• Expanding protein nanocages through designed symmetry-breaking
  Matdes
  Sangmin Lee, Ryan Kibler, Quinton Dowling, Yang Hsia, Neil King, David Baker. IPD Website, 2024 | doi:N/A
  
  Abstract

  Polyhedral protein nanocages have had considerable success as vaccine platforms (1–3) and are promising vehicles for biologics delivery (4–7). Hence there is considerable interest in designing larger and more complex structures capable of displaying larger numbers of antigens or packaging larger cargos. However, the regular polyhedra are the largest closed structures in which all subunits have identical local environments (8–11), and thus accessing larger and more complex closed structures requires breaking local symmetry. Viruses solve this problem by placing chemically distinct but structurally similar chains in unique environments (pseudosymmetry) (12) or utilizing identical subunits that adopt different conformations in different environments (quasisymmetry) (13–15) to access higher triangulation (T) number (13) structures with larger numbers of subunits and interior volumes. A promising route to designing larger and more complex nanocages is to start from regular polyhedral nanocages (T=1) constructed from a symmetric homotrimeric building block, isolate cyclic arrangements of these building blocks by substituting in pseudosymmetric heterotrimers, and then build T=4 and larger structures by combining these with additional homo- and heterotrimers. Here we provide a high-level geometric overview of this design approach to illustrate how tradeoffs between design diversity and design economy can be used to achieve different design outcomes, as demonstrated experimentally in two accompanying papers, Lee et al (16) and Dowling et al (17)

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• Fast and versatile sequence-independent protein docking for nanomaterials design using RPXDock
  Matdes Methods Nanoparticles Lab-led
  Sheffler W, Yang EC, Dowling Q, Hsia Y, Fries CN, Stanislaw J, Langowski MD, Brandys M, Li Z, Skotheim R, Borst AJ, Khmelinskaia A, King NP, Baker D.
  PLoS Comput Biol, 2023 | doi:10.1371/journal.pcbi.1010680
  
  Abstract

  Computationally designed multi-subunit assemblies have shown considerable promise for a variety of applications, including a new generation of potent vaccines. One of the major routes to such materials is rigid body sequence-independent docking of cyclic oligomers into architectures with point group or lattice symmetries. Current methods for docking and designing such assemblies are tailored to specific classes of symmetry and are difficult to modify for novel applications. Here we describe RPXDock, a fast, flexible, and modular software package for sequence-independent rigid-body protein docking across a wide range of symmetric architectures that is easily customizable for further development. RPXDock uses an efficient hierarchical search and a residue-pair transform (RPX) scoring method to rapidly search through multidimensional docking space. We describe the structure of the software, provide practical guidelines for its use, and describe the available functionalities including a variety of score functions and filtering tools that can be used to guide and refine docking results towards desired configurations.

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• Top-down design of protein architectures with reinforcement learning
  Matdes Methods Nanoparticles Machine Learning
  Lutz ID, Wang S, Norn C, Courbet A, Borst AJ, Zhao YT, Dosey A, Cao L, Xu J, Leaf EM, Treichel C, Litvicov P, Li Z, Goodson AD, Rivera-Sánchez P, Bratovianu AM, Baek M, King NP, Ruohola-Baker H, Baker D.
  Science, 2023 | doi:10.1126/science.adf6591
  
  Abstract

  As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a “top-down” reinforcement learning-based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo-electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.

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• Computational design of mechanically coupled axle-rotor protein assemblies
  Matdes Methods Rosetta
  Courbet A, Hansen J, Hsia Y, Bethel N, Park YJ, Xu C, Moyer A, Boyken SE, Ueda G, Nattermann U, Nagarajan D, Silva DA, Sheffler W, Quispe J, Nord A, King N, Bradley P, Veesler D, Kollman J, Baker D.
  Science, 2022 | doi:10.1126/science.abm1183
  
  Abstract

  Natural molecular machines contain protein components that undergo motion relative to each other. Designing such mechanically constrained nanoscale protein architectures with internal degrees of freedom is an outstanding challenge for computational protein design. Here we explore the de novo construction of protein machinery from designed axle and rotor components with internal cyclic or dihedral symmetry. We find that the axle-rotor systems assemble in vitro and in vivo as designed. Using cryo-electron microscopy, we find that these systems populate conformationally variable relative orientations reflecting the symmetry of the coupled components and the computationally designed interface energy landscape. These mechanical systems with internal degrees of freedom are a step toward the design of genetically encodable nanomachines.

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• Designed proteins assemble antibodies into modular nanocages
  Matdes Nanoparticles Antibodies
  Divine R, Dang HV, Ueda G, Fallas JA, Vulovic I, Sheffler W, Saini S, Zhao YT, Raj IX, Morawski PA, Jennewein MF, Homad LJ, Wan YH, Tooley MR, Seeger F, Etemadi A, Fahning ML, Lazarovits J, Roederer A, Walls AC, Stewart L, Mazloomi M, King NP, Campbell DJ, McGuire AT, Stamatatos L, Ruohola-Baker H, Mathieu J, Veesler D, Baker D.
  Science, 2021 | doi:10.1126/science.abd9994
  
  Abstract

  Multivalent display of receptor-engaging antibodies or ligands can enhance their activity. Instead of achieving multivalency by attachment to preexisting scaffolds, here we unite form and function by the computational design of nanocages in which one structural component is an antibody or Fc-ligand fusion and the second is a designed antibody-binding homo-oligomer that drives nanocage assembly. Structures of eight nanocages determined by electron microscopy spanning dihedral, tetrahedral, octahedral, and icosahedral architectures with 2, 6, 12, and 30 antibodies per nanocage, respectively, closely match the corresponding computational models. Antibody nanocages targeting cell surface receptors enhance signaling compared with free antibodies or Fc-fusions in death receptor 5 (DR5)-mediated apoptosis, angiopoietin-1 receptor (Tie2)-mediated angiogenesis, CD40 activation, and T cell proliferation. Nanocage assembly also increases severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pseudovirus neutralization by α-SARS-CoV-2 monoclonal antibodies and Fc-angiotensin-converting enzyme 2 (ACE2) fusion proteins.

