(165d) Structural Evaluation of a De Novo Coassembling ?-Sheet Peptide Nanofiber

Biomaterials based on the spontaneous assembly of peptides are useful for biotechnological applications such as tissue engineering and regenerative medicine. Engineering these peptide assemblies requires a deep understanding of the relationship between sequence and structure in the peptide assembly process. Solid-state nuclear magnetic resonance (NMR) spectroscopy allows us to gain insight into the structural arrangement of peptide assemblies. However, we have detected inconsistencies between the intended molecular designs and the NMR structural evaluation of existing peptide assemblies that were designed using heuristics-based approaches. To illustrate, the King-Webb and CATCH peptides have been found to be structurally heterogeneous, containing both parallel and antiparallel β-sheet content, despite both peptides being targeted to form antiparallel β-sheets. To improve upon existing designs, we have recently developed a peptide coassembly design (PepCAD) algorithm that uses molecular dynamics simulations to search for pairs of coassembling β-sheet peptides that form nanofibers. Coassembling β-sheet peptides are a route to control the formation of functional biomaterials because they can be designed to coassemble only when mixed and resist self-assembly when isolated in a single peptide solution. Preliminary biophysical measurements from transmission electron microscopy (TEM) and Fourier-transform infrared spectroscopy (FTIR), as well as 1D ¹³C NMR experiments, suggest that a de novo peptide design from our algorithm may exhibit a higher structural order than previous coassembling peptide designs. This promising design will be the subject of this structural evaluation study. We will also combine computational predictions of structure with NMR experimental design to quickly narrow down the nanofiber structure. Structural evaluation can be a bottleneck in peptide assembly studies because of multiple structural possibilities in a peptide nanofiber sample. Ongoing work is on modeling the multiple structural possibilities using atomistic simulations and building residue contact charts to aid in selecting possible ¹³C and ¹⁵N labels to isotopically enrich samples. By combining the computational predictions of coassembly with NMR knowledge, we wish to evaluate the coassembling peptide nanofiber structure more easily, streamlining efforts to identify future coassembling β-sheet peptides that form intended structures.