Molecular Machines Like Myosin Use Randomness to Behave Predictably

Peter Karagiannis, Yoshiharu Ishii, and Toshio Yanagida

We use machines to move, to lift, and to build. In a similar way, cells use machines to grow, to reproduce, and to live. These machines play essential roles in cellular functions such as cell signaling, energy transduction, and motion, to name just a few. Because they operate inside a cell, they are tiny and operate on a physical scale that makes them very different from the manmade, macroscopic objects we normally imagine when we hear the word “machine”. Further, their size and soft structure allows them to be much more dynamic and robust than artificial machines. They work needing very little input, as energy levels not far from average thermal energy (k B T) are sufficient for a given task. 1 This property too contrasts with artificial machines, which work much more rapidly, accurately, and deterministically, but with higher energy demands and less adaptability. To elucidate how molecular machines operate, single molecule techniques have been developed to measure the dynamic behavior of individual biomolecules with an accuracy that can correlate thermal effects on machine function. Understanding the uniqueness of how molecular machines operate and exploiting this mechanism will reveal the strategies used by nature to build its machines and, therefore, new paradigms for how we can build ours.

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