Computational placement of the chlorophyll special pair into symmetric protein scaffolds: Identifying residue positions capable of accommodating the Chl special pair which is scalable to millions of potential scaffolds was achieved by utilizing a motif-hash based method (Fallas et al., 2017; Yao et al., 2022) specifically adopted for the histidine-Chl dimer motif inspired by the special pair of purple bacteria, P865. However, the number of example structures of the histidine-Chl dimer motif found in the PDB is not acceptable for effectively populating a motif hash table. Therefore, generating additional structural examples of the symmetric histidine-Chl dimer complex was generated de novo.
The conformer generation was achieved using the NeRF algorithm (available on github at https://github.com/atom-moyer/nerf) which translates internal molecular coordinates to global molecular coordinates. Various conformers were generated by varying the internal coordinates such as the relative positioning of the Chl groups, the dihedral of ligation by the histidine residue, and the rotamer of the histidine sidechain. The full complex was duplicated along the C2 axis to create the symmetric complex. If the relative orientations of the Chls were varied, clashes between the rings and their substitutions were evaluated and filtered. The full process of de novo motif generation was repeated for ligation with the epsilon and delta nitrogen of the imidazole ring.
Once the de novo conformers were generated, the 6-D transformation that defines the relative orientation of the N-CA-C atoms of the ligating histidine residues were hashed using a method described previously (Fallas et al., 2017; Yao et al., 2022). The hashed 6-D transformation was used as a key in a multi value hash table (https://github.com/atom-moyer/getpy), and the associated value was a vector that defined the information necessary to rebuild the histidine-Chl complex, which nitrogen from the histidine was used for ligation and the internal coordinates of the histidine rotamer.
During evaluation of design scaffolds, the 6-D transformation of each symmetric residue pair across chains was evaluated and hashed using the same method used to hash the de novo conformers described above. That allowed the identification of symmetric residue pairs which have similar 6-D transformations to the potentially acceptable ligation geometries. If a matching 6-D transformation was found, the histidine-Chl complex was rebuilt from the associated value in the hash table, and the complex was evaluated in the context of the protein. If the Chls did not clash with the backbone atoms of the protein, the placement was accepted and passed into the protein design process.
A python package and example scripts which generate the de novo hash tables and place the histidine-Chl complexes into symmetric proteins can be found here: https://github.com/atom-moyer/stapler.
Protein expression and purification: Synthetic genes with N-terminal His6 tags followed by TEV protease cleavage sites were purchased in pET29b expression vectors from Integrated DNA Technologies, Inc. Plasmids were transformed into Lemo21(DE3) Competent E. coli (New England Biolabs). For each protein, a single E. coli colony was grown in a culture of 5 mL of LB with 100 μg/mL kanamycin overnight at 37°C. Overnight cultures were used to inoculate 50-500 mL cultures of auto-induction media (Studier, 2005). Bacteria were grown in auto-induction media at 37°C with shaking for 4 hours, then incubated shaking overnight at 18°C. Bacteria were harvested and resuspended in 300 mM NaCl, 30 mM imidazole, 25 mM Tris buffer at pH 8, ~0.01 mg/mL DNase (Sigma-Aldrich), ~0.1 mg/mL lysozyme (Sigma-Aldrich), and Pierce™ Protease Inhibitor Tablets (Thermo Fisher Scientific). Bacteria were lysed by sonication and centrifuged at ~18,000 g for 30 minutes. Soluble fractions were purified by Immobilized Metal Affinity Chromatography (IMAC) gravity columns packed with Ni-NTA agarose resin (Qiagen) at room temperature. Columns were washed with a buffer containing 20 mM imidazole and proteins were eluted with a 300 mM imidazole buffer. Samples were digested with His-tagged TEV protease in the presence of 0.5 mM dithiothreitol for 1-2 days at room temperature. Digested proteins were buffer exchanged into 20 mM imidazole buffer, 300 mM NaCl, and 25 mM Tris buffer at pH 8 and applied to IMAC columns to remove TEV protease and uncleaved protein. Proteins were further purified by size-exclusion chromatography (SEC) using an ÄKTA FPLC with a Superdex 200 Increase 10/300 GL column (GE Healthcare Life Sciences). Protein and Chl molecular weights were verified by reverse-phase liquid chromatography/mass spectrometry (LC/MS) with an Agilent G6230B TOF instrument using an AdvanceBio RP-Desalting column. Mass spectra were deconvoluted in Bioconfirm using a total entropy algorithm (Supplementary Figures 17-19).
