Design of biologically active binary protein 2D materials

Cell cycle dependent coordination of surface layer biogenesis in Caulobacter crescentus

Surface layers (S-layers) are proteinaceous, two-dimensional paracrystalline arrays that constitute a major component of the cell envelope in many prokaryotic species. In this study, we investigated S-layer biogenesis in the bacterial model organism Caulobacter crescentus. Fluorescence microscopy revealed localised incorporation of new S-layer at the poles and mid-cell, consistent with regions of cell growth in the cell cycle. Light microscopy and electron cryotomography investigations of drug-treated bacteria revealed that localised S-layer insertion is retained when cell division is inhibited, but is disrupted upon dysregulation of MreB or lipopolysaccharide. We further uncovered that S-layer biogenesis follows new peptidoglycan synthesis and localises to regions of high cell wall turnover. Finally, correlated cryo-light microscopy and electron cryotomographic analysis of regions of S-layer insertion showed the presence of discontinuities in the hexagonal S-layer lattice, contrasting with other S-layers completed by defined symmetric defects. Our findings present insights into how C. crescentus cells form an ordered S-layer on their surface in coordination with the biogenesis of other cell envelope components.

A suite of designed protein cages using machine learning and protein fragment-based protocols

Designed protein cages and related materials provide unique opportunities for applications in biotechnology and medicine, but their creation remains challenging. Here, we apply computational approaches to design a suite of tetrahedrally symmetric, self-assembling protein cages. For the generation of docked conformations, we emphasize a protein fragment-based approach, while for sequence design of the de novo interface, a comparison of knowledge-based and machine learning protocols highlights the power and increased experimental success achieved using ProteinMPNN. An analysis of design outcomes provides insights for improving interface design protocols, including prioritizing fragment-based motifs, balancing interface hydrophobicity and polarity, and identifying preferred polar contact patterns. In all, we report five structures for seven protein cages, along with two structures of intermediate assemblies, with the highest resolution reaching 2.0 Å using cryo-EM. This set of designed cages adds substantially to the body of available protein nanoparticles, and to methodologies for their creation.

Single-layer semiconductor-decorated flexible 2D protein nanosheets by engineered anchoring for efficient photocatalytic hydrogen production

Protein self-assembly can be accurately manipulated to form ordered nanostructures through various supramolecular forces. This strategy is expected to make significant breakthroughs in the field of new biomimetic functional materials. Specifically, the construction of photocatalytic systems on two-dimensional (2D) flexible protein nanosheets meets a great challenge. We introduce a synthetic methodology for creating single-layer semiconductor-decorated protein 2D materials under mild conditions with enhanced light-driven hydrogen production. This approach employs a bioengineered green fluorescent protein (E4P) with the addition of a Cd-binding peptide, enabling precise control of the assembly of CdS quantum dots (QDs) on the protein's surface. Consequently, we obtained 4.3 nm-thin single-layer 2D protein nanosheets with substantial surface areas ideal for accommodating CdS QDs. By orthogonal incorporation of metal-binding peptides and supramolecular coordination, significantly enhancing the overall photocatalytic efficiency. Our findings demonstrate the potential for stable and efficient hydrogen production, highlighting the adaptability and biocompatibility of protein scaffolds for photocatalysis.

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.

DNA-Nanostructure-Guided Assembly of Proteins into Programmable Shapes

The development of methods to synthesize artificial protein complexes with precisely controlled configurations will enable diverse biological and medical applications. Using DNA to link proteins provides programmability that can be difficult to achieve with other methods. Here, we use DNA origami as an "assembler" to guide the linking of protein-DNA conjugates using a series of oligonucleotide hybridization and displacement operations. We constructed several isomeric protein nanostructures, including a dimer, two types of trimer structures, and three types of tetramer assemblies, on a DNA origami platform by using a C3-symmetric building block composed of a protein trimer modified with DNA handles. Our approach expands the scope for the precise assembly of protein-based nanostructures and will enable the formulation of functional protein complexes with stoichiometric and geometric control.

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.

HEATR5B associates with dynein-dynactin and promotes motility of AP1-bound endosomal membranes

The microtubule motor dynein mediates polarised trafficking of a wide variety of organelles, vesicles and macromolecules. These functions are dependent on the dynactin complex, which helps recruit cargoes to dynein's tail and activates motor movement. How the dynein-dynactin complex orchestrates trafficking of diverse cargoes is unclear. Here, we identify HEATR5B, an interactor of the adaptor protein-1 (AP1) clathrin adaptor complex, as a novel player in dynein-dynactin function. HEATR5B was recovered in a biochemical screen for proteins whose association with the dynein tail is augmented by dynactin. We show that HEATR5B binds directly to the dynein tail and dynactin and stimulates motility of AP1-associated endosomal membranes in human cells. We also demonstrate that the Drosophila HEATR5B homologue is an essential gene that selectively promotes dynein-based transport of AP1-bound membranes to the Golgi apparatus. As HEATR5B lacks the coiled-coil architecture typical of dynein adaptors, our data point to a non-canonical process orchestrating motor function on a specific cargo. We additionally show that HEATR5B promotes association of AP1 with endosomal membranes independently of dynein. Thus, HEATR5B co-ordinates multiple events in AP1-based trafficking.

