In order to be able to evaluate the potential of complex NVNs in a biomimetic context, the alkaline phosphatase/FDP reaction model was extended. Transition from a compact geometry (a single spherical container) to a structured geometry (several spherical containers connected by nanotubes) in NVNs induces the rate of the dephosphorylation reaction to display wavelike properties. The reaction dynamics can be directly influenced by tuning the geometry of the network. If in this system an enzyme is introduced into a terminal node of the network, it diffuses into neighboring nodes through the interconnecting nanotubes (Fig. 8E–F). The directionality of enzyme SC 79 is thus controlled through establishing a concentration gradient. High initial concentration is achieved locally by injecting enzyme into a container, and a gradient is maintained by introducing “dilution” containers, where the migration of enzyme to the next node is hindered by the reduced probability of finding the entrance to the connecting nanotube [43]. A gradients in solvent composition is also known to affect enzyme diffusion [57]. In Fig. 8, all the nodes except the enzyme-containing node bear stocktickerFDP, which becomes fluorescent when converted to fluorescein and can thus be monitored by fluorescence microscopy. The temporal pattern of front propagation as well as the rate of reaction was dependent on geometry of the network [59]. More extensive theoretical studies on both diffusion and reaction phenomena in similar networks have been performed, showing fascinating and non-intuitive behavior on front propagation and reaction optimization [45] and [40].
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