Protein-chlorophyll sample preparation: Zn pheophorbide a methyl ester (ZnPPaM) was purchased from Frontier Scientific, Inc. ZnPPaM stock solutions were prepared in dimethyl sulfoxide (DMSO) or methanol to concentrations between 200 μM and 1 mM. ZnPPaM concentrations were determined using mass measurements and by using the known absorptivity of Zn pheophytin a, which has a similar absorbance spectrum and an extinction coefficient ε659nm of 77,300 M-1cm-1 in 80% acetone/20% deionized water (Jones et al., 1976). Ultraviolet/visible (UV/vis) absorbance spectra were collected using a Jasco V-750 spectrophotometer with a 1 nm bandwidth and 400 nm/min scanning speed. Protein-ZnPPaM complexes were prepared by slowly adding freshly-prepared ZnPPaM stock solution to protein solution in aqueous buffer at room temperature and incubating samples for several hours. Unbound ZnPPaM was removed by centrifugation to pellet precipitated ZnPPaM, sterile filtration using a 0.22 μm syringe filter, and/or running a PD-10 desalting column purification (Sephadex™ G-25 M resin, Cytiva Life Sciences).
Circular Dichroism (CD) spectroscopy: CD spectra were collected using a Jasco J-1500 spectrophotometer. For protein secondary structure assays, spectra were measured on samples of 0.2-0.4 mg/mL protein in 1 mm quartz cuvettes from 260 to 190 nm with a 1 nm bandwidth, 1 nm data interval, data integration time (DIT) of 1 second, and scanning speed of 50 nm/min. Thermal melts were monitored at 222 nm from 2 to 98°C with a 2 nm bandwidth and 8 second DIT. UV/vis/near-infrared (NIR) CD transitions of protein-bound Chls were examined in the 800-300 nm region in 1 cm quartz cuvettes as averages of 10 scans using a 3 nm bandwidth, 1 nm data interval, DIT of 4 seconds, and scanning speed of 50 nm/min unless otherwise noted. UV/vis/NIR CD spectra shown in Figure 2 were collected after sterile filtering with 0.22 μm filter and PD-10 desalting column purification (Sephadex™ G-25 M resin, Cytiva Life Sciences). Each spectrum represents the average of two independent sample preparations. Samples contained 8-15 μM protein (monomer concentration) with equimolar ZnPPaM, 150 mM NaCl, and 10 mM Tris buffer at pH 8. ZnPPaM dry powder was dissolved in methanol stock solutions immediately before adding to protein solutions. Samples were allowed to incubate for 8-16 hours at room temperature prior to measuring spectra.
Small angle X-ray scattering (SAXS): Data were collected at the Advanced Light Source (ALS) using the SIBYLS beamline for high throughput SAXS (Dyer et al., 2014). Proteins were sent as 30 μL samples in 96-well plates with buffer-matched blank solutions for background subtraction. Data sets were processed in SAXS Frameslice version 1.4.13 and compared to design models using FoXS (Schneidman-Duhovny et al., 2013, 2016).
Fluorescence quantum yield measurements: Fluorescence spectra displayed in Supplementary Figure 6 were recorded on a Fluorolog Horiba Jobin Yvon spectrofluorimeter equipped with a Xenon lamp, a double monochromator and a photomultiplier detector. The experiments were carried out in right angle (RA) configuration. Each baseline subtracted fluorescence spectrum was corrected for spectral sensitivity of the fluorimeter and re-absorption by assuming the middle of the cuvette is the origin of emission. Relative quantum yields were estimated using Chl a in diethyl ether as a reference (Weber & Teale, 1957).
