The computational design of an extremely stable icosahedral self-assembling protein nanocage is presented; the icosahedron should be useful for applications ranging from calibrating fluorescence microscopy to drug delivery. Icosahedral protein structures are widely utilized in biological systems for packaging and transport, and icosahedral viruses such as adenoviruses have been widely repurposed as vectors to package vaccines and for targeted delivery of therapeutics. Here David Baker and colleagues use computational design to produce icosahedral nanocage particles via self-assembly from trimeric building blocks. The particles are highly stable and robust to genetic fusions. The icosahedron is the largest of the Platonic solids, and icosahedral protein structures are widely used in biological systems for packaging and transport1,2. There has been considerable interest in repurposing such structures3,4,5 for applications ranging from targeted delivery to multivalent immunogen presentation. 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 with properties custom-tailored to specific applications. Here we describe the computational design of a 25-nanometre icosahedral nanocage that self-assembles from trimeric protein building blocks. The designed protein was produced in Escherichia coli, and found by electron microscopy to assemble into a homogenous population of icosahedral particles nearly identical to the design model. The particles are stable in 6.7 molar guanidine hydrochloride at up to 80 degrees Celsius, and undergo extremely abrupt, but reversible, disassembly between 2 molar and 2.25 molar guanidinium thiocyanate. The icosahedron is robust to genetic fusions: one or two copies of green fluorescent protein (GFP) can be fused to each of the 60 subunits to create highly fluorescent ‘standard candles’ for use in light microscopy, and a designed protein pentamer can be placed in the centre of each of the 20 pentameric faces to modulate the size of the entrance/exit channels of the cage. Such robust and customizable nanocages should have considerable utility in targeted drug delivery6, vaccine design7 and synthetic biology8.

New detector technology has improved the resolution of cryo-electron microscopy (cryo-EM), but tools for structure determination from high-resolution maps have lagged behind. DiMaio et al. report structure determination from high-resolution cryo-EM maps using a homologous structure as a starting model. Also in this issue, Wang et al. describe a de novo approach for structure determination that does not require a starting model. We describe a general approach for refining protein structure models on the basis of cryo-electron microscopy maps with near-atomic resolution. The method integrates Monte Carlo sampling with local density-guided optimization, Rosetta all-atom refinement and real-space B-factor fitting. In tests on experimental maps of three different systems with 4.5-Å resolution or better, the method consistently produced models with atomic-level accuracy largely independently of starting-model quality, and it outperformed the molecular dynamics–based MDFF method. Cross-validated model quality statistics correlated with model accuracy over the three test systems.

Building with designed proteins: General design principles for protein interaction specificity are challenging to extract. DNA nanotechnology, on the other hand, has harnessed the limited set of hydrogen-bonding interactions from Watson-Crick base-pairing to design and build a wide range of shapes. Protein-based materials have the potential for even greater geometric and chemical diversity, including additional functionality. Boyken et al. designed a class of protein oligomers that have interaction specificity determined by modular arrays of extensive hydrogen bond networks (see the Perspective by Netzer and Fleishman). They use the approach, which could one day become programmable, to build novel topologies with two concentric rings of helices. Science , this issue p. 680 ; see also p. 657

Building with alphahelical coiled coils: Understanding how proteins fold into well-defined three-dimensional structures has been a longstanding challenge. Increased understanding has led to increased success at designing proteins that mimic existing protein folds. This raises the possibility of custom design of proteins with structures not seen in nature. Thomson et al. describe the design of channelcontaining α-helical barrels, and Huang et al. designed hyperstable helical bundles. Both groups used rational and computational design to make new protein structures based on α-helical coiled coils but took different routes to reach different target structures. Science , this issue p. 485 , p. 481