Evolution of a designed protein assembly encapsulating its own RNA genome

Assembly and Functionality of 2D Protein Arrays

Among the unique classes of 2D nanomaterials, 2D protein arrays garner increasing attention due to their remarkable structural stability, exceptional physiochemical properties, and tunable electronic and mechanical attributes. The interest in mimicking and surpassing the precise architecture and advanced functionality of natural protein systems drives the field of 2D protein assembly toward the development of sophisticated functional materials. Recent advancements deepen the understanding of the fundamental principles governing 2D protein self-assembly, accelerating the creation of novel functional biomaterials. These developments encompass biological, chemical, and templated strategies, facilitating the self-organization of proteins into highly ordered and intricate 2D patterns. Consequently, these 2D protein arrays create new opportunities for integrating diverse components, from small molecules to nanoparticles, thereby enhancing the performance and versatility of materials in various applications. This review comprehensively assesses the current state of 2D protein nanotechnology, highlighting the latest methodologies for directing protein assembly into precise 2D architectures. The transformative potential of 2D protein assemblies in designing next-generation biomaterials, particularly in areas such as biomedicine, catalysis, photosystems, and membrane filtration is also emphasized.

Local structural flexibility drives oligomorphism in computationally designed protein assemblies

Many naturally occurring protein assemblies have dynamic structures that allow them to perform specialized functions. Although computational methods for designing novel self-assembling proteins have advanced substantially over the past decade, they primarily focus on designing static structures. Here we characterize three distinct computationally designed protein assemblies that exhibit unanticipated structural diversity arising from flexibility in their subunits. Cryo-EM single-particle reconstructions and native mass spectrometry reveal two distinct architectures for two assemblies, while six cryo-EM reconstructions for the third likely represent a subset of its solution-phase structures. Structural modeling and molecular dynamics simulations indicate that constrained flexibility within the subunits of each assembly promotes a defined range of architectures rather than nonspecific aggregation. Redesigning the flexible region in one building block rescues the intended monomorphic assembly. These findings highlight structural flexibility as a powerful design principle, enabling exploration of new structural and functional spaces in protein assembly design.

Hierarchical design of pseudosymmetric protein nanocages

Discrete protein assemblies ranging from hundreds of kilodaltons to hundreds of megadaltons in size are a ubiquitous feature of biological systems and perform highly specialized functions1,2. Despite remarkable recent progress in accurately designing new self-assembling proteins, the size and complexity of these assemblies has been limited by a reliance on strict symmetry3. Here, inspired by the pseudosymmetry observed in bacterial microcompartments and viral capsids, we developed a hierarchical computational method for designing large pseudosymmetric self-assembling protein nanomaterials. We computationally designed pseudosymmetric heterooligomeric components and used them to create discrete, cage-like protein assemblies with icosahedral symmetry containing 240, 540 and 960 subunits. At 49, 71 and 96 nm diameter, these nanocages are the largest bounded computationally designed protein assemblies generated to date. More broadly, by moving beyond strict symmetry, our work substantially broadens the variety of self-assembling protein architectures that are accessible through design.

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.

Semliki Forest Virus (SFV) Self-Amplifying RNA Delivered to J774A.1 Macrophage Lineage by Its Association with a Purified Recombinant SFV Capsid Protein

The Semliki Forest virus capsid protein (C) is an RNA binding protein which exhibits both specific and unspecific affinities to single-strand nucleic acids. The putative use of the self-amplifying RNAs (saRNAs) of alphaviruses for biotechnological purpose is one of the main studied strategies concerning RNA-based therapies or immunization. In this work, a recombinant C protein from SFV was expressed and purified from bacteria and used to associate in vitro with a saRNA derived from SFV. Results showed that the purified form of C protein can associate with the saRNA even after high temperature treatment. The C protein was associated with a modified saRNA coding for the green fluorescent protein (GFP) and delivered to murine macrophage cells which expressed the GFP, showing that the saRNA was functional after being associated with the recombinant purified C protein.

The recent advancements in protein nanoparticles for immunotherapy

In recent years, the advancement of nanoparticle-based immunotherapy has introduced an innovative strategy for combatting diseases. Compared with other types of nanoparticles, protein nanoparticles have obtained substantial attention owing to their remarkable biocompatibility, biodegradability, ease of modification, and finely designed spatial structures. Nature provides several protein nanoparticle platforms, including viral capsids, ferritin, and albumin, which hold significant potential for disease treatment. These naturally occurring protein nanoparticles not only serve as effective drug delivery platforms but also augment antigen delivery and targeting capabilities through techniques like genetic modification and covalent conjugation. Motivated by nature's originality and driven by progress in computational methodologies, scientists have crafted numerous protein nanoparticles with intricate assembly structures, showing significant potential in the development of multivalent vaccines. Consequently, both naturally occurring and de novo designed protein nanoparticles are anticipated to enhance the effectiveness of immunotherapy. This review consolidates the advancements in protein nanoparticles for immunotherapy across diseases including cancer and other diseases like influenza, pneumonia, and hepatitis.

