Stepping statistics in molecular motors
- lessons from simple models
by
DrMartin Lindén(Uppsala University)
→
Europe/Stockholm
FB55
FB55
Description
Motor proteins are molecular motors that convert chemical energy, for
example ATP or ions flow through a membrane potential, into mechanical
work. Motor proteins play important roles in many cellular processes,
such as intracellular transport, bacterial motility, or respiration.
They are also interesting for future applications in nano technology,
and from a physics point of view, as examples of non-equilibrium
systems whose kinetics can be studies at the single molecule level.
To understand in detail how different motor proteins work has proven a
major challenge. Theoretical modelling of the statistical properties
of single molecule data, for example from trapping experiments where
single motors step along molecular tracks, is one possibility to gain
further insight.
We have studied the statistical properties of simple Markov models for
stepping motor proteins, and come up with two interesting results.
First, we have shown that steps and dwell times observed in stepping
experiments can be correlated, even in very simple models. Second, we
have derived a symmetry property for the waiting time distributions in
reversible motors, that can be used to extract the free energy per cycle
directly from stepping trajectories. To illustrate our results, we
analyze recent stepping data from the bacterial flagellar motor, and
discuss the implications for efficiency and reversibility for the force
generating subunits.