Low-temperature absorbance and fluorescence spectroscopy in a sucrose/trehalose film:
Solutions of SP2-ZnPPaM were mixed with a saturated sugar solution made by dissolving a 50:50 sucrose/trehalose (w/w) in distilled water as described previously (Caram et al., 2016). A 100 μL sample of SP2 at 34 mg/mL (ZnPPaM dimer) or 156 mg/mL (ZnPPaM monomer) was added dropwise to 100 μL of the sugar solution and gently mixed. The sugar/protein mixture was dropped onto a 0.1 mm quartz cuvette from Starna Cells Inc. and kept under vacuum in the dark for 24 hr. The sample was then loaded into a Janis ST-100 cryostat using a custom-built copper cuvette holder and cooled with liquid nitrogen. A Lakeshore 330 Autotuning Temperature Controller was used to control the temperature. An Agilent Cary-60 spectrometer was used to collect all absorbance spectra across temperatures. For the temperature-dependent fluorescence emission spectra, a home-built setup equipped with a Thorlabs 405 nm laser head (CPS405). The collected emission was fiber coupled into a Flame Ocean Optics spectrometer. Lifetimes were recorded using a homebuilt, all-reflective epifluorescence setup. The samples were excited via a pulsed laser output from a 405 nm pulsed diode laser (LDH-P-C-405, PicoQuant) with a 10 MHz repetition rate. The emission was subsequently filtered with a 420 nm longpass dichroic beam splitter (DMLP425R, Thorlabs) and 420 nm longpass filter (10CGA-420, Newport). The emission was detected by avalanche photodiodes (PD050-CTD, Micro Photon Devices). Time-correlated single photon counting (TCSPC) traces were histogrammed using a Picoquant HydraHarp 400 and analyzed via the corresponding software.
Molecular dynamics simulations: All molecular dynamics (MD) simulations were performed with Amber18 (Case et al., 2018) using the ff14SB forcefield (Maier et al., 2015) for proteins and TIP3P (Jorgensen et al., 1983) for water. To obtain the forcefield parameters of the chromophore (ZnPPaM), we used the MCPB.py module of Amber (Li & Merz, 2016). Atomic charges were calculated using the restrained electrostatic potential (RESP) fitting scheme, while force constants were calculated with the Seminario method. QM geometry optimization and ESP calculations were performed with Gaussian 16 (Rev B.01) (Frisch et al., 2016) at the B3LYP/6-31G* level. Parameters for the organic part of the chromophore were taken from the general AMBER force field (GAFF).
As starting structures, either design models or crystal structures were employed. Protonation states were determined with the H++ webserver, at pH 8 (using default parameters) (Anandakrishnan et al., 2012; Gordon et al., 2005; Myers et al., 2006). Topology and geometry files were generated with LEaP, using an isometric truncated-octahedron shape for the periodic box, with a minimum distance between the protein and the edges of the box of 1.5 nm. Protein charges were neutralized with Na+ and Cl- ions.
Minimization and initial equilibration steps were performed following a recently developed protocol (Roe & Brooks, 2020). Briefly, it consists of nine sequential energy minimizations and short MD runs, which sum 4000 steps of minimization and 40000 MD steps (totalling 30 ps), followed by a final MD equilibration (500000 steps, 1000 ps). Then, after discarding the first 200 ns, production runs were done in the NPT ensemble at 300.0 K, with a time step of 2 fs, and constraining bonds involving hydrogen atoms via the SHAKE algorithm. Constant temperature and pressure were ensured with the Langevin thermostat (collision frequency: 2 ps-1) and Monte Carlo barostat, respectively. Long-range electrostatics were considered via the Particle Mesh Ewald (PME) model, setting the direct space sum cut-off to 1.0 nm.
Calculation of Chl dimer excitonic coupling and spectra: Calculations involving excited states were performed on the chromophore geometries of the design models and on the crystal structures. In the latter case, hydrogen atoms were added using UCSF Chimera 1.11 (Pettersen et al., 2004). Electronic couplings were calculated using the EET (electronic energy transfer) module from Gaussian, at the CAM-B3LYP/6-31G* level. The effect of the environment was considered through the polarizable continuum model (PCM) (Iozzi et al., 2004; Tomasi et al., 2005), choosing n-octanol as representative of the protein dielectric behavior. The EET analysis considered six singlet excited states per chromophore.
To obtain circular dichroism spectra we used the results of the EET calculations and the Excitonic Analysis Tool (EXAT) program (Jurinovich et al., 2014, 2015, 2018). Rotatory strengths were calculated by considering both electric and magnetic dipoles in the velocity formulation. Spectral lineshapes were simulated as gaussians, with a full-width at half-maximum of 350 cm-1 for the Qy and Qx transitions and 1150 cm-1 for transitions in the Soret region. Spectra were shifted by -0.25 eV to reproduce the experimental position of the Qy band.
