The self-assembly of proteins into highly ordered nanoscale architectures is a hallmark of biological systems. The sophisticated functions of these molecular machines have inspired the development of methods to engineer self-assembling protein nanostructures; however, the design of multi-component protein nanomaterials with high accuracy remains an outstanding challenge. Here we report a computational method for designing protein nanomaterials in which multiple copies of two distinct subunits co-assemble into a specific architecture. We use the method to design five 24-subunit cage-like protein nanomaterials in two distinct symmetric architectures and experimentally demonstrate that their structures are in close agreement with the computational design models. The accuracy of the method and the number and variety of two-component materials that it makes accessible suggest a route to the construction of functional protein nanomaterials tailored to specific applications.

Accurate design of co-assembling multi-component protein nanomaterials.

Nature provides many examples of self- and co-assembling protein-based molecular machines, including icosahedral protein cages that serve as scaffolds, enzymes, and compartments for essential biochemical reactions and icosahedral virus capsids, which encapsidate and protect viral genomes and mediate entry into host cells. Inspired by these natural materials, we report the computational design and experimental characterization of co-assembling, two-component, 120-subunit icosahedral protein nanostructures with molecular weights (1.8 to 2.8 megadaltons) and dimensions (24 to 40 nanometers in diameter) comparable to those of small viral capsids. Electron microscopy, small-angle x-ray scattering, and x-ray crystallography show that 10 designs spanning three distinct icosahedral architectures form materials closely matching the design models. In vitro assembly of icosahedral complexes from independently purified components occurs rapidly, at rates comparable to those of viral capsids, and enables controlled packaging of molecular cargo through charge complementarity. The ability to design megadalton-scale materials with atomic-level accuracy and controllable assembly opens the door to a new generation of genetically programmable protein-based molecular machines.

/pdf/accurate-design-of-megadalton-scale-two-component-1lykeeyoa8.pdf

Accurate design of megadalton-scale two-component icosahedral protein complexes.

Nature endows life with a wide variety of sophisticated, synergistic, and highly functional protein assemblies. Following Nature’s inspiration to assemble protein building blocks into exquisite nanostructures is emerging as a fascinating research field. Dictating protein assembly to obtain highly ordered nanostructures and sophisticated functions not only provides a powerful tool to understand the natural protein assembly process but also offers access to advanced biomaterials. Over the past couple of decades, the field of protein assembly has undergone unexpected and rapid developments, and various innovative strategies have been proposed. This Review outlines recent advances in the field of protein assembly and summarizes several strategies, including biotechnological strategies, chemical strategies, and combinations of these approaches, for manipulating proteins to self-assemble into desired nanostructures. The emergent applications of protein assemblies as versatile platforms to design a wide variety ...

Protein Assembly: Versatile Approaches to Construct Highly Ordered Nanostructures

Structural Genomics (SG) projects aim to expand our structural knowledge of biological macromolecules, while lowering the average costs of structure determination. We quantitatively analyzed the novelty, cost, and impact of structures solved by SG centers, and contrast these results with traditional structural biology. The first structure from a protein family is particularly important to reveal the fold and ancient relationships to other proteins. In the last year, approximately half of such structures were solved at a SG center rather than in a traditional laboratory. Furthermore, the cost of solving a structure at the most efficient U.S. center has now dropped to one-quarter the estimated cost of solving a structure by traditional methods. However, top structural biology laboratories are much more efficientthan the average, and comparable to SG centers despite working on very challenging structures. Moreover, traditional structural biology papers are cited significantly more often, suggesting greater current impact.

/pdf/the-impact-of-structural-genomics-expectations-and-outcomes-5bfjxu2q3i.pdf

The Impact of Structural Genomics: Expectations and Outcomes - eScholarship

By using DNA sequence information to encode the shapes of DNA origami building blocks, shape-programmable assemblies can be created, with sizes and complexities similar to those of viruses. In nature, large and complex structures such as viruses assemble with ease, but building such large and complex artificial objects remains a grand challenge. Hendrik Dietz and colleagues now show that large and discrete objects can be created efficiently by using DNA sequence information to encode the shapes of individual DNA origami building blocks, and the geometry and details of the interactions between these building blocks to control their copy numbers, positions and orientations within higher-order assemblies. The team create planar rings reaching 350 nanometres in diameter, tubes the size of some bacilli, and three-dimensional polyhedral cages 450 nanometres in diameter, which strikingly illustrate the capability of this method. The technique can in principle be adjusted to create other assemblies that might find use in drug delivery, as scaffolds or for creating complex machine-like objects. Three related papers is this issue report further advances in DNA origami, and all four are summarized in a News & Views. Natural biomolecular assemblies such as molecular motors, enzymes, viruses and subcellular structures often form by self-limiting hierarchical oligomerization of multiple subunits1,2,3. Large structures can also assemble efficiently from a few components by combining hierarchical assembly and symmetry, a strategy exemplified by viral capsids4. De novo protein design5,6,7,8,9 and RNA10,11 and DNA nanotechnology12,13,14 aim to mimic these capabilities, but the bottom-up construction of artificial structures with the dimensions and complexity of viruses and other subcellular components remains challenging. Here we show that natural assembly principles can be combined with the methods of DNA origami15,16,17,18,19,20,21,22,23,24 to produce gigadalton-scale structures with controlled sizes. DNA sequence information is used to encode the shapes of individual DNA origami building blocks, and the geometry and details of the interactions between these building blocks then control their copy numbers, positions and orientations within higher-order assemblies. We illustrate this strategy by creating planar rings of up to 350 nanometres in diameter and with atomic masses of up to 330 megadaltons, micrometre-long, thick tubes commensurate in size to some bacilli, and three-dimensional polyhedral assemblies with sizes of up to 1.2 gigadaltons and 450 nanometres in diameter. We achieve efficient assembly, with yields of up to 90 per cent, by using building blocks with validated structure and sufficient rigidity, and an accurate design with interaction motifs that ensure that hierarchical assembly is self-limiting and able to proceed in equilibrium to allow for error correction. We expect that our method, which enables the self-assembly of structures with sizes approaching that of viruses and cellular organelles, can readily be used to create a range of other complex structures with well defined sizes, by exploiting the modularity and high degree of addressability of the DNA origami building blocks used.

Gigadalton-scale shape-programmable DNA assemblies

Protein crystals have catalytic and materials applications and are central to efforts in structural biology and therapeutic development. Designing predetermined crystal structures can be subtle given the complexity of proteins and the noncovalent interactions that govern crystallization. De novo protein design provides an approach to engineer highly complex nanoscale molecular structures, and often the positions of atoms can be programmed with sub-Å precision. Herein, a computational approach is presented for the design of proteins that self-assemble in three dimensions to yield macroscopic crystals. A three-helix coiled-coil protein is designed de novo to form a polar, layered, three-dimensional crystal having the P6 space group, which has a “honeycomb-like” structure and hexameric channels that span the crystal. The approach involves: (i) creating an ensemble of crystalline structures consistent with the targeted symmetry; (ii) characterizing this ensemble to identify “designable” structures from minima in the sequence-structure energy landscape and designing sequences for these structures; (iii) experimentally characterizing candidate proteins. A 2.1 Å resolution X-ray crystal structure of one such designed protein exhibits sub-Å agreement [backbone root mean square deviation (rmsd)] with the computational model of the crystal. This approach to crystal design has potential applications to the de novo design of nanostructured materials and to the modification of natural proteins to facilitate X-ray crystallographic analysis.

/pdf/computational-design-of-a-protein-crystal-507169qn7q.pdf

X. Jade Qiu

Papers

Computational design of a protein crystal