Oxidation-induced structural changes in actin and myosin evaluated by computational simulation, machine learning modeling and high-speed AFM
Bibliographic record
Abstract
Abstract High levels of reactive oxygen species produced during muscle oxidative stress are implicated in the development of several muscle diseases. To better understand the mechanism behind a reduced myosin force generation under oxidizing conditions, we analyzed the structural and functional changes in the actin and actin-myosin complex using high-speed atomic force microscopy (HS-AFM), simulated HS-AFM, and molecular dynamics (MD) simulation. Computational oxidative nitration of tyrosine residues demonstrated instability in the molecular structure of the F-actin subunit. Cross-section analysis of the simulated HS-AFM images revealed a shift in the height values (∼0.2-1.5 nm in magnitude) between the non-oxidized and oxidized actin, which correspond to the height differences observed in HS-AFM experiments with in vitro oxidized F-actin. The oxidation-induced structural alterations in actin impact myosin molecule displacement on the single-molecule level. The displacements of myosin heads along the F-actin filaments in the presence of ATP involve the binding of the myosin molecule to a specific site on the F-actin filament, followed by the rotation of the myosin lever arm, which triggers the release of inorganic phosphate (Pi). Subsequently, the myosin head detaches from the F-actin and re-binds to a new site on the filament. The formation of the SIN-1-treated F-actin-myosin complex in the presence of ATP resulted in a change in myosin head displacement size, with a significant decrease in the frequency of long displacements (≥ 4 nm). These results suggest that oxidation decreases the pool of the weak-bound myosin molecules and shortens the long displacements related to the Pi release step, reducing the force generation by myosin motors.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".