Fluorescence lifetime imaging (FLIM): Fluorescence lifetime imaging was conducted on a home-built laser scanning time-resolved fluorescence microscope as described previously (Huang et al., 2020). The microscope was equipped with a 485 nm picosecond diode laser (PicoQuant, PDL 828) and a 450 nm LED (Thorlabs, M470L2) (wide-field illumination) as excitation sources. The excitation light was focused by a 100 × objective (PlaneFluorite, NA = 1.4, oil immersion, Olympus). The emitted light was filtered using a 495 nm dichroic beam-splitter (Semrock) and 565/25, 630/20 and 680/45 nm bandpass filters (Semrock) to remove the background excitation light. The microscope was fitted with a spectrometer (150 lines/mm grating, Acton SP2558, Princeton Instruments) and an electron-multiplying charge-coupled device (EMCCD) camera (ProEM 512, Princeton Instruments) for emission spectrum acquisition and wide-field imaging. A hybrid detector (HPM-100-50, Becker & Hickl) was used for single-photon counting. The modulation of the excitation laser was synchronized with a time-correlated single-photon counting (TCSPC) module (SPC-150, Becker & Hickl) for the lifetime decay measurement. The repetition rate of the laser was set at 1 MHz. The excitation laser power was adjusted to produce a fluence of approximately 2×1014 photons pulse-1 cm-2. The instrument response function (IRF) of the set up was approximately 130 ps. Fluorescence lifetime images were recorded by scanning the excitation laser over the sample using a piezo scanner. The FLIM data was analyzed using OriginPro (OriginLab Corporation) and FLIMfit (www.flimfit.org).
X-ray crystallography for SP1 and SP2: Crystals of SP1 and SP2 were grown using protein purified as described above. Protein samples dispensed in 1 μL drops at purification concentrations were mixed with equal volume of a crystallization solution and set in hanging drops (refer to Supplementary Table 4 for conditions). Vapor phase equilibration of the resulting drops against a 1 mL reservoir of the same crystallization solution resulted in growth of crystals. The crystals were flash cooled in liquid nitrogen. Diffraction data were collected on a Pilatus area detector at the Advanced Light Source (ALS) synchrotron facility at beamline 5.0.2 for SP1-ZnPPaM and SP2-ZnPPaM protein assemblies. Diffraction data were collected on a Rigaku HyPix-6000HE hybrid photon counting detector at the Fred Hutchinson Cancer Center (Fred Hutch) for SP2. The resulting data sets (Supplementary Table 4) extend to 2.0 Å, 2.4 Å, and 2.5 Å resolution for SP1-ZnPPaM, apo-state SP2, and SP2-ZnPPaM, respectively. The asymmetric units of the SP1-ZnPPaM and apo-state SP2 structures each contained one complete dimer (two copies of a protein subunit), and the SP2-ZnPPaM structure had 2 dimers in the asymmetric unit.
Data were processed using HKL2000 (Otwinowski & Minor, 1997) or Aimless (Evans & Murshudov, 2013). The placement of subunits was determined using the molecular replacement algorithm in program PHENIX (Adams et al., 2010). Local rebuilding of all constructs was performed using the program COOT (Emsley et al., 2010), followed by refinement in PHENIX (Adams et al., 2010). For the ZnPPaM-bound structures, the protein was built and refined completely with waters (excluding waters from the binding site) and other chemicals before manually fitting ZnPPaM into the density that remained. ZnPPaM energies were calculated using eLBOW (Moriarty et al., 2009). The final values for Rwork / Rfree are notated in Supplementary Table 4.
X-ray crystallography for SP3x: All crystallization experiments for the SP3x protein were conducted using the sitting drop vapor diffusion method. Crystallization trials were set up in 200 nL drops using the 96-well plate format at 20°C. Crystallization plates were set up using a Mosquito from SPT Labtech, then imaged using UVEX microscopes and UVEX PS-600 from JAN Scientific. Diffraction quality SP3x crystals formed in 2.4 M sodium malonate dibasic monohydrate pH 7.0.
Diffraction data were collected at the Advanced Light Source at beamline 5.0.1. X-ray intensities and data reduction were evaluated and integrated using XDS (Kabsch, 2010) and merged/scaled using Pointless/Aimless in the CCP4 program suite (Winn et al., 2011). Structure determination and refinement starting phases were obtained by molecular replacement using Phaser (McCoy et al., 2007) using the designed model for the structures. Following molecular replacement, the models were improved using phenix.autobuild (Adams et al., 2010); efforts were made to reduce model bias by setting rebuild-in-place to false, and using simulated annealing and prime-and-switch phasing. Structures were refined in Phenix (Adams et al., 2010). Model building was performed using COOT (Emsley & Cowtan, 2004). The final model was evaluated using MolProbity (Williams et al., 2018). Data collection and refinement statistics are recorded in Supplementary Table 4. Data deposition, atomic coordinates, and structure factors reported for the SP3x protein in this paper have been deposited in the Protein Data Bank (PDB), http://www.rcsb.org/ with accession code 8EVM.
