The icosahedron and the dodecahedron are the largest of the Platonic solids, and icosahedral protein structures are widely utilized in biological systems for packaging and transport1,2. There has been considerable interest in repurposing such structures3–5, for example, virus-like particles for the targeted delivery and vaccine design. The ability to design proteins that self assemble into precisely specified, highly ordered icosahedral structures would open the door to a new generation of protein 'containers' that could exhibit properties custom-made for various applications. In this manuscript, we describe the computational design of an icosahedral nano-cage that self-assembles from trimeric building blocks. Electron microscopy images of the designed protein expressed in E. coli reveals a homogenous population of icosahedral particles nearly identical to the design model. The particles are stable in 6.7 M guanidine hydrochloride at up to 80 °C, and undergo extremely abrupt, but reversible, disassembly between 2 M and 2.25 M guanidinium thiocyanate. The icosahedron is robust to genetic fusions: one or two copies of superfolder GFP can be fused to each of the 60 subunits to create highly fluorescent standard candles for light microscopy, and a designed protein pentamer can be placed in the center of each of the twenty pentameric faces to potentially gate macromolecule access to the nanocage interior. Such robust designed nanocages should have considerable utility for targeted drug delivery6, vaccine design7, and synthetic biology8.

Direct electron detectors have made it possible to generate electron density maps at near atomic resolution using cryo-electron microscopy single particle reconstructions. Critical current questions include how best to build models into these maps, how high quality a map is required to generate an accurate model, and how to cross-validate models in a system independent way. We describe a modeling approach that integrates Monte Carlo optimization with local density guided moves, Rosetta all-atom refinement, and real space B-factor fitting, yielding accurate models from experimental maps for three different systems with resolutions 4.5 Å or higher. We characterize model accuracy as a function of data quality, and present a model validation statistic that correlates with model accuracy over the three test systems.

In nature, structural specificity in DNA and proteins is encoded quite differently: in DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen bond networks with atomic accuracy is a milestone for protein design and enables the programming of protein interaction specificity for a broad range of synthetic biology applications.

We describe a procedure for designing proteins with backbones produced by varying the parameters in the Crick coiled coil-generating equations. Combinatorial design calculations identify low-energy sequences for alternative helix supercoil arrangements, and the helices in the lowest-energy arrangements are connected by loop building. We design an antiparallel monomeric untwisted three-helix bundle with 80-residue helices, an antiparallel monomeric right-handed fourhelix bundle, and a pentameric parallel left-handed five-helix bundle. The designed proteins are extremely stable (extrapolated ΔG fold > 60 kilocalories per mole), and their crystal structures are close to those of the design models with nearly identical core packing between the helices. The approach enables the custom design of hyperstable proteins with fine-tuned geometries for a wide range of applications. ‡