학술논문
Discrete step sizes of molecular motors lead to bimodal non-Gaussian velocity distributions under force
Document Type
Working Paper
Source
Phys. Rev. Lett. 117, 078101 (2016)
Subject
Language
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, yet there is lack a rigorous theoretical model for these probabilities up to now. 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 that take forward and backward steps on a track. Our theory quantitatively explains the zero force kinesin-1 data for both $P(n)$ and $P(v)$ using the detachment rate as the only parameter, thus allowing us to obtain the variations of these quantities under load. At non-zero $F$, $P(v)$ is non-Gaussian, and is bimodal with peaks at positive and negative values of $v$. The prediction that $P(v)$ is bimodal is a consequence of the discrete step-size of kinesin-1, and remains even when the step-size distribution is taken into account. 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.
Comment: 30 pages, 14 figures
Comment: 30 pages, 14 figures