Synopsis: Molecular Motors Perform Better in Traffic

A new model of molecular motors working in unison finds that motor-motor interactions can boost the efficiency of the system.
Synopsis figure
Courtesy Alberto Imparato/University of Aarhus

Molecular motors are tiny biological machines that turn chemical energy into mechanical motion. Previous research has considered the thermodynamic efficiency of single motors, but often several motors are operating together in the same place. A new theoretical model—presented in Physical Review Letters—explores the consequences of “traffic” interactions between transporting motors. The findings show that, when working at maximum power output, interacting motors can be more efficient than single motors working alone.

Molecular motors perform various tasks, from contracting muscles to maneuvering DNA. An example is kinesin, which carries molecular cargo by walking along cellular structures called microtubules. Thermal fluctuations cause transitions between different chemical states of the motor, while a particular chemical reaction driving the motor biases the transitions such that forward motion becomes more probable than backward motion. But if several kinesin are moving on the same microtubule, their motion will be affected because they can’t “step” on each other.

Natalia Golubeva and Alberto Imparato of the University of Aarhus in Denmark studied how kinesin efficiency at maximum power depends on such traffic interactions. They varied the available chemical energy and calculated the maximum output power per molecule with respect to cargo load. In general, the larger the load, the slower the molecules moved, but small cargo loads could lead to “bumper-to-bumper” traffic, in which the output power behaves differently than for large cargo loads, where the traffic flowed more freely. For certain values of the chemical energy, the efficiency at maximum power was higher for interacting molecules than it would be for noninteracting molecules, and these cases turned out to be in the biologically relevant parameter range. – Michael Schirber


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