The Effect of β-Sheet Secondary Structure on All-β Proteins by Molecular Dynamics Simulations

The effect of β-sheet ratio and chain length on all-β proteins was investigated by MD simulations. Protein samples composed of different repeating units with various β-sheet ratios or a different number of repeating units were simulated under a broad temperature range. The simulation results show that the smaller radius of gyration was achieved by the protein with the higher proportion of β-sheet secondary structure, which had the lower nonbonded energy with more HBs within the protein. The root mean square deviation (RMSD) and the root mean square fluctuation (RMSF) both increased with temperature, especially in the case of a longer chain. The visible period was also shown according to the repeated secondary structure. Several minimum values of RMSF were located on the skeleton of Cα atoms participating in the β-sheet, indicating that it is a kind of stable secondary structure. We also concluded that proteins with a short chain or a lower ratio of β-sheet could easily transform their oriented and compact structures to other ones, such as random coils, turns, and even α-helices. These results clarified the relationship from the primary level to the 3D structure of proteins and potentially predicted protein folding.

Advancements of the Molecular Directed Design and Structure-Activity Relationship of Ferritin Nanocage

Ferritin nanocages possess remarkable structural properties and biological functions, making them highly attractive for applications in functional materials and biomedicine. This comprehensive review presents an overview of the molecular characteristics, extraction and identification of ferritin, ferritin receptors, as well as the advancements in the directional design of high-order assemblies of ferritin and the applications based on its unique structural properties. Specifically, this Review focuses on the regulation of ferritin assembly from one to three dimensions, leveraging the symmetry of ferritin and modifications on key interfaces. Furthermore, it discusses targeted delivery of nutrition and drugs through facile loading and functional modification of ferritin. The aim of this Review is to inspire the design of micro/nano functional materials using ferritin and the development of nanodelivery vehicles for nutritional fortification and disease treatment.

Macromolecular Cargo Encapsulation via In Vitro Assembly of Two-Component Protein Nanoparticles

Self-assembling protein nanoparticles are a promising class of materials for targeted drug delivery. Here, the use of a computationally designed, two-component, icosahedral protein nanoparticle is reported to encapsulate multiple macromolecular cargoes via simple and controlled self-assembly in vitro. Single-stranded RNA molecules between 200 and 2500 nucleotides in length are encapsulated and protected from enzymatic degradation for up to a month with length-dependent decay rates. Immunogenicity studies of nanoparticles packaging synthetic polymers carrying a small-molecule TLR7/8 agonist show that co-delivery of antigen and adjuvant results in a more than 20-fold increase in humoral immune responses while minimizing systemic cytokine secretion associated with free adjuvant. Coupled with the precise control over nanoparticle structure offered by computational design, robust and versatile encapsulation via in vitro assembly opens the door to a new generation of cargo-loaded protein nanoparticles that can combine the therapeutic effects of multiple drug classes.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN

The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Computational Design of Peptide Assemblies

With the ongoing development of peptide self-assembling materials, there is growing interest in exploring novel functional peptide sequences. From short peptides to long polypeptides, as the functionality increases, the sequence space is also expanding exponentially. Consequently, attempting to explore all functional sequences comprehensively through experience and experiments alone has become impractical. By utilizing computational methods, especially artificial intelligence enhanced molecular dynamics (MD) simulation and de novo peptide design, there has been a significant expansion in the exploration of sequence space. Through these methods, a variety of supramolecular functional materials, including fibers, two-dimensional arrays, nanocages, etc., have been designed by meticulously controlling the inter- and intramolecular interactions. In this review, we first provide a brief overview of the current main computational methods and then focus on the computational design methods for various self-assembled peptide materials. Additionally, we introduce some representative protein self-assemblies to offer guidance for the design of self-assembling peptides.

In vivo selection of synthetic nucleocapsids for tissue targeting

Controlling the biodistribution of protein- and nanoparticle-based therapeutic formulations remains challenging. In vivo library selection is an effective method for identifying constructs that exhibit desired distribution behavior; library variants can be selected based on their ability to localize to the tissue or compartment of interest despite complex physiological challenges. Here, we describe further development of an in vivo library selection platform based on self-assembling protein nanoparticles encapsulating their own mRNA genomes (synthetic nucleocapsids or synNCs). We tested two distinct libraries: a low-diversity library composed of synNC surface mutations (45 variants) and a high-diversity library composed of synNCs displaying miniproteins with binder-like properties (6.2 million variants). While we did not identify any variants from the low-diversity surface library that yielded therapeutically relevant changes in biodistribution, the high-diversity miniprotein display library yielded variants that shifted accumulation toward lungs or muscles in just two rounds of in vivo selection. Our approach should contribute to achieving specific tissue homing patterns and identifying targeting ligands for diseases of interest.

Effect of ionic strength on the assembly of simian vacuolating virus capsid protein around poly(styrene sulfonate)

Virus-like particles (VLPs) are noninfectious nanocapsules that can be used for drug delivery or vaccine applications. VLPs can be assembled from virus capsid proteins around a condensing agent, such as RNA, DNA, or a charged polymer. Electrostatic interactions play an important role in the assembly reaction. VLPs assemble from many copies of capsid protein, with a combinatorial number of intermediates. Hence, the mechanism of the reaction is poorly understood. In this paper, we combined solution small-angle X-ray scattering (SAXS), cryo-transmission electron microscopy (TEM), and computational modeling to determine the effect of ionic strength on the assembly of Simian Vacuolating Virus 40 (SV40)-like particles. We mixed poly(styrene sulfonate) with SV40 capsid protein pentamers at different ionic strengths. We then characterized the assembly product by SAXS and cryo-TEM. To analyze the data, we performed Langevin dynamics simulations using a coarse-grained model that revealed incomplete, asymmetric VLP structures consistent with the experimental data. We found that close to physiological ionic strength, [Formula: see text] VLPs coexisted with VP1 pentamers. At lower or higher ionic strengths, incomplete particles coexisted with pentamers and [Formula: see text] particles. Including the simulated structures was essential to explain the SAXS data in a manner that is consistent with the cryo-TEM images.

