Motor properties from persistence: a linear molecular walker lacking spatial and temporal asymmetry
Bibliographic record
Abstract
The stepping direction of linear molecular motors is usually defined by a spatial asymmetry of the motor, its track, or both. Here we present a model for a molecular walker that undergoes biased directional motion along a symmetric track in the presence of a temporally symmetric chemical cycle. Instead of using asymmetry, directionality is achieved by persistence. At small load force the walker can take on average thousands of steps in a given direction until it stochastically reverses direction. We discuss a specific experimental implementation of a synthetic motor based on this design and find, using Langevin and Monte Carlo simulations, that a realistic walker can work against load forces on the order of picoNewtons with an efficiency of ∼18%, comparable to that of kinesin. In principle, the walker can be turned into a permanent motor by externally monitoring the walker's momentary direction of motion, and using feedback to adjust the direction of a load force. We calculate the thermodynamic cost of using feedback to enhance motor performance in terms of the Shannon entropy, and find that it reduces the efficiency of a realistic motor only marginally. We discuss the implications for natural protein motor performance in the context of the strong performance of this design based only on a thermal ratchet.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".