Pattern Generation and Information Transfer through a Liquid/Liquid Interface in 3D Constitutional Dynamic Networks...

The immense discriminative capacity of the human olfactory chemosensory systems relies on the generation of a combinatorial signal in response to the interaction of a particular odorant molecule with many different olfactory receptors. In this work, we report the generation of distributional signals by the action of particular effectors, here metal cations, on dynamic covalent libraries (DCLs) of receptor molecules, here ligands for metal cations. Different effectors are discriminated by the formation of different constitutional distributions, which result from the adaptation of the DCL to the action of a particular cation effector through the selection and exchange of components. Compartmentalization by operation in a system of immiscible solvents (here water and chloroform) results in a 3D constitutional dynamic network (CDN), effecting distributional signal and information transfer between two domains, through the interface from the "writing" input phase (the IN-phase) and the "reading" output phase (the OUT-phase). Here, it is not the selectivity of a specific recognition process between a particular DCL member and a given effector that is key to the information processing, but the change in the distribution of the components and constituents, a dynamic pattern or fingerprint, induced in one phase in response to interaction with a given effector binding and transmitted to the other phase by component and constituent exchange across the phase boundary. Finally, the pattern recognition techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA) were successfully applied to analyze the output generated by the action of different effectors on the higher order [5 × 5] DCL. Discrimination between different effectors was characterized by specific domains. Such data processing also opens the way toward extension to much larger DCLs.