralization, offering a novel perspective for antiviral strategy development against SARS-CoV-2. This study adds important knowledge to the field of viral protein dynamics and highlights the critical role of structural and computational biology in uncovering new therapeutic avenues.
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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) | 0.001 | 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) | 0.001 | 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".