The bioactivity of complex organic macrocycles can vary unpredictably with their three-dimensional structural contours. Here, we present a streamlined, programmable and systematic strategy for skeleta...

Peptide macrocycles are promising therapeutics for a variety of disease indications due to their overall metabolic stability and potential to make highly selective binding interactions with targets. Recent advances in covalent macrocycle peptide discovery, driven by phage and mRNA display methods, have enabled the rapid identification of highly potent and selective molecules from large libraires of diverse macrocycles. However, there are currently limited examples of macrocycles that can be used to disrupt protein–protein interactions and even fewer examples that function by formation of a covalent bond to a target protein. In this work, we describe a directed counter-selection method that enables identification of covalent macrocyclic ligands targeting a protein–protein interaction using a phage display screening platform. This method utilizes binary and ternary screenings of a chemically modified phage display library, employing the stable and weakly reactive aryl fluorosulfate electrophile. We demonstrate the utility of this approach using the SARS-CoV-2 spike-ACE2 protein–protein interaction and identify multiple covalent macrocyclic inhibitors that disrupt this interaction. The resulting compounds displayed antiviral activity against live virus that was irreversible after washout due to the covalent binding mechanism. These results highlight the potential of this screening platform for developing covalent macrocyclic drugs that disrupt protein–protein interactions with long lasting effects.

Chiral macrocycles are key to the discovery of new medicines. Their synthesis is, however, challenging and typically requires the often-cumbersome installation of stereochemical features in a linear p...

Macrocycles show high activity for the electrochemical reduction of oxygen in alkaline media. However, even macrocycles with the same metal centers and MN4 active site can vary significantly in activi...

Designing molecular receptors that bind anions in water is a significant challenge, and an even greater difficulty lies in using these receptors to remove anions from water without resorting to the ha...

AI-powered protein design creates macrocycles, leveraging machine learning to generate novel drug candidates and transform molecular engineering approaches.

Synthetic macrocycles are promising therapeutics; however, most high-throughput discovery platforms rely on genetically encoded libraries of large peptide macrocycles, which are typically not optimize...