Computationally Guided Tuning of Amino Acid Configuration Influences the Chiroptical Properties of Supramolecular Peptide-π-Peptide Nanostructures.

Self-assembled supramolecular materials derived from peptidic macromolecules with π-conjugated building blocks are of enormous interest because of their aqueous solubility and biocompatibility. The design rules to achieve tailored optoelectronic properties from these types of materials can be guided by computation and virtual screening rather than intuition-based experimental trial-and-error. Using machine learning, we reported previously that the supramolecular chirality in self-assembled aggregates from VEVAG-π-GAVEV type peptidic materials was most strongly influenced by hydrogen bonding and hydrophobic packing of the alanine and valine residues. Herein, we build upon this idea to demonstrate through molecular-level experimental characterization and all-atom molecular modeling that varying the stereogenic centers of these residues has a profound impact on the optoelectronic properties of the supramolecular aggregates, whereas the variation of stereogenic centers of other residues has only nominal influence on these properties. This study highlights the synergy between computational and experimental insight relevant to the control of chiroptical or other electronic properties associated with supramolecular materials.