Millisecond Conformational Dynamics of Skeletal Myosin II Power Stroke Studied by High-Speed Atomic Force Microscopy
Bibliographic record
Abstract
Abstract Myosin-based molecular motors are responsible for a variety of functions in the cells. Myosin II is ultimately responsible for muscle contraction and can be affected by multiple mutations, that may lead to myopathies. Therefore, it is essential to understand the nanomechanical properties of myosin II. Due to the lack of technical capabilities to visualize rapid changes in nonprocessive molecular motors, there are several mechanistic details in the force-generating steps produced by myosin II that are poorly understood. In this study, high-speed atomic force microscopy was used to visualize the actin–myosin complex at high temporal and spatial resolutions, providing further details about the myosin mechanism of force generation. A two-step motion of the double-headed heavy meromyosin (HMM) lever arm, coupled to an 8.4 nm working stroke was observed in the presence of ATP. HMM heads attached to an actin filament worked independently, exhibiting different lever arm configurations in given time during experiments. A lever arm rotation was associated with several non-stereospecific long-lived and stereospecific short-lived (∼1 ms) HMM conformations. The presence of free Pi increased the short-lived stereospecific binding events in which the power stroke occurred, followed by release of Pi after the power stroke.
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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 | 0.000 |
| 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) | 0.001 | 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".