Protein structure alignment: Protein crystal structures were compared to Rosetta design models by aligning corresponding backbone Cα atoms and calculating RMSDs using TM-align (Zhang & Skolnick, 2005). (B)Chl special pair geometries were compared using the align function in The PyMOL Molecular Graphics System, Version 2.5.2, Schrödinger, LLC. To facilitate comparison of the geometries of special pairs composed of different (B)Chl types, omit unimportant conformational differences such as rotameric states of peripheral substituents, and neglect differences in the Mg(II) vs. Zn(II) positions, only the atoms of the tetrapyrrole rings were considered in pairwise special pair structural alignments. These atoms included the 4 pyrrole nitrogen atoms, 16 pyrrole carbon atoms, and 4 methine bridge carbons from each (B)Chl monomer, giving 48 atoms per (B)Chl dimer that were used for structural comparisons. Corresponding atoms were aligned in PyMOL and the RMSD over all 48 atom pairs was calculated. Native BChl a special pairs used for comparison to the SP1 protein came from 5 different species of purple photosynthetic bacteria, including Rhodobacter sphaeroides, Rhodopseudomonas palustris, Thermochromatium tepidum, Gemmatimonas phototrophica, and Thiorhodovibrio strain 970. The PDB IDs of the nine X-ray crystal and cryo-EM structures containing the native special pairs used for comparison to SP1 were: 7PIL, 7VNY, 6Z27, 6Z02, 6Z5S, 3WMM, 5Y5S, 7O0U, and 7C9R (Cao et al., 2022; Niwa et al., 2014; Qian et al., 2021, 2022; Selikhanov et al., 2020; Swainsbury et al., 2021; Tani et al., 2020; Yu et al., 2018).
Nanocage design: The Chl binding dimer SP2 was docked against a library of trimeric cyclic oligomer scaffolds (C3) from previous de novo designs (Boyken et al., 2016; Fallas et al., 2017; Hsia et al., 2021) to form octahedral cages (O32) using the RPXDock software (Sheffler et al., 2022). The RPXdock package utilizes a hierarchical sampling strategy to search for interfaces with high shape complementarity based on residue pair transform scoring. The top 10 scored docking configurations for each scaffold were subsequently sequence designed by symmetric RosettaDesign calculations, using a previously reported protocol (King et al., 2014) to carry out two-component protein-protein interface design. Briefly, we aim to design low-energy, well-packed hydrophobic protein-protein interfaces where protein building blocks are treated as rigid backbones and only side chain rotamers of interface residues are packed with layer design restrictions. The beta_nov16 or a clash-fixed score function was used during the design. Finally, all cage designs were filtered based on shape complementarity (>0.6), interface surface area (solvent-accessible surface area, 1000 < sasa <1600), predicted binding energy (ddG <-20 kcal/mol), buried unsatisfied hydrogen bonds (uhb <3), and clash check (< 3). All Rosetta scripts used are available upon request.
Transmission negative-stain electron microscopy (nsEM) and image processing: SEC purified cage fractions were diluted to about 0.5 µM (monomeric component concentration) for negative-stain EM characterization. Briefly, on a glow-discharged formvar/carbon supported 400-mesh copper grid (Ted Pella, Inc.), 6 μL of protein sample were drop-casted for 2 mins. The grid was blotted and stained with 3 μL of 2% uranyl formate, blotted again, and stained with 3 μL of uranyl formate for 20 s before final blotting. Micrographs of stained samples were taken on a 120kV Talos L120C transmission electron microscope. All nsEM datasets were collected using the EPU software and processed by CryoSparc (Punjani et al., 2017) with contrast transfer function (CTF) correction. All the particle picks were 2D classified for 20 iterations into 50 classes. Particles from selected classes were used for building the ab-initio initial model. The initial model was homogeneously refined using C1 and the corresponding O symmetry.
