PreprintCited by 5Force Microscopy Techniques and Applicationsstochastic dynamics and bifurcationAdvanced Fluorescence Microscopy Techniques

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Chemical-state-dependent free energy profile from single-molecule trajectories of biomolecular motor: Application to processive chitinase

Open access
Okazaki, Kei-ichi, Nakamura, Akihiko, Iino, Ryota·2019·The Journal of Physical Chemistry B

Preprint — published as 10.1021/acs.jpcb.0c02698

Abstract

The mechanism of biomolecular motors has been elucidated using single-molecule experiments for visualizing motor motion. However, it remains elusive that how changes in the chemical state during the catalytic cycle of motors lead to unidirectional motions. In this study, we use singlemolecule trajectories to estimate an underlying diffusion model with chemical-state-dependent free energy profile. To consider nonequilibrium trajectories driven by the chemical energy consumed by biomolecular motors, we develop a novel framework based on a hidden Markov model, wherein switching among multiple energy profiles occurs reflecting the chemical state changes in motors. The method is tested using simulation trajectories and applied to singlemolecule trajectories of processive chitinase, a linear motor that is driven by the hydrolysis energy of a single chitin chain. The chemical-state-dependent free energy profile underlying the burnt- bridge Brownian ratchet mechanism of processive chitinase is determined. The novel framework allows us to connect the chemical state changes to the unidirectional motion of biomolecular motors.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/655878

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Research works printed but not linked: 86

  1. 10.1038/386299a0 · DOI
  2. 10.1038/nsmb721 · DOI
  3. 10.1016/j.cell.2007.05.020 · DOI
  4. 10.1038/nchembio.443 · DOI
  5. 10.1073/pnas.1106787108 · DOI
  6. 10.1073/pnas.1524720113 · DOI
  7. 10.1073/pnas.0507764102 · DOI
  8. 10.1074/jbc.RA119.008947 · DOI
  9. 10.1038/374555a0 · DOI
  10. 10.1016/S0092-8674(00)80911-3 · DOI
  11. 10.1126/science.1084398 · DOI
  12. 10.1038/nature09450 · DOI
  13. 10.1038/365721a0 · DOI · Paper page
  14. 10.1038/nchembio.2028 · DOI
  15. 2018, Nonequilibrium Energetics of Molecular Motor Kinesin, Phys. Rev. Lett, 121, 218101, 10.1103/PhysRevLett.121.218101 · DOI
  16. 10.1016/j.cell.2006.05.046 · DOI
  17. 10.1126/science.1215804 · DOI
  18. 10.1038/nsmb.2205 · DOI
  19. 10.1038/s41598-020-59121-0 · DOI
  20. 10.1126/science.1208386 · DOI
  21. 10.1038/ncomms4975 · DOI
  22. 10.1038/s41467-018-02974-x · DOI · Paper page
  23. 10.1039/C7CP04606E · DOI
  24. 10.1074/jbc.RA119.012078 · DOI
  25. 10.1016/S0969-2126(02)00789-X · DOI
  26. 10.1073/pnas.0509642103 · DOI
  27. 10.1073/pnas.1305497110 · DOI
  28. 10.1073/pnas.1317641110 · DOI
  29. 10.1016/j.str.2010.01.014 · DOI
  30. 10.1016/j.str.2007.11.008 · DOI · Paper page
  31. 10.1007/s003390201340 · DOI
  32. 10.1073/pnas.1818589116 · DOI
  33. 10.1016/S0096-4174(18)30128-8 · DOI · Paper page
  34. 10.1038/233533a0 · DOI
  35. 10.1016/0065-227X(90)90009-I · DOI
  36. 10.1103/PhysRevLett.72.1766 · DOI
  37. 10.1103/RevModPhys.69.1269 · DOI
  38. 2010, Motor Proteins as Nanomachines: The Roles of Thermal Fluctuations in Generating Force and Motion, Prog. Math. Phys, 60, 47
  39. 2016, Molecular Motors: Power Strokes Outperform Brownian Ratchets, J. Phys. Chem. B, 120, 6327, 10.1021/acs.jpcb.6b02776 · DOI
  40. 10.1073/pnas.0911830107 · DOI
  41. 2018, Diffusion Enhancement of Brownian Motors Revealed by a Solvable Model, Phys. Rev. E, 98, 1
  42. 10.1529/biophysj.106.082487 · DOI
  43. 10.1021/jp903671p · DOI
  44. 2014, Complex RNA Folding Kinetics Revealed by Single-Molecule FRET and Hidden Markov Models, J. Am. Chem. Soc, 136, 4534, 10.1021/ja4098719 · DOI · Paper page
  45. 10.1126/science.1215768 · DOI
  46. 2018, Protein Folding Transition Path Times from Single Molecule FRET, Curr. Opin. Struct. Biol, 48, 30, 10.1016/j.sbi.2017.10.007 · DOI
  47. Matsunaga, Y. ; Sugita, Y. Linking Time-Series of Single-Molecule Experiments with Molecular Dynamics Simulations by Machine Learning. Elife 2018, 1–19. https://doi.org/10.7554/eLife.32668. · DOI
  48. 2013, Expectation-Maximization of the Potential of Mean Force and Diffusion Coefficient in Langevin Dynamics from Single Molecule FRET Data Photon by Photon, J. Phys. Chem. B, 117, 15591, 10.1021/jp405983d · DOI
  49. Das, R. ; Cairo, C. W. ; Coombs, D. A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton. PLoS Comput. Biol. 2009, 5 (11). https://doi.org/10.1371/journal.pcbi.1000556. · DOI
  50. 10.1016/j.sbi.2004.01.009 · DOI
  51. 10.1073/pnas.0604375103 · DOI
  52. 10.1073/pnas.0802524105 · DOI
  53. 10.1021/ja1061399 · DOI
  54. 10.1016/j.sbi.2014.12.003 · DOI
  55. 10.1073/pnas.0704167104 · DOI
  56. 10.1007/s00249-010-0616-9 · DOI
  57. 10.1038/35185 · DOI
  58. 10.1038/24409 · DOI · Paper page
  59. 10.1073/pnas.0910390107 · DOI
  60. 10.1039/c1cp21541h · DOI
  61. Neupane, K. ; Manuel, A. P. ; Woodside, M. T. Protein Folding Trajectories Can Be Described Quantitatively by One-Dimensional Diffusion over Measured Energy Landscapes. Nat. Phys. 2016, No. March, 10–14. https://doi.org/10.1038/nphys3677. · DOI
  62. 2005, Position-Dependent Diffusion Coefficients and Free Energies from Bayesian Analysis of Equilibrium and Replica Molecular Dynamics Simulations, New J. Phys, 7, 0
  63. 10.1073/pnas.1419490112 · DOI
  64. 10.1021/jp0761665 · DOI · Paper page
  65. Press, W. H. ; Teukolsky, S. A. ; Vetterling, W. T. ; Flannery, B. P. Numerical Recipes 3rd Edition: The Art of Scientific Computing; Cambridge University Press, 2007.
  66. 10.1038/nchembio.715 · DOI
  67. Cossio, P. ; Hummer, G. ; Szabo, A. Transition Paths in Single-Molecule Force Spectroscopy. J. Chem. Phys. 2018, 148 (12). https://doi.org/10.1063/1.5004767. · DOI
  68. 10.1063/1.476800 · DOI
  69. 10.1021/j100540a008 · DOI
  70. 2012, Microscopic Reversibility as the Organizing Principle of Molecular Machines, Nat. Nanotechnol, 7, 684, 10.1038/nnano.2012.188 · DOI
  71. 2014, Nonequilibrium Dissipation-Free Transport in F1-ATPase and the Thermodynamic Role of Asymmetric Allosterism, Biophys. J, 106, 2450, 10.1016/j.bpj.2014.04.034 · DOI
  72. 10.1016/j.bpj.2018.11.016 · DOI
  73. 10.1016/j.copbio.2013.12.002 · DOI
  74. 10.1126/science.1099179 · DOI
  75. 2006, Powering a Burnt Bridges Brownian Ratchet: A Model for an Extracellular Motor Driven by Proteolysis of Collagen, Phys. Rev. E - Stat. Nonlinear, Soft Matter Phys, 73, 1
  76. 10.1038/nature04928 · DOI
  77. 10.1209/epl/i2002-00385-6 · DOI
  78. 10.1016/S0092-8674(00)81456-7 · DOI
  79. 10.1146/annurev.biophys.33.110502.132716 · DOI
  80. 10.1103/PhysRevLett.104.208101 · DOI
  81. 2015, Elasticity, Friction, and Pathway of γ-Subunit Rotation in F o F ι -ATP Synthase, Proc. Natl. Acad. Sci, 2015, 201500691
  82. 10.1074/jbc.M115.659656 · DOI
  83. 10.1021/jp200912q · DOI
  84. Berezhkovskii, A. M. ; Makarov, D. E. From Nonequilibrium Single-Molecules Trajectories to Underlying Dynamics. J. Phys. Chem. Lett. 2020. https://doi.org/10.1021/acs.jpclett.9b03705. · DOI
  85. 10.1016/S0006-3495(96)79605-4 · DOI
  86. 2012, Recovery of State-Specific Potential of Molecular Motor from Single-Molecule Trajectory, EPL (Europhysics Lett, 97, 40004, 10.1209/0295-5075/97/40004 · DOI