Drug delivery systems for CRISPR-based genome editors

CRISPR-based drugs can theoretically manipulate any genetic target. In practice, however, these drugs must enter the desired cell without eliciting an unwanted immune response, so a delivery system is often required. Here, we review drug delivery systems for CRISPR-based genome editors, focusing on adeno-associated viruses and lipid nanoparticles. After describing how these systems are engineered and their subsequent characterization in preclinical animal models, we highlight data from recent clinical trials. Preclinical targeting mediated by polymers, proteins, including virus-like particles, and other vehicles that may deliver CRISPR systems in the future is also discussed.

Local structural flexibility drives oligomorphism in computationally designed protein assemblies

Many naturally occurring protein assemblies have dynamic structures that allow them to perform specialized functions. For example, clathrin coats adopt a wide variety of architectures to adapt to vesicular cargos of various sizes. Although computational methods for designing novel self-assembling proteins have advanced substantially over the past decade, most existing methods focus on designing static structures with high accuracy. Here we characterize the structures of three distinct computationally designed protein assemblies that each form multiple unanticipated architectures, and identify flexibility in specific regions of the subunits of each assembly as the source of structural diversity. Cryo-EM single-particle reconstructions and native mass spectrometry showed that only two distinct architectures were observed in two of the three cases, while we obtained six cryo-EM reconstructions that likely represent a subset of the architectures present in solution in the third case. Structural modeling and molecular dynamics simulations indicated that the surprising observation of a defined range of architectures, instead of non-specific aggregation, can be explained by constrained flexibility within the building blocks. Our results suggest that deliberate use of structural flexibility as a design principle will allow exploration of previously inaccessible structural and functional space in designed protein assemblies.

Molecular Time Capsules Enable Transcriptomic Recording in Living Cells

Live-cell transcriptomic recording can help reveal hidden cellular states that precede phenotypic transformation. Here we demonstrate the use of protein-based encapsulation for preserving samples of cytoplasmic RNAs inside living cells. These molecular time capsules (MTCs) can be induced to create time-stamped transcriptome snapshots, preserve RNAs after cellular transitions, and enable retrospective investigations of gene expression programs that drive distinct developmental trajectories. MTCs also open the possibility to uncover transcriptomes in difficult-to-reach conditions.

Protein-modified nanomaterials: emerging trends in skin wound healing

Prolonged inflammation can impede wound healing, which is regulated by several proteins and cytokines, including IL-4, IL-10, IL-13, and TGF-β. Concentration-dependent effects of these molecules at the target site have been investigated by researchers to develop them as wound-healing agents by regulating signaling strength. Nanotechnology has provided a promising approach to achieve tissue-targeted delivery and increased effective concentration by developing protein-functionalized nanoparticles with growth factors (EGF, IGF, FGF, PDGF, TGF-β, TNF-α, and VEGF), antidiabetic wound-healing agents (insulin), and extracellular proteins (keratin, heparin, and silk fibroin). These molecules play critical roles in promoting cell proliferation, migration, ECM production, angiogenesis, and inflammation regulation. Therefore, protein-functionalized nanoparticles have emerged as a potential strategy for improving wound healing in delayed or impaired healing cases. This review summarizes the preparation and applications of these nanoparticles for normal or diabetic wound healing and highlights their potential to enhance wound healing.

Exploring the Landscape of the PP7 Virus-like Particle for Peptide Display

Self-assembling virus-like particles (VLPs) can tolerate a wide degree of genetic and chemical manipulation to their capsid protein to display a foreign molecule polyvalently. We previously reported the successful incorporation of foreign peptide sequences in the junction loop and onto the C-terminus of PP7 dimer VLPs, as these regions are accessible for surface display on assembled capsids. Here, we report the implementation of a library-based approach to test the assembly tolerance of PP7 dimer capsid proteins to insertions or terminal extensions of randomized 15-mer peptide sequences. By performing two iterative rounds of assembly-based selection, we evaluated the degree of favorability of all 20 amino acids at each of the 15 randomized positions. Deep sequencing analysis revealed a distinct preference for the inclusion of hydrophilic peptides and negatively charged amino acids (Asp and Glu) and the exclusion of positively charged peptides and bulky and hydrophobic amino acid residues (Trp, Phe, Tyr, and Cys). Within the libraries tested here, we identified 4000 to 22,000 unique 15-mer peptide sequences that can successfully be displayed on the surface of the PP7 dimer capsid. Overall, the use of small initial libraries consisting of no more than a few million members yielded a significantly larger number of unique and assembly-competent VLP sequences than have been previously characterized for this class of nucleoprotein particle.

