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Record W1785292658 · doi:10.1088/1367-2630/17/5/055017

Motor properties from persistence: a linear molecular walker lacking spatial and temporal asymmetry

2015· article· en· W1785292658 on OpenAlexafffund
Martin J. Zuckermann, Christopher N. Angstmann, Regina K. Schmitt, Gerhard A. Blab, Elizabeth H. C. Bromley, Nancy R. Forde, Heiner Linke, Paul M. G. Curmi

Bibliographic record

VenueNew Journal of Physics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
Topicstochastic dynamics and bifurcation
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaDivision of Mathematical SciencesVetenskapsrådetUniversity of New South WalesWestern Canada Research GridCompute CanadaSimon Fraser UniversityPacific Institute for the Mathematical Sciences
KeywordsPhysicsAsymmetryRatchetMolecular motorContext (archaeology)Statistical physicsWork (physics)Monte Carlo methodThermalClassical mechanicsNanotechnologyQuantum mechanics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.241
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2015
Admission routes2
Has abstractyes

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