Metadata

Authors
Okazaki, K.-I., Nakamura, A., & Iino, R.
Affiliations
  • National Institutes of Natural Sciences (JP)
  • Shizuoka University (JP)
Corresponding author
Okazaki, Kei-ichi
Venue
The Journal of Physical Chemistry B
Publisher
openRxiv
Published
2019-05-30
Volume
124
Issue
30
Pages
6475-6487
ISSN
1520-5207 (ISSN-L)
OpenAlex
W3039422301
Cited by
5
References
1
Citations by year
2026: 1 · 2023: 1 · 2022: 1 · 2021: 1 · 2020: 1
FWCI
0.41
Type
journal article
Language
en
Open access
Locations
  • The Journal of Physical Chemistry B (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed (publishedVersion)
Funders
  • Ministry of Education, Culture, Sports, Science and Technology (JP18H02418, JP18H02415, J281002, JP18H05424)
  • Japan Society for the Promotion of Science (18H02418, JP18H05424, 18H02415)
  • National Institutes of Natural Sciences (J281002)
Topics
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Force Microscopy Techniques and Applications
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
Keywords
molecular motors, single-molecule trajectories, hidden Markov models, unidirectional motion, chitin hydrolysis
MeSH terms
Chitinases, Diffusion, Kinetics, Motion, Molecular Motor Proteins

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Chemical-state-dependent free energy profile from single-molecule trajectories of biomolecular motor: Application to processive chitinase. https://app.cochat.ai/papers/10.1101/655878
The paper
Okazaki, K.-I., Nakamura, A., & Iino, R. (2019). Chemical-state-dependent free energy profile from single-molecule trajectories of biomolecular motor: Application to processive chitinase. The Journal of Physical Chemistry B. https://doi.org/10.1101/655878