Quantifying Interactions and Solvent Effects Using Molecular Balances and Model Complexes.

Abstract

Where the basic units of molecular chemistry are the bonds within molecules, supramolecular chemistry is based on the interactions that occur between molecules. Understanding the "how" and "why" of the processes that govern molecular self-assembly remains an open challenge to the supramolecular community. While many interactions are readily examined in silico through electronic structure calculations, such insights may not be directly applicable to experimentalists. The practical limitations of computationally accounting for solvation is perhaps the largest bottleneck in this regard, with implicit solvation models failing to comprehensively account for the specific nature of solvent effects and explicit models incurring a prohibitively high computational cost. Since molecular recognition processes usually occur in solution, insight into the nature and effect of solvation is imperative not only for understanding these phenomena but also for the rational design of systems that exploit them.Molecular balances and supramolecular complexes have emerged as useful tools for the experimental dissection of the physicochemical basis of various noncovalent interactions, but they have historically been underexploited as a platform for the evaluation of solvent effects. Contrasting with large biological complexes, smaller synthetic model systems enable combined experimental and computational analyses, often facilitating theoretical analyses that can work in concert with experiment.Our research has focused on the development of supramolecular systems to evaluate the role of solvents in molecular recognition, and further characterize the underlying mechanisms by which molecules associate. In particular, the use of molecular balances has provided a framework to measure the magnitude of solvent effects and to examine the accuracy of solvent models. Such approaches have revealed how solvation can modulate the electronic landscape of a molecule and how competitive solvation and solvent cohesion can provide thermodynamic driving forces for association. Moreover, the use of simple model systems facilitates the interrogation and further dissection of the physicochemical origins of molecular recognition. This tandem experimental/computational approach has married less common computational techniques, like symmetry adapted perturbation theory (SAPT) and natural bonding orbital (NBO) analysis, with experimental observations to elucidate the influence of effects that are difficult to resolve experimentally (e.g., London dispersion and electron delocalization).