Rationally seeded computational protein design

Abstract Computational protein design is advancing rapidly. Here we describe efficient routes to two families of α-helical-barrel proteins with central channels that bind small molecules. The designs are seeded by the sequences and structures of defined de novo oligomeric barrel-forming peptides. Adjacent helices are connected using computational loop building. For targets with antiparallel helices, short loops are sufficient. However, targets with parallel helices require longer connectors; namely, an outer layer of helix-turn-helix-turn-helix motifs that are packed onto the barrels computationally. Throughout these pipelines, residues that define open states of the barrels are maintained. This minimises sequence sampling and accelerates routes to successful designs. For each of 6 targets, just 2 – 6 synthetic genes are made for expression in E. coli . On average, 80% express to give soluble monomeric proteins that are characterized fully, including high-resolution structures for most targets that match the seed structures and design models with high accuracy.