PNNL

Abstract

Peptide drugs offer many advantages over traditional small-molecule therapeutics, including enhanced specificity and reduced off-target effects.  Constrained peptides are commonly employed by nature as signaling molecules or toxins, and the incorporation of multiple disulfide covalent crosslinks between pairs of cysteine residues is thought to be responsible for the stability and potent drug-like properties of these molecules.  Knottins and short-chain scorpion toxins are two well-characterized groups within this protein family; each is demarcated by conserved structural motifs and highly-conserved disulfide bonds. However, the ability to generate stable structures adopting a wide range of specified sizes and shapes not observed in nature will be necessary to unlock the full pharmacological potential of peptide-based drugs.  Working towards this goal, we previously reported a computational method for the de novo design of genetically encodable cysteine-rich peptides of various topologies, which were validated by experiments. Here, we describe two extensions to the above methodology. First, we present an efficient and generalizable method for the production of de novo designed, disulfide-rich peptides via genetic fusion to DsbC and expression in the cytoplasm of Escherichia coli.   This is demonstrated by producing two peptides with divergent structures and sequences: a mixed a/ß topology with a helix packing against a three-stranded antiparallel ß-sheet stabilized by three disulfide bonds (gHEEE_02), and a helix-turn-helix topology containing a single disulfide bond adjacent to the main-chain termini (gHH_02). The efficacy of the expression system to successfully fold peptides as designed was confirmed by determining the structure for these two peptides using solution NMR spectroscopy.  These two new NMR structures confirm the design accuracy for two additional de novo designed peptides that were not previously validated by full structural determination. Second, motivated by the observation that some of the computational designs did not appear to fold as expected, we developed a computational strategy based on molecular dynamics (MD) simulations to identify misfolded designs prior to synthesis and propose rescue mutations to improve these designs.