Preparation of Semisynthetic Peptides Macrocycles Using Split Inteins

Preparation of Bacterial Cell-Surface Displayed Semisynthetic Cyclic Peptides

Semisynthetic cyclic peptides bearing both non-proteinogenic and genetically encoded amino acids are excellent ligands for peptide-based drug discovery. While semisynthesis expands the chemical space, genetic encoding allows access to a large library via randomization at the nucleic acid level. Selection of novel binders of such macrocyclic ligands requires linking their genotype to phenotype. In this chapter, we report a bacterial cell-surface display system to present cyclic peptides composed of synthetic and genetically encoded fragments. The synthetic fragment along with the split intein partner and an aminooxy moiety is ligated and cyclized with the recombinant backbone containing an unnatural amino acid by protein trans-splicing and intramolecular oxime ligation, respectively. A pH-shift protocol was applied to accelerate on surface cyclization. This method will enable generation of semisynthetic cyclic peptide libraries and their selection by fluorescence-activated cell sorting.

Benchmark of Generic Shapes for Macrocycles

Macrocycles target proteins that are otherwise considered undruggable because of a lack of hydrophobic cavities and the presence of extended featureless surfaces. Increasing efforts by computational chemists have developed effective software to overcome the restrictions of torsional and conformational freedom that arise as a consequence of macrocyclization. Moloc is an efficient algorithm, with an emphasis on high interactivity, and has been constantly updated since 1986 by drug designers and crystallographers of the Roche biostructural community. In this work, we have benchmarked the shape-guided algorithm using a dataset of 208 macrocycles, carefully selected on the basis of structural complexity. We have quantified the accuracy, diversity, speed, exhaustiveness, and sampling efficiency in an automated fashion and we compared them with four commercial (Prime, MacroModel, molecular operating environment, and molecular dynamics) and four open-access (experimental-torsion distance geometry with additional “basic knowledge” alone and with Merck molecular force field minimization or universal force field minimization, Cambridge Crystallographic Data Centre conformer generator, and conformator) packages. With three-quarters of the database processed below the threshold of high ring accuracy, Moloc was identified as having the highest sampling efficiency and exhaustiveness without producing thousands of conformations, random ring splitting into two half-loops, and possibility to interactively produce globular or flat conformations with diversity similar to Prime, MacroModel, and molecular dynamics. The algorithm and the Python scripts for full automatization of these parameters are freely available for academic use.