Engineering nanoparticle toolkits for mRNA delivery

The concept of using mRNA to produce its own medicine in situ in the body makes it an ideal drug candidate, holding great potential to revolutionize the way we approach medicine. The unique characteristics of mRNA, as well as its customizable biomedical functions, call for the rational design of delivery systems to protect and transport mRNA molecules. In this review, a nanoparticle toolkit is presented for the development of mRNA-based therapeutics from a drug delivery perspective. Nano-delivery systems derived from either natural systems or chemical synthesis, in the nature of organic or inorganic materials, are summarised. Delivery strategies in controlling the tissue targeting and mRNA release, as well as the role of nanoparticles in building and boosting the activity of mRNA drugs, have also been introduced. In the end, our insights into the clinical and translational development of mRNA nano-drugs are presented.

High-Throughput Screening of Streptavidin-Binding Proteins in Self-Assembled Solid Films for Directed Evolution of Materials

Evolution has shaped the development of proteins with an incredible diversity of properties. Incorporating proteins into materials is desirable for applications including biosensing; however, high-throughput selection techniques for screening protein libraries in materials contexts is lacking. In this work, a high-throughput platform to assess the binding affinity for ordered sensing proteins was established. A library of fusion proteins, consisting of an elastin-like polypeptide block, one of 22 variants of rcSso7d, and a coiled-coil order-directing sequence, was generated. All selected variants had high binding in films, likely due to the similarity of the assay to magnetic bead sorting used for initial selection, while solution binding was more variable. From these results, both the assembly of the fusion proteins in their operating state and the functionality of the binding protein are key factors in the biosensing performance. Thus, the integration of directed evolution with assembled systems is necessary to the design of better materials.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN

The design of novel protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. A new generation of deep learning methods promises to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

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.

De Novo Design of Polyhedral Protein Assemblies: Before and After the AI Revolution

Self-assembling polyhedral protein biomaterials have gained attention as engineering targets owing to their naturally evolved sophisticated functions, ranging from protecting macromolecules from the environment to spatially controlling biochemical reactions. Precise computational design of de novo protein polyhedra is possible through two main types of approaches: methods from first principles, using physical and geometrical rules, and more recent data-driven methods based on artificial intelligence (AI), including deep learning (DL). Here, we retrospect first principle- and AI-based approaches for designing finite polyhedral protein assemblies, as well as advances in the structure prediction of such assemblies. We further highlight the possible applications of these materials and explore how the presented approaches can be combined to overcome current challenges and to advance the design of functional protein-based biomaterials.

Complementary charge-driven encapsulation of functional protein by engineered protein cages in cellulo

Charge-driven inclusion complex formation in live cells was examined using a degradation-prone fluorescent protein and a series of protein cages. The results show that sufficiently strong host-guest ionic interaction and an intact shell-like structure are crucial for the protective guest encapsulation.

Design of Beta-2 Microglobulin Adsorbent Protein Nanoparticles

Beta-2 microglobulin (B2M) is an immune system protein that is found on the surface of all nucleated human cells. B2M is naturally shed from cell surfaces into the plasma, followed by renal excretion. In patients with impaired renal function, B2M will accumulate in organs and tissues leading to significantly reduced life expectancy and quality of life. While current hemodialysis methods have been successful in managing electrolyte as well as small and large molecule disturbances arising in chronic renal failure, they have shown only modest success in managing plasma levels of B2M and similar sized proteins, while sparing important proteins such as albumin. We describe a systematic protein design effort aimed at adding the ability to selectively remove specific, undesired waste proteins such as B2M from the plasma of chronic renal failure patients. A novel nanoparticle built using a tetrahedral protein assembly as a scaffold that presents 12 copies of a B2M-binding nanobody is described. The designed nanoparticle binds specifically to B2M through protein-protein interactions with nanomolar binding affinity (~4.2 nM). Notably, binding to the nanoparticle increases the effective size of B2M by over 50-fold, offering a potential selective avenue for separation based on size. We present data to support the potential utility of such a nanoparticle for removing B2M from plasma by either size-based filtration or by polyvalent binding to a stationary matrix under blood flow conditions. Such applications could address current shortcomings in the management of problematic mid-sized proteins in chronic renal failure patients.

Hierarchical design of pseudosymmetric protein nanoparticles

Discrete protein assemblies ranging from hundreds of kilodaltons to hundreds of megadaltons in size are a ubiquitous feature of biological systems and perform highly specialized functions 1-3. Despite remarkable recent progress in accurately designing new self-assembling proteins, the size and complexity of these assemblies has been limited by a reliance on strict symmetry 4,5. Inspired by the pseudosymmetry observed in bacterial microcompartments and viral capsids, we developed a hierarchical computational method for designing large pseudosymmetric self-assembling protein nanomaterials. We computationally designed pseudosymmetric heterooligomeric components and used them to create discrete, cage-like protein assemblies with icosahedral symmetry containing 240, 540, and 960 subunits. At 49, 71, and 96 nm diameter, these nanoparticles are the largest bounded computationally designed protein assemblies generated to date. More broadly, by moving beyond strict symmetry, our work represents an important step towards the accurate design of arbitrary self-assembling nanoscale protein objects.

