Accurate de novo design of hyperstable constrained peptides

Abstract

Summary Naturally occurring, pharmacologically active peptides constrained with covalent crosslinks generally have shapes evolved to fit precisely into binding pockets on their targets. Such peptides can have excellent pharmaceutical properties, combining the stability and tissue penetration of small molecule drugs with the specificity of much larger protein therapeutics. The ability to design constrained peptides with precisely specified tertiary structures would enable the design of shape-complementary inhibitors of arbitrary targets. Here we describe the development of computational methods for de novo design of conformationally-restricted peptides, and the use of these methods to design 15–50 residue disulfide-crosslinked and heterochiral N-C backbone-cyclized peptides. These peptides are exceptionally stable to thermal and chemical denaturation, and twelve experimentally-determined X-ray and NMR structures are nearly identical to the computational models. The computational design methods and stable scaffolds presented here provide the basis for development of a new generation of peptide-based drugs.

Structural and Functional Modeling of Artificial Bioactive Proteins

“…Figures A1 and A2 show that several de novo α-helical and β-sheet peptides reported by Woolfson and co-workers [23][24][25], Quinn et al [47], Schneider et al [48], Griffioen et al [49] and Baker and co-workers [26] exhibit almost identical frequency peaks when compared to the Hecht_α and Hecht_β dataset (Table 1, Figure 1). These distinct α-helical and β-sheet frequency peaks are within the range predicted by Eisenberg et al [45] for α helices (mean = 0.28, range from 0.25-0.31) and β strands (mean = 0.44, range from 0.39-0.50).…”

“…Figure A2. Characteristic frequency peaks of de novo genetically-encodable disulfide-rich peptides and mutants designed by Baker and co-workers [26] were determined using the PRIFT/LSSA method of Cornette et al [27]. Figure A3.…”

“…The overall goal of the paper is to investigate whether the use of standard bioinformatics algorithms is applicable for efficient and accurate structure-function modeling of the synthetic proteins subsets Hecht_α and Hecht_β. The applicability of the presented methodology will be discussed considering de novo protein subsets recently reported by Woolfson and co-workers [4,5,[23][24][25] and Baker and co-workers [1,26].…”

“…Heme binding is relatively easy to achieve with the de novo design since many peptides and proteins have been designed to bind heme [54]. The interaction of the SynSer3 with heme and Fe 2+ in the aa region 16-31 was predicted by the COBEpro method (the epitope/exposed region NDRKNLH, aa [25][26][27][28][29][30][31] and by ISM (L30); Scheme S3 and Table 2, respectively. The list of predicted continuous epitopes for all Hecht_α proteins is shown in the Schemes S1-S15, using the COBEpro method [32].…”

Greedy motif-based approach to parsing large and diverge coiled-coil proteins into domains

“…Over 150 surface proteins found in S. pyogenes, an important human pathogen, binds about 250 human plasma proteins in significant amounts (as measured by enrichment over background plasma) [2]. High-resolution models of the protein-protein interactions enable the design of inhibitors, for example, large L/D-mixed synthetic circular peptides [3]. The majority of these models were created using highresolution data such as NMR or X-ray crystallography, but these datasets remain challenging to produce.…”