As part of the artMotor project, we want to investigate how (artificial) biological motors walking along a track, consuming proteins in the process, work, by analysis of a (self-developed) coarse grained model using rigid-body dynamics to describe the dynamical properties of such motors. The dynamical equation used is a set of Langevin equations describing the translational and rotational degrees of freedom, connected with rate equations for chemical state changes due to the (implicit) interaction with 'food' proteins.
Goal, in particular, is to analyze which parameters of the model, and thus which elements of the motor/track, affect most the speed and processivity of the motors walking. For a motor to be able to walk, one has to introduce an asymmetry into the system, e.g. in the form of a 'information machine', that allows for processive, i.e. directed movement and not just diffusion. An information machine is e.g. a logical check which allows for a part of the motor to unbind from the track only if this part corresponds to a 'backwards' position, by e.g. modifying the rates of state change.
Goal is further to investigate whether this information processing can be incorporated into the model more 'naturally' by utilizing more intrinsic asymmetries of the motor and track system. Information processing, or driving the system into a nonequilibrium state using logical operations, is always necessary to create processive movement from an initially thermal system. However, it is interesting to find out how nature is able to process information without a direct logical if operation, but baking it into the dynamics, which we want propose ideas and check whether they work (e.g. the rate of state change for the chemical processing of the 'food'-proteins in dependence of specific forces/force directions acting on the motor).