Discrete Step Sizes of Molecular Motors Lead to Bimodal Non-Gaussian Velocity Distributions under Force
Year: 2016
Type: article
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.
Source: Physical Review Letters
Language: English
Subfield: Cell Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2318671158