Multivalent antigen display on nanoparticle immunogens increases B cell clonotype diversity and neutralization breadth to pneumoviruses.

Nanoparticles for multivalent display and delivery of vaccine antigens have emerged as a promising avenue for enhancing B cell responses to protein subunit vaccines. Here, we evaluated B cell responses in rhesus macaques immunized with prefusion-stabilized respiratory syncytial virus (RSV) F glycoprotein trimer compared with nanoparticles displaying 10 or 20 copies of the same antigen. We show that multivalent display skews antibody specificities and drives epitope-focusing of responding B cells. Antibody cloning and repertoire sequencing revealed that focusing was driven by the expansion of clonally distinct B cells through recruitment of diverse precursors. We identified two antibody lineages that developed either ultrapotent neutralization or pneumovirus cross-neutralization from precursor B cells with low initial affinity for the RSV-F immunogen. This suggests that increased avidity by multivalent display facilitates the activation and recruitment of these cells. Diversification of the B cell response by multivalent nanoparticle immunogens has broad implications for vaccine design.

De novo design of allosterically switchable protein assemblies.

Allosteric modulation of protein function, wherein the binding of an effector to a protein triggers conformational changes at distant functional sites, plays a central part in the control of metabolism and cell signalling1-3. There has been considerable interest in designing allosteric systems, both to gain insight into the mechanisms underlying such 'action at a distance' modulation and to create synthetic proteins whose functions can be regulated by effectors4-7. However, emulating the subtle conformational changes distributed across many residues, characteristic of natural allosteric proteins, is a significant challenge8,9. Here, inspired by the classic Monod-Wyman-Changeux model of cooperativity10, we investigate the de novo design of allostery through rigid-body coupling of peptide-switchable hinge modules11 to protein interfaces12 that direct the formation of alternative oligomeric states. We find that this approach can be used to generate a wide variety of allosterically switchable systems, including cyclic rings that incorporate or eject subunits in response to peptide binding and dihedral cages that undergo effector-induced disassembly. Size-exclusion chromatography, mass photometry13 and electron microscopy reveal that these designed allosteric protein assemblies closely resemble the design models in both the presence and absence of peptide effectors and can have ligand-binding cooperativity comparable to classic natural systems such as haemoglobin14. Our results indicate that allostery can arise from global coupling of the energetics of protein substructures without optimized side-chain-side-chain allosteric communication pathways and provide a roadmap for generating allosterically triggerable delivery systems, protein nanomachines and cellular feedback control circuitry.

Blueprinting extendable nanomaterials with standardized protein blocks.

A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures1. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight 'train track' assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence-structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to 'back of an envelope' architectural blueprints.

HIV-1 VRC01 Germline-Targeting Immunogens Select Distinct Epitope-Specific B Cell Receptors.

Activating precursor B cell receptors of HIV-1 broadly neutralizing antibodies requires specifically designed immunogens. Here, we compared the abilities of three such germline-targeting immunogens against the VRC01-class receptors to activate the targeted B cells in transgenic mice expressing the germline VH of the VRC01 antibody but diverse mouse light chains. Immunogen-specific VRC01-like B cells were isolated at different time points after immunization, their VH and VL genes were sequenced, and the corresponding antibodies characterized. VRC01 B cell sub-populations with distinct cross-reactivity properties were activated by each immunogen, and these differences correlated with distinct biophysical and biochemical features of the germline-targeting immunogens. Our study indicates that the design of effective immunogens to activate B cell receptors leading to protective HIV-1 antibodies will require a better understanding of how the biophysical properties of the epitope and its surrounding surface on the germline-targeting immunogen influence its interaction with the available receptor variants in vivo.

De novo design of protein structure and function with RFdiffusion.

There has been considerable recent progress in designing new proteins using deep-learning methods1-9. Despite this progress, a general deep-learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models10,11 have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due to the complexity of protein backbone geometry and sequence-structure relationships. Here we show that by fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal-binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryogenic electron microscopy structure of a designed binder in complex with influenza haemagglutinin that is nearly identical to the design model. In a manner analogous to networks that produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.

Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains.

Computationally designed protein nanoparticles have recently emerged as a promising platform for the development of new vaccines and biologics. For many applications, secretion of designed nanoparticles from eukaryotic cells would be advantageous, but in practice, they often secrete poorly. Here we show that designed hydrophobic interfaces that drive nanoparticle assembly are often predicted to form cryptic transmembrane domains, suggesting that interaction with the membrane insertion machinery could limit efficient secretion. We develop a general computational protocol, the Degreaser, to design away cryptic transmembrane domains without sacrificing protein stability. The retroactive application of the Degreaser to previously designed nanoparticle components and nanoparticles considerably improves secretion, and modular integration of the Degreaser into design pipelines results in new nanoparticles that secrete as robustly as naturally occurring protein assemblies. Both the Degreaser protocol and the nanoparticles we describe may be broadly useful in biotechnological applications.

Accurate computational design of three-dimensional protein crystals.

Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain-side-chain interactions across protein-protein interfaces is an outstanding challenge. Here we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein-protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.

Fast and versatile sequence-independent protein docking for nanomaterials design using RPXDock.

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.

Design of Diverse Asymmetric Pockets in De Novo Homo-oligomeric Proteins.

A challenge for design of protein-small-molecule recognition is that incorporation of cavities with size, shape, and composition suitable for specific recognition can considerably destabilize protein monomers. This challenge can be overcome through binding pockets formed at homo-oligomeric interfaces between folded monomers. Interfaces surrounding the central homo-oligomer symmetry axes necessarily have the same symmetry and so may not be well suited to binding asymmetric molecules. To enable general recognition of arbitrary asymmetric substrates and small molecules, we developed an approach to designing asymmetric interfaces at off-axis sites on homo-oligomers, analogous to those found in native homo-oligomeric proteins such as glutamine synthetase. We symmetrically dock curved helical repeat proteins such that they form pockets at the asymmetric interface of the oligomer with sizes ranging from several angstroms, appropriate for binding a single ion, to up to more than 20 Å across. Of the 133 proteins tested, 84 had soluble expression in E. coli, 47 had correct oligomeric states in solution, 35 had small-angle X-ray scattering (SAXS) data largely consistent with design models, and 8 had negative-stain electron microscopy (nsEM) 2D class averages showing the structures coming together as designed. Both an X-ray crystal structure and a cryogenic electron microscopy (cryoEM) structure are close to the computational design models. The nature of these proteins as homo-oligomers allows them to be readily built into higher-order structures such as nanocages, and the asymmetric pockets of these structures open rich possibilities for small-molecule binder design free from the constraints associated with monomer destabilization.

Smart data collection for CryoEM.

This report provides an overview of the discussions, presentations, and consensus thinking from the Workshop on Smart Data Collection for CryoEM held at the New York Structural Biology Center on April 6-7, 2022. The goal of the workshop was to address next generation data collection strategies that integrate machine learning and real-time processing into the workflow to reduce or eliminate the need for operator intervention.

CryoEM structure of a prokaryotic cyclic nucleotide-gated ion channel.

Cyclic nucleotide-gated (CNG) and hyperpolarization-activated cyclic nucleotide-regulated (HCN) ion channels play crucial physiological roles in phototransduction, olfaction, and cardiac pace making. These channels are characterized by the presence of a carboxyl-terminal cyclic nucleotide-binding domain (CNBD) that connects to the channel pore via a C-linker domain. Although cyclic nucleotide binding has been shown to promote CNG and HCN channel opening, the precise mechanism underlying gating remains poorly understood. Here we used cryoEM to determine the structure of the intact LliK CNG channel isolated from Leptospira licerasiae-which shares sequence similarity to eukaryotic CNG and HCN channels-in the presence of a saturating concentration of cAMP. A short S4-S5 linker connects nearby voltage-sensing and pore domains to produce a non-domain-swapped transmembrane architecture, which appears to be a hallmark of this channel family. We also observe major conformational changes of the LliK C-linkers and CNBDs relative to the crystal structures of isolated C-linker/CNBD fragments and the cryoEM structures of related CNG, HCN, and KCNH channels. The conformation of our LliK structure may represent a functional state of this channel family not captured in previous studies.

