Can We Understand the Complex Dynamics of Motor Proteins Using Simple Stochastic Models?

Anatoly B. Kolomeisky

Department of Chemistry, Rice University, Houston, TX 77005-1892, USA

Motor proteins, or molecular motors, are enzyme molecules that convert chemical energy, obtained from the hydrolysis of ATP (adenosine triphosphate) or related compounds, into mechanical work and motion. However, the mechanism of this mechanochemical coupling is still largely unknown. They play a crucial role in many biological processes such as cellular transport, cell compartment organization, cell motility, transcription, protein synthesis, transfer of genetic information, etc. Motor proteins typically move along rigid cytoskeleton filaments (actin filaments and microtubules), or along DNA and RNA molecules. Current experimental methods enable one to measure the biochemical and biophysical properties of motor proteins on a single-molecule basis. Experimental advances strongly stimulated the development of theoretical methods to understand the dynamics of motor proteins. We present a theoretical approach, based on simple discrete stochastic models, that allows calculating explicitly the biophysical properties of motor proteins, such as drift velocities, dispersions and stall forces. We argue that this method provides a very good description of the dynamics of molecular motors, and it allows to uncover the mechanisms underlying the functioning of motor proteins.

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