Selective thiazoline peptide cyclisation compatible with mRNA display and efficient synthesis

Abstract

Peptide display technologies are a powerful method for discovery of new bioactive sequences, but linear sequences are often very unstable in a biological setting. Macrocyclisation of such peptides is beneficial for target affinity, selectivity, stability, and cell permeability. However, macrocyclisation of a linear hit is unreliable and requires extensive structural knowledge. Genetically encoding macrocyclisation during the discovery process is a better approach, and so there is a need for diverse cyclisation options that can be deployed in the context of peptide display techniques such as mRNA display. In this work we show that meta-cyanopyridylalanine ( mCNP) can be ribosomally incorporated into peptides, forming a macrocycle in a spontaneous and selective reaction with an N-terminal cysteine generated from bypassing the initiation codon in translation. This reactive amino acid can also be easily incorporated into peptides during standard Fmoc solid phase peptide synthesis, which can otherwise be a bottleneck in transferring from peptide discovery to peptide testing and application. We demonstrate the potential of this new method by discovery of macrocyclic peptides targeting influenza haemagglutinin, and molecular dynamics simulation indicates the mCNP cross-link stabilises a beta sheet structure in a representative of the most abundant cluster of active hits. Cyclisation by mCNP is also shown to be compatible with thioether macrocyclisation at a second cysteine to form bicycles of different architectures, provided that cysteine placement reinforces selectivity, with this bicyclisation happening spontaneously and in a controlled manner during peptide translation. Our new approach generates macrocycles with a more rigid cross-link and with better control of regiochemistry when additional cysteines are present, opening these up for further exploitation in chemical modification of in vitro translated peptides, and so is a valuable addition to the peptide discovery toolbox.