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Lab-Led

• Accurate design of megadalton-scale two-component icosahedral protein complexes
  Matdes Nanoparticles Rosetta Lab-led
  Bale JB, Gonen S, Liu Y, Sheffler W, Ellis D, Thomas C, Cascio D, Yeates TO, Gonen T, King NP, Baker D.
  Science, 2016 | doi:10.1126/science.aaf8818
  
  Abstract

  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.

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• Design of a hyperstable 60-subunit protein dodecahedron. [corrected]
  Matdes Nanoparticles
  Hsia Y, Bale JB, Gonen S, Shi D, Sheffler W, Fong KK, Nattermann U, Xu C, Huang PS, Ravichandran R, Yi S, Davis TN, Gonen T, King NP, Baker D.
  Nature, 2016 | doi:10.1038/nature18010
  
  Abstract

  The dodecahedron [corrected] is the largest of the Platonic solids, and icosahedral protein structures are widely used in biological systems for packaging and transport. There has been considerable interest in repurposing such structures 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 dodecahedron [corrected] 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 delivery, vaccine design and synthetic biology.

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Collaborator-Led

• Multivalent Display of Antifreeze Proteins by Fusion to Self-Assembling Protein Cages Enhances Ice-Binding Activities
  Matdes Nanoparticles
  Phippen SW, Stevens CA, Vance TD, King NP, Baker D, Davies PL.
  Biochemistry, 2016 | doi:10.1021/acs.biochem.6b00864
  
  Abstract

  Antifreeze proteins (AFPs) are small monomeric proteins that adsorb to the surface of ice to inhibit ice crystal growth and impart freeze resistance to the organisms producing them. Previously, monomeric AFPs have been conjugated to the termini of branched polymers to increase their activity through the simultaneous binding of more than one AFP to ice. Here, we describe a superior approach to increasing AFP activity through oligomerization that eliminates the need for conjugation reactions with varying levels of efficiency. A moderately active AFP from a fish and a hyperactive AFP from an Antarctic bacterium were genetically fused to the C-termini of one component of the 24-subunit protein cage T33-21, resulting in protein nanoparticles that multivalently display exactly 12 AFPs. The resulting nanoparticles exhibited freezing point depression >50-fold greater than that seen with the same concentration of monomeric AFP and a similar increase in the level of ice-recrystallization inhibition. These results support the anchored clathrate mechanism of binding of AFP to ice. The enhanced freezing point depression could be due to the difficulty of overgrowing a larger AFP on the ice surface and the improved ice-recrystallization inhibition to the ability of the nanoparticle to simultaneously bind multiple ice grains. Oligomerization of these proteins using self-assembling protein cages will be useful in a variety of biotechnology and cryobiology applications.

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• Structure of a designed tetrahedral protein assembly variant engineered to have improved soluble expression
  Matdes Nanoparticles
  Bale JB, Park RU, Liu Y, Gonen S, Gonen T, Cascio D, King NP, Yeates TO, Baker D.
  Protein Sci, 2015 | doi:10.1002/pro.2748
  
  Abstract

  We recently reported the development of a computational method for the design of coassembling multicomponent protein nanomaterials. While four such materials were validated at high-resolution by X-ray crystallography, low yield of soluble protein prevented X-ray structure determination of a fifth designed material, T33-09. Here we report the design and crystal structure of T33-31, a variant of T33-09 with improved soluble yield resulting from redesign efforts focused on mutating solvent-exposed side chains to charged amino acids. The structure is found to match the computational design model with atomic-level accuracy, providing further validation of the design approach and demonstrating a simple and potentially general means of improving the yield of designed protein nanomaterials.

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• Accurate design of co-assembling multi-component protein nanomaterials
  Matdes Nanoparticles Methods Rosetta Lab-led
  King NP, Bale JB, Sheffler W, McNamara DE, Gonen S, Gonen T, Yeates TO, Baker D.
  Nature, 2014 | doi:10.1038/nature13404
  
  Abstract

  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.

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• Computational design of self-assembling protein nanomaterials with atomic level accuracy
  Matdes Nanoparticles Methods Rosetta Lab-led
  King NP, Sheffler W, Sawaya MR, Vollmar BS, Sumida JP, André I, Gonen T, Yeates TO, Baker D.
  Science, 2012 | doi:10.1126/science.1219364
  
  Abstract

  We describe a general computational method for designing proteins that self-assemble to a desired symmetric architecture. Protein building blocks are docked together symmetrically to identify complementary packing arrangements, and low-energy protein-protein interfaces are then designed between the building blocks in order to drive self-assembly. We used trimeric protein building blocks to design a 24-subunit, 13-nm diameter complex with octahedral symmetry and a 12-subunit, 11-nm diameter complex with tetrahedral symmetry. The designed proteins assembled to the desired oligomeric states in solution, and the crystal structures of the complexes revealed that the resulting materials closely match the design models. The method can be used to design a wide variety of self-assembling protein nanomaterials.

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