@article {7507,
	title = {Discrete Step Sizes of Molecular Motors Lead to Bimodal Non-Gaussian Velocity Distributions under Force},
	journal = {Phys. Rev. Lett.},
	volume = {117},
	year = {2016},
	month = {8 Aug, 2016},
	pages = {078101},
	abstract = {
	Fluctuations in the physical properties of biological machines are inextricably linked to their functions. Distributions of run lengths and velocities of processive molecular motors, like kinesin-1, are accessible through single-molecule techniques, but rigorous theoretical models for these probabilities are lacking. Here, we derive exact analytic results for a kinetic model to predict the resistive force (F)-dependent velocity [P(v)] and run length [P(n)] distribution functions of generic finitely processive molecular motors. Our theory quantitatively explains the zero force kinesin-1 data for both\&nbsp;P(n)\&nbsp;and\&nbsp;P(v)\&nbsp;using the detachment rate as the only parameter. In addition, we predict the\&nbsp;F\&nbsp;dependence of these quantities. At nonzero\&nbsp;F,\&nbsp;P(v)\&nbsp;is non-Gaussian and is bimodal with peaks at positive and negative values of\&nbsp;v, which is due to the discrete step size of kinesin-1. Although the predictions are based on analyses of kinesin-1 data, our results are general and should hold for any processive motor, which walks on a track by taking discrete steps.

},
	url = {https://doi.org/10.1103/PhysRevLett.117.078101},
	author = {Huong T. Vu and Chakrabarti, Shaon and Hinczewski, Michael and D. Thirumalai}
}