Cryo-EM grid preparation and data collection: Grids (QUANTIFOIL® R 2/2 on Cu 300 mesh grids + 2 nm C) were vitrified using a Vitrobot Mark IV with chamber maintained at 22°C and 100% humidity. Grids were plunge-frozen into liquid ethane directly following application of 3.5 μl of the ZnPPaM-loaded nanocage to the glow-discharged (for 5 s) surface of the grid. Grids were screened at the NYU Cryo-EM core facility using a Talos Arctica microscope operated at 200 kV with a Gatan K3 camera. Data were then collected on a Titan Krios microscope operated at 300 kV with a Gatan K3 camera with BioQuantum imaging filter (“Krios 2” at the New York Structural Biology Center). Data were acquired from duplicate grids using Leginon (Suloway et al., 2005) and pre-processed (2X binned and motion-corrected with MotionCor2 (Zheng et al., 2017) within Appion (Lander et al., 2009). Full data collection parameters are shown in Supplementary Table 5.
Cryo-EM data processing and model building: Aligned and dose-weighted micrographs were imported to Cryosparc v.3 (Punjani et al., 2017) and processed using the workflow shown in Supplementary Figure 15. During data collection, we noted a high proportion of damaged (compressed or fragmented) nanocage particles in areas of ice with a reported ALS thickness below 40 nm. Curation of micrographs to exclude those with the thinnest ice, and with CTF fit resolution lower than ~6Å, facilitated picking of intact nanocage particles. 2D classification was performed on manually-picked particles to generate templates representing diverse views of the nanocage, but subsequent template-based picking tended to exclude rare particle views. Recovery of these rare views was improved by using a single template for picking representing the view most often missed in prior template-based picking efforts (see Supplementary Table 6). Compared to picking with multiple templates, using a single, rare-view template improved the recovery of diverse particle views, which were then used as a training set for Topaz (Bepler et al., 2019). Picking with Topaz yielded diverse, well-centered nanocage particles. Data from each of the two grids imaged were picked with Topaz separately, and the curated particles were then combined and further curated in 2D. This larger set of curated particles was used to retrain Topaz (204,039 vs. 19,355 in initial Topaz training set) on the full set of micrographs from both grids. Particles picked using this Topaz model were then curated by 2D classification, micrograph curation by ice thickness and CTF fit values, and removal of duplicates.
A 200-micrograph subset from a single grid was used to generate an ab initio 3D reconstruction. Following iterative rounds of homogeneous and heterogeneous refinement, this map served as the initial 3D model for processing of the full particle set from both grids. 3D refinement and classification yielded a map of the full nanocage with an average reported resolution of ~6.5Å (as calculated in Cryosparc using gold-standard FSC cutoff of 0.143). O symmetry was imposed during the final round of refinement. Continuous conformational heterogeneity likely limited the resolution of the full nanocage map, as discrete states were not readily separable by further 3D classification. Multiple modes of flexibility were visualized using Cryosparc’s 3D Variability Analysis (Punjani & Fleet, 2021), supporting the notion that the nanocage particles used in refinement were subject to compression/deformation (see Supplementary Information for movies of protein breathing motions). We then used partial signal subtraction and focused refinement to improve resolution in the ligand-binding region of the cage (region enclosed in yellow mask, Supplementary Figure 15 inset). Prior to partial signal subtraction, particles were expanded with T symmetry (the highest-order symmetry containing a complete Chl-binding dimer). The symmetry-expanded, partially-subtracted particle set was then refined in C1 using Local Refinement in Cryosparc.
The cryo-EM map of the full nanocage was used for real-space refinement of a model in Phenix (Echols et al., 2012). Due to the intermediate map resolution, all residues were modeled as alanine and restraints (secondary structure, Ramachandran, and non-crystallographic symmetry constraints) were imposed during refinement. The designed nanocage model was used as a starting point for refinement, and individual chains were docked into cryo-EM maps using Chimera (Pettersen et al., 2004) before hydrogen removal and truncation to polyalanine using phenix.pdbtools. Stubbed, docked models were then subjected to restrained real-space refinement in Phenix. We observed a notable difference between the design model and the cryoEM density in the angle between each trimeric interface helix and its attached DHR “arm”. To generate a starting model for restrained refinement of the full nanocage, we first performed rigid-body refinement, with each trimer subunit modeled as two rigid bodies (corresponding to the interface helix and “arm” regions; residues 259-337 and 1-258, respectively). Cryo-EM model statistics are listed in Supplementary Table 7.