The circulating microbiome signature and inferred functional metagenomics in alcoholic hepatitis.

Intestinal dysbiosis is implicated in alcoholic hepatitis (AH). However, changes in the circulating microbiome, its association with the presence and severity of AH, and its functional relevance in AH is unknown. Qualitative and quantitative assessment of changes in the circulating microbiome were performed by sequencing bacterial DNA in subjects with moderate AH (MAH) (n = 18) or severe AH (SAH) (n = 19). These data were compared with heavy drinking controls (HDCs) without obvious liver disease (n = 19) and non-alcohol-consuming controls (NACs, n = 20). The data were related to endotoxin levels and markers of monocyte activation. Linear discriminant analysis effect size (LEfSe) analysis, inferred metagenomics, and predictive functional analysis using PICRUSt were performed. There was a significant increase in 16S copies/ng DNA both in MAH (P < 0.01) and SAH (P < 0.001) subjects. Compared with NACs, the relative abundance of phylum Bacteroidetes was significantly decreased in HDCs, MAH, and SAH (P < 0.001). In contrast, all alcohol-consuming groups had enrichment with Fusobacteria; this was greatest for HDCs and decreased progressively in MAH and SAH. Subjects with SAH had significantly higher endotoxemia (P = 0.01). Compared with alcohol-consuming groups, predictive functional metagenomics indicated an enrichment of bacteria with genes related to methanogenesis and denitrification. Furthermore, both HDCs and SAH showed activation of a type III secretion system that has been linked to gram-negative bacterial virulence. Metagenomics in SAH versus NACs predicted increased isoprenoid synthesis via mevalonate and anthranilate degradation, known modulators of gram-positive bacterial growth and biofilm production, respectively. CONCLUSION: Heavy alcohol consumption appears to be the primary driver of changes in the circulating microbiome associated with a shift in its inferred metabolic functions. (Hepatology 2018;67:1284-1302).

Vitrification after multiple rounds of sample application and blotting improves particle density on cryo-electron microscopy grids.

Single particle cryo-electron microscopy (cryoEM) is becoming widely adopted as a tool for structural characterization of biomolecules at near-atomic resolution. Vitrification of the sample to obtain a dense distribution of particles within a single field of view remains a major bottleneck for the success of such experiments. Here, we describe a simple and cost-effective method to increase the density of frozen-hydrated particles on grids with holey carbon support films. It relies on performing multiple rounds of sample application and blotting prior to plunge freezing in liquid ethane. We show that this approach is generally applicable and significantly increases particle density for a range of samples, such as small protein complexes, viruses and filamentous assemblies. The method is versatile, easy to implement, minimizes sample requirements and can enable characterization of samples that would otherwise resist structural studies using single particle cryoEM.

Computational design of bifaceted protein nanomaterials with tailorable properties.

Recent advances in computational methods have led to considerable progress in the design of self-assembling protein nanoparticles. However, nearly all nanoparticles designed to date exhibit strict point group symmetry, with each subunit occupying an identical, symmetrically related environment. This property limits the structural diversity that can be achieved and precludes anisotropic functionalization. Here, we describe a general computational strategy for designing multi-component bifaceted protein nanomaterials with two distinctly addressable sides. The method centers on docking pseudosymmetric heterooligomeric building blocks in architectures with dihedral symmetry and designing an asymmetric protein-protein interface between them. We used this approach to obtain an initial 30-subunit assembly with pseudo-D5 symmetry, and then generated an additional 15 variants in which we controllably altered the size and morphology of the bifaceted nanoparticles by designing de novo extensions to one of the subunits. Functionalization of the two distinct faces of the nanoparticles with de novo protein minibinders enabled specific colocalization of two populations of polystyrene microparticles coated with target protein receptors. The ability to accurately design anisotropic protein nanomaterials with precisely tunable structures and functions will be broadly useful in applications that require colocalizing two or more distinct target moieties.

