title: Predicting the stochastic guiding of kinesin-driven microtubules in microfabricated tracks: a statistical-mechanics-based modeling approach.
abstract: Directional control of microtubule shuttles via microfabricated tracks is key to the development of controlled nanoscale mass transport by kinesin motor molecules. Here we develop and test a model to quantitatively predict the stochastic behavior of microtubule guiding when they mechanically collide with the sidewalls of lithographically patterned tracks. By taking into account appropriate probability distributions of microscopic states of the microtubule system, the model allows us to theoretically analyze the roles of collision conditions and kinesin surface densities in determining how the motion of microtubule shuttles is controlled. In addition, we experimentally observe the statistics of microtubule collision events and compare our theoretical prediction with experimental data to validate our model. The model will direct the design of future hybrid nanotechnology devices that integrate nanoscale transport systems powered by kinesin-driven molecular shuttles.
authors.affiliation: Department of Electrical Engineering, National Taiwan University, Taipei 106, Taiwan.
authors.forename: Chih-Tin
authors.initials: CT
authors.lastname: Lin
authors.forename: Edgar
authors.initials: E
authors.lastname: Meyhofer
authors.forename: Katsuo
authors.initials: K
authors.lastname: Kurabayashi
mesh_terms: D000465:Algorithms; D005656:Fungal Proteins / Q000378:metabolism; D006801:Humans; D016547:Kinesins / Q000378:metabolism*; D055616:Microtechnology / Q000379:methods*; D008870:Microtubules / Q000502:physiology*; D008954:Models, Biological; D009038:Motion; D009492:Neurospora crassa; D011336:Probability; D013269:Stochastic Processes
chemical_list: D005656:Fungal Proteins; D016547:Kinesins