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 important for targeted delivery of biologics. We describe the design of octahedral non-porous nanoparticles with the three symmetry axes (four-fold, three-fold, and two-fold) occupied by three distinct protein homooligomers: a de novo designed tetramer, an antibody of interest, and a designed trimer programmed to disassemble below a tunable pH transition point. The nanoparticles assemble cooperatively from independently purified components, and a cryo-EM density map reveals that the structure is very close to the computational design model. The designed nanoparticles can package a variety of molecular payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between to 5.9-6.7. To our knowledge, these are the first designed nanoparticles with more than two structural components and with finely tunable environmental sensitivity, and they provide new routes to antibody-directed targeted delivery.

Programming the Cellular Uptake of Protein-Based Viromimetic Nanoparticles for Enhanced Delivery

Viral mimetics is a noteworthy strategy to design efficient delivery systems without the safety drawbacks and engineering difficulties of modifying viral vectors. The triblock polypeptide CSB was previously designed de novo to self-assemble with DNA into nanocomplexes called artificial virus-like particles (AVLPs) due to their similarities to viral particles. Here, we show how we can incorporate new blocks into the CSB polypeptide to enhance its transfection without altering its self-assembly capabilities and the stability and morphology of the AVLPs. The addition of a short peptide (aurein) and/or a large protein (transferrin) to the AVLPs improved their internalization and specific targeting to cells by up to 11 times. Overall, these results show how we can further program the cellular uptake of the AVLPs with a wide range of bioactive blocks. This can pave the way to develop programmable and efficient gene delivery systems.

Ferritin nanocages as efficient nanocarriers and promising platforms for COVID-19 and other vaccines development

BACKGROUND

The development of safe and effective vaccines against SARS-CoV-2 and other viruses with high antigenic drift is of crucial importance to public health. Ferritin is a well characterized and ubiquitous iron storage protein that has emerged not only as a useful nanoreactor and nanocarrier, but more recently as an efficient platform for vaccine development.

SCOPE OF REVIEW

This review discusses ferritin structure-function properties, self-assembly, and novel bioengineering strategies such as interior cavity and exterior surface modifications for cargo encapsulation and delivery. It also discusses the use of ferritin as a scaffold for biomedical applications, especially for vaccine development against influenza, Epstein-Barr, HIV, hepatitis-C, Lyme disease, and respiratory viruses such as SARS-CoV-2. The use of ferritin for the synthesis of mosaic vaccines to deliver a cocktail of antigens that elicit broad immune protection against different viral variants is also explored.

MAJOR CONCLUSIONS

The remarkable stability, biocompatibility, surface functionalization, and self-assembly properties of ferritin nanoparticles make them very attractive platforms for a wide range of biomedical applications, including the development of vaccines. Strong immune responses have been observed in pre-clinical studies against a wide range of pathogens and have led to the exploration of ferritin nanoparticles-based vaccines in multiple phase I clinical trials.

GENERAL SIGNIFICANCE

The broad protective antibody response of ferritin nanoparticles-based vaccines demonstrates the usefulness of ferritin as a highly promising and effective approaches for vaccine development.

A Thermal-Stable Protein Nanoparticle That Stimulates Long Lasting Humoral Immune Response

A thermally stable vaccine platform is considered the missing piece of vaccine technology. In this article, we reported the creation of a novel protein nanoparticle and assessed its ability to withstand extended high temperature incubation while stimulating a long-lasting humoral immune response. This protein nanoparticle was assembled from a fusion protein composed of an amphipathic helical peptide derived from the M2 protein of the H5N1 influenza virus (AH3) and a superfolder green fluorescent protein (sfGFP). Its proposed structure was modeled according to transmission electronic microscope (TEM) images of protein nanoparticles. From this proposed protein model, we created a mutant with two gain-of-function mutations that work synergistically on particle stability. A protein nanoparticle assembled from this gain-of-function mutant is able to remove a hydrophobic patch from its surface. This gain-of-function mutant also contributes to the higher thermostability of protein nanoparticles and stimulates a long lasting humoral immune response after a single immunization. This assembled nanoparticle showed increasing particle stability at higher temperatures and salt concentrations. This novel protein nanoparticle may serve as a thermally-stable platform for vaccine development.

Systematic engineering of virus-like particles to identify self-assembly rules for shifting particle size

Virus-like particles (VLPs) are promising scaffolds for biomaterials as well as diagnostic and therapeutic applications. However, there are some key challenges to be solved, such as the ability to engineer alternate sizes for varied use cases. To this end, we created a library of MS2 VLP variants at two key residues in the coat protein which have been implicated as important to controlling VLP size and geometry. By adapting a method for systematic mutagenesis coupled with size-based selections and high-throughput sequencing as a readout, we developed a quantitative assessment of two residues in MS2 coat protein that govern the size shift in MS2 VLPs. We then applied the strategy to the equivalent residues in Qβ VLPs, an MS2 homolog, and demonstrate that the analogous pair of residues are also able to impact Qβ VLP size and shape. These results underscore the power of fitness landscapes in identifying critical features for assembly.

