  Actin is a globular protein which forms long filaments in the eukaryotic
cytoskeleton, whose roles in cell function include structural support,
contractile activity to intracellular signalling. We model actin filaments as
two chains of one-dimensional binary-state semi-totalistic automaton arrays to
describe hypothetical signalling events therein. Each node of the actin
automaton takes state `0' (resting) or `1' (excited) and updates its state in
discrete time depending on its neighbour's states. We analyse the complete rule
space of actin automata using integral characteristics of space-time
configurations generated by these rules and compute state transition rules that
support travelling and mobile localizations. Approaches towards selection of
the localisation supporting rules using the global characteristics are
outlined. We find that some properties of actin automata rules may be predicted
using Shannon entropy, activity and incoherence of excitation between the
polymer chains. We also show that it is possible to infer whether a given rule
supports travelling or stationary localizations by looking at ratios of excited
neighbours are essential for generations of the localizations. We conclude by
applying biomolecular hypotheses to this model and discuss the significance of
our findings in context with cell signalling and emergent behaviour in cellular
computation.
