Revealing the effect of stereocontrol on intermolecular interactions between abiotic, sequence-defined macromolecules and a ligand

The development of precision polymer synthesis gives access to a broad library of abiotic structures, where monomers are placed in particular positions in macromolecule chains. Those structures are expected to exhibit folding characteristics for biotic macromolecules and inherit similar functionalities. However, engineering complex properties into abiotic polymers remains beyond reach due to the vast sequence space and multiple variables that impede rational structure design. To develop sophisticated functions in abiotic macromolecules, it is necessary to provide effective tools to study their conformation and molecular interactions. In this work, we investigated various methods to analyse receptor-like features of sequence-defined oligourethanes towards the bisphenol A ligand. We evaluated molecular dynamic simulations and experimental techniques, i.e., nuclear magnetic resonance, circular dichroism and fluorescence spectroscopy, in studies of intermolecular interactions between model oligomers and the ligand. We tested the accuracy of methods to reveal the effect of discrete changes in stereochemical arrangements on the structure of formed complexes and binding strength. Based on atomistic details delivered by computational studies, we found that formed complexes display high structural diversity depending on the sequence of stereocenters. However, due to the dynamic nature of studied systems, they are challenging to characterise using common experimental methods. Among tested techniques, fluorescence spectroscopy data fitted to the Stern-Volmer equation provided the most consistent data with the calculations that enabled verification of the simulation methodology. The described computational strategy is an efficient tool for screening the libraries of various sequences to facilitate the engineering of host-guest systems based on abiotic sequence-defined polymers. Using computational capacity reduces the amount of experimental work, generated chemical waste, and time to get an outcome increasing the feasibility of programming receptor-like functionalities in non-natural macromolecules.