Protein Cages and Nanostructures Constructed from Protein Nanobuilding Blocks

Protein cages and nanostructures are promising biocompatible medical materials, such as vaccines and drug carriers. Recent advances in designed protein nanocages and nanostructures have opened up cutting-edge applications in the fields of synthetic biology and biopharmaceuticals. A simple approach for constructing self-assembling protein nanocages and nanostructures is the design of a fusion protein composed of two different proteins forming symmetric oligomers. In this chapter, we describe the design and methods of protein nanobuilding blocks (PN-Blocks) using a dimeric de novo protein WA20 to construct self-assembling protein cages and nanostructures. A protein nanobuilding block (PN-Block), WA20-foldon, was developed by fusing an intermolecularly folded dimeric de novo protein WA20 and a trimeric foldon domain from bacteriophage T4 fibritin. The WA20-foldon self-assembled into several oligomeric nanoarchitectures in multiples of 6-mer. De novo extender protein nanobuilding blocks (ePN-Blocks) were also developed by fusing tandemly two WA20 with various linkers, to construct self-assembling cyclized and extended chain-like nanostructures. These PN-Blocks would be useful for the construction of self-assembling protein cages and nanostructures and their potential applications in the future.

Fitness Landscape-Guided Engineering of Locally Supercharged Virus-like Particles with Enhanced Cell Uptake Properties

Protein-based nanoparticles are useful models for the study of self-assembly and attractive candidates for drug delivery. Virus-like particles (VLPs) are especially promising platforms for expanding the repertoire of therapeutics that can be delivered effectively as they can deliver many copies of a molecule per particle for each delivery event. However, their use is often limited due to poor uptake of VLPs into mammalian cells. In this study, we use the fitness landscape of the bacteriophage MS2 VLP as a guide to engineer capsid variants with positively charged surface residues to enhance their uptake into mammalian cells. By combining mutations with positive fitness scores that were likely to produce assembled capsids, we identified two key double mutants with internalization efficiencies as much as 67-fold higher than that of wtMS2. Internalization of these variants with positively charged surface residues depends on interactions with cell surface sulfated proteoglycans, and yet, they are biophysically similar to wtMS2 with low cytotoxicity and an overall negative charge. Additionally, the best-performing engineered MS2 capsids can deliver a potent anticancer small-molecule therapeutic with efficacy levels similar to antibody-drug conjugates. Through this work, we were able to establish fitness landscape-based engineering as a successful method for designing VLPs with improved cell penetration. These findings suggest that VLPs with positive surface charge could be useful in improving the delivery of small-molecule- and nucleic acid-based therapeutics.

Engineering Self-Assembling Protein Nanoparticles for Therapeutic Delivery

Despite remarkable advances over the past several decades, many therapeutic nanomaterials fail to overcome major in vivo delivery barriers. Controlling immunogenicity, optimizing biodistribution, and engineering environmental responsiveness are key outstanding delivery problems for most nanotherapeutics. However, notable exceptions exist including some lipid and polymeric nanoparticles, some virus-based nanoparticles, and nanoparticle vaccines where immunogenicity is desired. Self-assembling protein nanoparticles offer a powerful blend of modularity and precise designability to the field, and have the potential to solve many of the major barriers to delivery. In this review, we provide a brief overview of key designable features of protein nanoparticles and their implications for therapeutic delivery applications. We anticipate that protein nanoparticles will rapidly grow in their prevalence and impact as clinically relevant delivery platforms.

Virus-inspired strategies for cancer therapy

The intentional use of viruses for cancer therapy dates back over a century. As viruses are inherently immunogenic and naturally optimized delivery vehicles, repurposing viruses for drug delivery, tumor antigen presentation, or selective replication in cancer cells represents a simple and elegant approach to cancer treatment. While early virotherapy was fraught with harsh side effects and low response rates, virus-based therapies have recently seen a resurgence due to newfound abilities to engineer and tune oncolytic viruses, virus-like particles, and virus-mimicking nanoparticles for improved safety and efficacy. However, despite their great potential, very few virus-based therapies have made it through clinical trials. In this review, we present an overview of virus-inspired approaches for cancer therapy, discuss engineering strategies to enhance their mechanisms of action, and highlight their application for overcoming the challenges of traditional cancer therapies.

Engineering Self-Assembled Endolysin Nanoparticles against Antibiotic-Resistant Bacteria

Antibiotic resistance represents a serious global health concern and has stimulated the development of antimicrobial nanomaterials to combat resistant bacteria. Protein-based nanoparticles combining characteristics of both proteins and nanoparticles offer advantages including high biocompatibility, attractive biodegradability, enhanced bioavailability and functional versatility. They have played an increasing role as promising candidates for broad applications ranging from biocatalysts and drug delivery to vaccine development to cancer therapeutics. However, their application as antibacterial biomaterials to address challenging antibiotic-resistance problems has not been explicitly pursued. Herein, we describe engineering protein-only nanoparticles against resistant Gram-positive bacteria. A self-assembling peptide (P114) enables the assembly of a phage lytic enzyme (P128) into nanoparticles in response to pH reduction. Compared to native P128 and monomeric P114-P128, P128 nanoparticles (P128NANO) demonstrated a stronger bactericidal ability with high potency at lower concentrations (2-3-fold lower), particularly for methicillin-resistant Staphylococcus aureus strains. In addition, P128NANO showed an enhanced thermal (up to 65 °C) and storage stability and elicited extensive damages to bacterial cell walls. These remarkable antibacterial abilities are likely due to the P128NANO nanostructure, mediating multivalent interactions with bacterial cell walls at increased local concentrations of endolysin. The engineered endolysin nanoparticles offer a promising antimicrobial alternative to conventional antibiotics.

