Peptide ligation chemistry has revolutionized protein science by providing access to homogeneously modified peptides and proteins. However, lipidated polypeptides and integral membrane proteinsan important class of biomoleculesremain enormously challenging to access synthetically owing to poor aqueous solubility of one or more of the fragments under typical ligation conditions. Herein we describe the advent of a reductive diselenide-selenoester ligation (rDSL) method that enables efficient ligation of peptide fragments down to low nanomolar concentrations, without resorting to solubility tags or hybridizing templates. The power of rDSL is highlighted in the efficient synthesis of the FDA-approved therapeutic lipopeptide tesamorelin and palmitylated variants of the transmembrane lipoprotein phospholemman (FXYD1). Lipidation of FXYD1 was shown to critically modulate inhibitory activity against the Na+/K+ pump.

Native chemical ligation (NCL) combined with desulfurization chemistry has revolutionized the way in which large polypeptides and proteins are accessed by chemical synthesis. Herein, we outline the use of flow chemistry for the ligation-based assembly of polypeptides. We also describe the development of a novel photodesulfurization transformation that, when coupled with flow NCL, enables efficient access to native polypeptides on time scales up to 2 orders of magnitude faster than current batch NCL-desulfurization methods. The power of the new ligation-photodesulfurization flow platform is showcased through the rapid synthesis of the 36 residue clinically approved HIV entry inhibitor enfuvirtide and the peptide diagnostic agent somatorelin.

Multivalent ligands offer a powerful approach to obtain high affinity reagents to bind the aggregates that form in neurodegenerative disease. Selectivity for different proteins was achieved by using different linkers to connect the head groups.

Fibrillar protein aggregates are characteristic of neurodegenerative diseases but represent difficult targets for ligand design, because limited structural information about the binding sites is available. Ligand-based virtual screening has been used to develop a computational method for the selection of new ligands for Aβ(1–42) fibrils, and five new ligands have been experimentally confirmed as nanomolar affinity binders. A database of ligands for Aβ(1–42) fibrils was assembled from the literature and used to train models for the prediction of dissociation constants based on chemical structure. The virtual screening pipeline consists of three steps: a molecular property filter based on charge, molecular weight, and logP; a machine learning model based on simple chemical descriptors; and machine learning models that use field points as a 3D description of shape and surface properties in the Forge software. The three-step pipeline was used to virtually screen 698 million compounds from the ZINC15 database. From the top 100 compounds with the highest predicted affinities, 46 compounds were experimentally investigated by using a thioflavin T fluorescence displacement assay. Five new Aβ(1–42) ligands with dissociation constants in the range 20–600 nM and novel structures were identified, demonstrating the power of this ligand-based approach for discovering new structurally unique, high-affinity amyloid ligands. The experimental hit rate using this virtual screening approach was 10.9%.

The development of an iterative one-pot peptide ligation strategy is described that capitalises on the rapid and efficient nature of the diselenide-selenoester ligation reaction, together with photodeselenisation chemistry. This ligation...

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