Selective molecular recognition, biological models

In order to address the characteristics of biological models, we have to first define the basic principles of biological systems that a supramolecular model may mimic. Among the most important are selective molecular recognition of a molecular entity selective and highly accelerated modification of a substrate (typieal role of enzymes) compartmentalization and selective translocation of chemical species across boundaries (typieal role of biomembranes) harvesting and transformation of energy and self-replication. 

We wished to develop a macroscopic model of the interactions between molecular ligands and receptors. Molecular recognition is a broad subject that describes selective assembly in chemistry and biology, with examples from DNA-protein complex formation to asymmetric catalysis. The principle behind molecular recognition dictates that the molecules that mate have complementary shapes and interfacial characteristics. Our extension of this principle to the mesoscale involved the self-assembly of objects that matched both... 

The first practical application for cyclophanes was found in host-guest chemistry [4]. Molecular recognition of ions and neutral molecules in functionalized cavities of cyclophanes has been demonstrated for numerous examples. Here, special interest has been attracted by complexes in water since it can directly model molecular recognition events in biological systems. The development of suitable water soluble hosts with high binding selectivity is an active field of research [5] that has recently been reviewed [6]. 

The quantitative comparison of the optimized 3D structure of a selected set of ligands allows the development of their minimal 3D structural requirements for the recognition and activation of the biological target, that is, the pharmacophore hypothesis, and gives a sound 3D rationale to the available SARs [21]. A more complete and mechanistically relevant approach to the development of the 3D pharmacophore consists in its translation into a numerical molecular descriptor that quantifies the molecular-pharmacophore similarity-diversity for computational QSAR modeling [21,41]. 

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