Self-assembling nanocarriers from engineered proteins: Design, functionalization, and application for drug delivery

Self-assembling proteins are valuable building blocks for constructing drug nanocarriers due to their self-assembly behavior, monodispersity, biocompatibility, and biodegradability. Genetic and chemical modifications allow for modular design of protein nanocarriers with effective drug encapsulation, targetability, stimuli responsiveness, and in vivo half-life. Protein nanocarriers have been developed to deliver various therapeutic molecules including small molecules, proteins, and nucleic acids with proven in vitro and in vivo efficacy. This article reviews recent advances in protein nanocarriers that are not derived from natural protein nanostructures, such as protein cages or virus like particles. The protein nanocarriers described here are self-assembled from rationally or de novo designed recombinant proteins, as well as recombinant proteins complexed with other biomolecules, presenting properties that are unique from those of natural protein carriers. Design, functionalization, and therapeutic application of protein nanocarriers will be discussed.

Single-particle studies of the effects of RNA-protein interactions on the self-assembly of RNA virus particles

Understanding the pathways by which simple RNA viruses self-assemble from their coat proteins and RNA is of practical and fundamental interest. Although RNA-protein interactions are thought to play a critical role in the assembly, our understanding of their effects is limited because the assembly process is difficult to observe directly. We address this problem by using interferometric scattering microscopy, a sensitive optical technique with high dynamic range, to follow the in vitro assembly kinetics of more than 500 individual particles of brome mosaic virus (BMV)-for which RNA-protein interactions can be controlled by varying the ionic strength of the buffer. We find that when RNA-protein interactions are weak, BMV assembles by a nucleation-and-growth pathway in which a small cluster of RNA-bound proteins must exceed a critical size before additional proteins can bind. As the strength of RNA-protein interactions increases, the nucleation time becomes shorter and more narrowly distributed, but the time to grow a capsid after nucleation is largely unaffected. These results suggest that the nucleation rate is controlled by RNA-protein interactions, while the growth process is driven less by RNA-protein interactions and more by protein-protein interactions and intraprotein forces. The nucleated pathway observed with the plant virus BMV is strikingly similar to that previously observed with bacteriophage MS2, a phylogenetically distinct virus with a different host kingdom. These results raise the possibility that nucleated assembly pathways might be common to other RNA viruses.

Polymorphic self-assembly of helical tubules is kinetically controlled

In contrast to most self-assembling synthetic materials, which undergo unbounded growth, many biological self-assembly processes are self-limited. That is, the assembled structures have one or more finite dimensions that are much larger than the size scale of the individual monomers. In many such cases, the finite dimension is selected by a preferred curvature of the monomers, which leads to self-closure of the assembly. In this article, we study an example class of self-closing assemblies: cylindrical tubules that assemble from triangular monomers. By combining kinetic Monte Carlo simulations, free energy calculations, and simple theoretical models, we show that a range of programmable size scales can be targeted by controlling the intricate balance between the preferred curvature of the monomers and their interaction strengths. However, their assembly is kinetically controlled-the tubule morphology is essentially fixed shortly after closure, resulting in a distribution of tubule widths that is significantly broader than the equilibrium distribution. We develop a simple kinetic model based on this observation and the underlying free-energy landscape of assembling tubules that quantitatively describes the distributions. Our results are consistent with recent experimental observations of tubule assembly from triangular DNA origami monomers. The modeling framework elucidates design principles for assembling self-limited structures from synthetic components, such as artificial microtubules that have a desired width and chirality.

Precise Assembly of Proteins and Carbohydrates for Next-Generation Biomaterials

The complexity and diversity of biomacromolecules make them a unique class of building blocks for generating precise assemblies. They are particularly available to a new generation of biomaterials integrated with living systems due to their intrinsic properties such as accurate recognition, self-organization, and adaptability. Therefore, many excellent approaches have been developed, leading to a variety of quite practical outcomes. Here, we review recent advances in the fabrication and application of artificially precise assemblies by employing proteins and carbohydrates as building blocks, followed by our perspectives on some of new challenges, goals, and opportunities for the future research directions in this field.

A method for targeting a specified segment of DNA to a bacterial microorganelle

Encapsulation of a selected DNA molecule in a cell has important implications for bionanotechnology. Non-viral proteins that can be used as nucleic acid containers include proteinaceous subcellular bacterial microcompartments (MCPs) that self-assemble into a selectively permeable protein shell containing an enzymatic core. Here, we adapted a propanediol utilization (Pdu) MCP into a synthetic protein cage to package a specified DNA segment in vivo, thereby enabling subsequent affinity purification. To this end, we engineered the LacI transcription repressor to be routed, together with target DNA, into the lumen of a Strep-tagged Pdu shell. Sequencing of extracted DNA from the affinity-isolated MCPs shows that our strategy results in packaging of a DNA segment carrying multiple LacI binding sites, but not the flanking regions. Furthermore, we used LacI to drive the encapsulation of a DNA segment containing operators for LacI and for a second transcription factor.

