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Reduced-order models for the dynamics of superparamagnetic nanoparticles interacting with cargoes transported by kinesins

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Abstract

Magnetic nanoparticles are widely used for different applications in biological systems. Multiphysics models that capture the dynamics of both magnetic nanoparticles and biological phenomena are computationally expensive. We develop a novel reduced-order model (ROM) for the dynamics of magnetic nanoparticles to study the interaction of superparamagnetic nanoparticles with cellular nanotransport upon delivery of these particles into cells. Superparamagnetic nanoparticles can form chain-like structures in the presence of external magnetic fields. Such chains influence the nanotransport inside cells. We model the viscous and magnetic forces on the nanoparticles, and the formation of aggregates/structures composed of nanoparticles to construct our novel ROM. Further, we model the stochastic nanotransport coupled with the dynamics of the magnetic nanoparticles. We use our novel ROM to characterize the stochastic motion of a kinesin in the presence of magnetic nanoparticles by determining the force acting on cargoes for different aggregate shapes and sizes (without having to solve the full-order dynamics every time). The ROM coupled with kinesin model allows the quantification of the decreases in processivity of kinesin and in its average velocity under external loads caused by chains of superparamagnetic nanoparticles.

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Acknowledgements

Funding was provided by Division of Civil, Mechanical and Manufacturing Innovation (Grant No. 1161874).

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  1. College of Engineering, University of Michigan, Ann Arbor, USA

    Ehsan Mirzakhalili, Woochul Nam & Bogdan I. Epureanu

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  1. Ehsan Mirzakhalili
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  3. Bogdan I. Epureanu
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Correspondence to Bogdan I. Epureanu.

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Mirzakhalili, E., Nam, W. & Epureanu, B.I. Reduced-order models for the dynamics of superparamagnetic nanoparticles interacting with cargoes transported by kinesins. Nonlinear Dyn 90, 425–442 (2017). https://doi.org/10.1007/s11071-017-3673-0

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