Bond-centric modular design of protein assemblies.

We describe a modular bond-centric approach to protein nanomaterial design inspired by the rich diversity of chemical structures that can be generated from the small number of atomic valencies and bonding interactions. We design protein building blocks with regular coordination geometries and bonding interactions that enable the assembly of a wide variety of closed and opened nanomaterials using simple geometrical principles. Experimental characterization confirms successful formation of more than twenty multi-component polyhedral protein cages, 2D arrays, and 3D protein lattices, with a high (10-50 %) success rate and electron microscopy data closely matching the corresponding design models. Because of the modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable systems.

Computational design of non-porous pH-responsive antibody nanoparticles.

Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and is important for targeted delivery of biologics. Here we describe the design of octahedral non-porous nanoparticles with a targeting antibody on the two-fold symmetry axis, a designed trimer programmed to disassemble below a tunable pH transition point on the three-fold axis, and a designed tetramer on the four-fold symmetry axis. Designed non-covalent interfaces guide cooperative nanoparticle assembly from independently purified components, and a cryo-EM density map closely matches the computational design model. The designed nanoparticles can package protein and nucleic acid payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between 5.9 and 6.7. The ability to incorporate almost any antibody into a non-porous pH-dependent nanoparticle opens up new routes to antibody-directed targeted delivery.

Atomically accurate de novo design of single-domain antibodies.

Despite the central role that antibodies play in modern medicine, there is currently no way to rationally design novel antibodies to bind a specific epitope on a target. Instead, antibody discovery currently involves time-consuming immunization of an animal or library screening approaches. Here we demonstrate that a fine-tuned RFdiffusion network is capable of designing de novo antibody variable heavy chains (VHH's) that bind user-specified epitopes. We experimentally confirm binders to four disease-relevant epitopes, and the cryo-EM structure of a designed VHH bound to influenza hemagglutinin is nearly identical to the design model both in the configuration of the CDR loops and the overall binding pose.

Precisely patterned nanofibres made from extendable protein multiplexes.

Molecular systems with coincident cyclic and superhelical symmetry axes have considerable advantages for materials design as they can be readily lengthened or shortened by changing the length of the constituent monomers. Among proteins, alpha-helical coiled coils have such symmetric, extendable architectures, but are limited by the relatively fixed geometry and flexibility of the helical protomers. Here we describe a systematic approach to generating modular and rigid repeat protein oligomers with coincident C2 to C8 and superhelical symmetry axes that can be readily extended by repeat propagation. From these building blocks, we demonstrate that a wide range of unbounded fibres can be systematically designed by introducing hydrophilic surface patches that force staggering of the monomers; the geometry of such fibres can be precisely tuned by varying the number of repeat units in the monomer and the placement of the hydrophilic patches.

Spatial subcellular organelle networks in single cells.

Organelles play important roles in human health and disease, such as maintaining homeostasis, regulating growth and aging, and generating energy. Organelle diversity in cells not only exists between cell types but also between individual cells. Therefore, studying the distribution of organelles at the single-cell level is important to understand cellular function. Mesenchymal stem cells are multipotent cells that have been explored as a therapeutic method for treating a variety of diseases. Studying how organelles are structured in these cells can answer questions about their characteristics and potential. Herein, rapid multiplexed immunofluorescence (RapMIF) was performed to understand the spatial organization of 10 organelle proteins and the interactions between them in the bone marrow (BM) and umbilical cord (UC) mesenchymal stem cells (MSCs). Spatial correlations, colocalization, clustering, statistical tests, texture, and morphological analyses were conducted at the single cell level, shedding light onto the interrelations between the organelles and comparisons of the two MSC subtypes. Such analytics toolsets indicated that UC MSCs exhibited higher organelle expression and spatially spread distribution of mitochondria accompanied by several other organelles compared to BM MSCs. This data-driven single-cell approach provided by rapid subcellular proteomic imaging enables personalized stem cell therapeutics.

Top-down design of protein architectures with reinforcement learning.

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.