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03:15
Studying Energy Dynamics and Productivity - Concept
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Reconstructing free-energy landscapes for cyclic molecular motors using full multidimensional or partial
N J López-Alamilla1, M W Jack1, K J Challis2
1Department of Physics, University of Otago, P. O. Box 56, Dunedin 9054, New Zealand.
Physical Review. E
|September 11, 2019
Summary
We developed a k-space method to reconstruct free-energy landscapes from molecular motor trajectories. This method effectively reconstructs landscapes from partial data, aiding the study of energy conversion in molecular motors.
Area of Science:
- Biophysics
- Physical Chemistry
- Computational Biology
Background:
- Diffusion on free-energy landscapes is key to understanding molecular motors.
- Energy conversion (chemical to mechanical) is modeled using multidimensional potential landscapes.
Purpose of the Study:
- To present a k-space method for reconstructing multidimensional free-energy landscapes from single-molecule trajectories.
- To assess the method's robustness with full and partial dynamic information.
- To explore implications for studying biological molecular motors.
Main Methods:
- Developed a k-space method to reconstruct free-energy landscapes.
- Utilized simulated 2D stochastic trajectories (full and partial dynamic information).
- Reconstructed multidimensional landscapes and effective 1D landscapes.
Main Results:
- Successfully reconstructed 2D free-energy landscapes from full dynamic information.
- Demonstrated limited reconstruction of 2D landscapes from partial data.
- Successfully reconstructed effective 1D landscapes from partial data.
- Identified signatures of energy conversion within reconstructed landscapes.
Conclusions:
- The k-space method is robust for reconstructing free-energy landscapes from molecular trajectories.
- Partial trajectory data limits full landscape reconstruction but allows effective 1D landscape analysis.
- Findings have implications for experimental studies of biological molecular motors and energy conversion.
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