RESUMO
Self-assembling peptides are a popular vector for therapeutic cargo delivery due to their versatility, tunability, and biocompatibility. Accurately predicting secondary and supramolecular structures of self-assembling peptides is essential for de novo peptide design. However, computational modeling of such assemblies is not yet able to accurately predict structure formation for many peptide sequences. This review identifies patterns in literature between secondary and supramolecular structures, primary sequences, and applications to provide a guide for informed peptide design. An overview of peptide structures, their applications as nanocarriers, and analytical methods for characterizing secondary and supramolecular structure is examined. A top-down approach is then used to identify trends between peptide sequence and assembly structure from the current literature, including an analysis of the drivers at work, such as local and nonlocal sequence effects and solution conditions.