Directional stepping model for yeast dynein: Longitudinal- and side- step distributions

Abstract

We deduce the directional step distribution of yeast dynein motor protein on the microtubule surface by combing intrinsic features of the dynein and microtubule. These include the probability distribution of the separation vector between the two microtubule binding domains (MTBDs), the angular probability distribution of a single MTBD translation, the existence of a microtubule seam defect, microtubule binding sites, and theoretical extension that accounts for a load force on the motor. Our predictions are in excellent accord with the measured longitudinal step size distributions at various load forces. Moreover, we predict the side-step distribution and its dependence on longitudinal load forces, which shows a few surprising features. First, the distribution is broad. Second, in the absence of load, we find a small right-hand bias. Third, the side-step bias is susceptible to the longitudinal load force; it vanishes at a load equal to the motor stalling force and changes to a left-hand bias above that value. Fourth, our results are sensitive to the ability of the motor to explore the seam several times during its walk. While available measurements of side-way distribution are limited, our findings are amenable to experimental check and, moreover, suggest a diversity of results depending on whether the microtubule seam is viable to motor sampling.\n\nSignificance StatementThe function of microtubule (MT) associated protein motors, kinesin and dynein, is essential for a myriad of intracellular processes. Different measurements on yeast cytoplasmic-dynein stepping characteristics appear to be unrelated to each other. We provide a unified physical-statistical model that combines these seemingly independent features with a theoretical expression that accounts for the exertion of a longitudinal load force, to yield the longitudinal step distribution at various load forces. The latter is in excellent accord with the measured distributions. Moreover, we deduce the side-step distribution, which surprisingly is susceptible to longitudinal load forces and comprises a right or left bias. This side-way bias is consistent with observations of helical motion of a nanoparticle carried by a number of motors.