Designing Protease-Triggered Protein Cages

Proteins that self-assemble into enclosed polyhedral cages, both naturally and by design, are garnering attention for their prospective utility in the fields of medicine and biotechnology. Notably, their potential for encapsulation and surface display are attractive for experiments that require protection and targeted delivery of cargo. The ability to control their opening or disassembly would greatly advance the development of protein nanocages into widespread molecular tools. Toward the development of protein cages that disassemble in a systematic manner and in response to biologically relevant stimuli, here we demonstrate a modular protein cage system that is opened by highly sequence-specific proteases, based on sequence insertions at strategically chosen loop positions in the protein cage subunits. We probed the generality of the approach in the context of protein cages built using the two prevailing methods of construction: genetic fusion between oligomeric components and (non-covalent) computational interface design between oligomeric components. Our results suggest that the former type of cage may be more amenable than the latter for endowing proteolytically controlled disassembly. We show that a successfully designed cage system, based on oligomeric fusion, is modular with regard to its triggering protease. One version of the cage is targeted by an asparagine protease implicated in cancer and Alzheimer's disease, whereas the second version is responsive to the blood-clotting protease, thrombin. The approach demonstrated here should guide future efforts to develop therapeutic vectors to treat disease states where protease induction or mis-regulation occurs.

Microcompartment assembly around multicomponent fluid cargoes

This article describes dynamical simulations of the assembly of an icosahedral protein shell around a bicomponent fluid cargo. Our simulations are motivated by bacterial microcompartments, which are protein shells found in bacteria that assemble around a complex of enzymes and other components involved in certain metabolic processes. The simulations demonstrate that the relative interaction strengths among the different cargo species play a key role in determining the amount of each species that is encapsulated, their spatial organization, and the nature of the shell assembly pathways. However, the shell protein–shell protein and shell protein–cargo component interactions that help drive assembly and encapsulation also influence cargo composition within certain parameter regimes. These behaviors are governed by a combination of thermodynamic and kinetic effects. In addition to elucidating how natural microcompartments encapsulate multiple components involved within reaction cascades, these results have implications for efforts in synthetic biology to colocalize alternative sets of molecules within microcompartments to accelerate specific reactions. More broadly, the results suggest that coupling between self-assembly and multicomponent liquid–liquid phase separation may play a role in the organization of the cellular cytoplasm.

Thermodynamic Size Control in Curvature-Frustrated Tubules: Self-Limitation with Open Boundaries

We use computational modeling to investigate the assembly thermodynamics of a particle-based model for geometrically frustrated assembly, in which the local packing geometry of subunits is incompatible with uniform, strain-free large-scale assembly. The model considers discrete triangular subunits that drive assembly toward a closed, hexagonal-ordered tubule, but have geometries that locally favor negative Gaussian curvature. We use dynamical Monte Carlo simulations and enhanced sampling methods to compute the free energy landscape and corresponding self-assembly behavior as a function of experimentally accessible parameters that control assembly driving forces and the magnitude of frustration. The results determine the parameter range where finite-temperature self-limiting assembly occurs, in which the equilibrium assembly size distribution is sharply peaked around a well-defined finite size. The simulations also identify two mechanisms by which the system can escape frustration and assemble to unlimited size, and determine the particle-scale properties of subunits that suppress unbounded growth.

How Pore Architecture Regulates the Function of Nanoscale Protein Compartments

Self-assembling proteins can form porous compartments that adopt well-defined architectures at the nanoscale. In nature, protein compartments act as semipermeable barriers to enable spatial separation and organization of complex biochemical processes. The compartment pores play a key role in their overall function by selectively controlling the influx and efflux of important biomolecular species. By engineering the pores, the functionality of compartments can be tuned to facilitate non-native applications, such as artificial nanoreactors for catalysis. In this review, we analyze how protein structure determines the porosity and impacts the function of both native and engineered compartments, highlighting the wealth of structural data recently obtained by cryo-EM and X-ray crystallography. Through this analysis, we offer perspectives on how current structural insights can inform future studies into the design of artificial protein compartments as nanoreactors with tunable porosity and function.

Computational design of mechanically coupled axle-rotor protein assemblies

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.

Methods for the directed evolution of biomolecular interactions

Noncovalent interactions between biomolecules such as proteins and nucleic acids coordinate all cellular processes through changes in proximity. Tools that perturb these interactions are and will continue to be highly valuable for basic and translational scientific endeavors. By taking cues from natural systems, such as the adaptive immune system, we can design directed evolution platforms that can generate proteins that bind to biomolecules of interest. In recent years, the platforms used to direct the evolution of biomolecular binders have greatly expanded the range of types of interactions one can evolve. Herein, we review recent advances in methods to evolve protein-protein, protein-RNA, and protein-DNA interactions.

Protein Cages: From Fundamentals to Advanced Applications

Proteins that self-assemble into polyhedral shell-like structures are useful molecular containers both in nature and in the laboratory. Here we review efforts to repurpose diverse protein cages, including viral capsids, ferritins, bacterial microcompartments, and designed capsules, as vaccines, drug delivery vehicles, targeted imaging agents, nanoreactors, templates for controlled materials synthesis, building blocks for higher-order architectures, and more. A deep understanding of the principles underlying the construction, function, and evolution of natural systems has been key to tailoring selective cargo encapsulation and interactions with both biological systems and synthetic materials through protein engineering and directed evolution. The ability to adapt and design increasingly sophisticated capsid structures and functions stands to benefit the fields of catalysis, materials science, and medicine.