Interface-mediated protein aggregation

The aggregation of proteins at interfaces has significant roles and can also lead to dysfunction of different physiological processes. The interfacial effects on the assembly and aggregation of biopolymers are not only crucial for a comprehensive understanding of protein biological functions, but also hold great potential for advancing the state-of-the-art applications of biopolymer materials. Recently, there has been remarkable progress in a collaborative context, as we strive to gain control over complex interfacial assembly structures of biopolymers. These biopolymer structures range from the nanoscale to mesoscale and even macroscale, and are attained through the rational design of interactions between biological building blocks and surfaces/interfaces. This review spotlights the recent advancements in interface-mediated assembly and properties of biopolymer materials. Initially, we introduce the solid-liquid interface (SIL)-mediated biopolymer assembly that includes the inorganic crystalline template effect and protein self-adoptive deposition through phase transition. Next, we display the advancement of biopolymer assembly instigated by the air-water interface (AWI) that acts as an energy conversion station. Lastly, we discuss succinctly the assembly of biopolymers at the liquid-liquid interface (LLI) along with their applications. It is our hope that this overview will stimulate the integration and progression of the science of interfacial assembled biopolymer materials and surfaces/interfaces.

Site-selected in situ polymerization for living cell surface engineering

The construction of polymer-based mimicry on cell surface to manipulate cell behaviors and functions offers promising prospects in the field of biotechnology and cell therapy. However, precise control of polymer grafting sites is essential to successful implementation of biomimicry and functional modulation, which has been overlooked by most current research. Herein, we report a biological site-selected, in situ controlled radical polymerization platform for living cell surface engineering. The method utilizes metabolic labeling techniques to confine the growth sites of polymers and designs a Fenton-RAFT polymerization technique with cytocompatibility. Polymers grown at different sites (glycans, proteins, lipids) have different membrane retention time and exhibit differential effects on the recognition behaviors of cellular glycans. Of particular importance is the achievement of in situ copolymerization of glycomonomers on the outermost natural glycan sites of cell membrane, building a biomimetic glycocalyx with distinct recognition properties.

Synthetic Par polarity induces cytoskeleton asymmetry in unpolarized mammalian cells

Polarized cells rely on a polarized cytoskeleton to function. Yet, how cortical polarity cues induce cytoskeleton polarization remains elusive. Here, we capitalized on recently established designed 2D protein arrays to ectopically engineer cortical polarity of virtually any protein of interest during mitosis in various cell types. This enables direct manipulation of polarity signaling and the identification of the cortical cues sufficient for cytoskeleton polarization. Using this assay, we dissected the logic of the Par complex pathway, a key regulator of cytoskeleton polarity during asymmetric cell division. We show that cortical clustering of any Par complex subunit is sufficient to trigger complex assembly and that the primary kinetic barrier to complex assembly is the relief of Par6 autoinhibition. Further, we found that inducing cortical Par complex polarity induces two hallmarks of asymmetric cell division in unpolarized mammalian cells: spindle orientation, occurring via Par3, and central spindle asymmetry, depending on aPKC activity.

A Suite of Designed Protein Cages Using Machine Learning Algorithms and Protein Fragment-Based Protocols

Designed protein cages and related materials provide unique opportunities for applications in biotechnology and medicine, while methods for their creation remain challenging and unpredictable. In the present study, we apply new computational approaches to design a suite of new tetrahedrally symmetric, self-assembling protein cages. For the generation of docked poses, we emphasize a protein fragment-based approach, while for de novo interface design, a comparison of computational protocols highlights the power and increased experimental success achieved using the machine learning program ProteinMPNN. In relating information from docking and design, we observe that agreement between fragment-based sequence preferences and ProteinMPNN sequence inference correlates with experimental success. Additional insights for designing polar interactions are highlighted by experimentally testing larger and more polar interfaces. In all, using X-ray crystallography and cryo-EM, we report five structures for seven protein cages, with atomic resolution in the best case reaching 2.0 Å. We also report structures of two incompletely assembled protein cages, providing unique insights into one type of assembly failure. The new set of designed cages and their structures add substantially to the body of available protein nanoparticles, and to methodologies for their creation.

Advances in the two-dimensional layer materials for cancer diagnosis and treatment: unique advantages beyond the microsphere

In recent years, two-dimensional (2D) layer materials have shown great potential in the field of cancer diagnosis and treatment due to their unique structural, electronic, and chemical properties. These non-spherical materials have attracted increasing attention around the world because of its widely used biological characteristics. The application of 2D layer materials like lamellar graphene, transition metal dichalcogenides (TMDs), and black phosphorus (BPs) and so on have been developed for CT/MRI imaging, serum biosensing, drug targeting delivery, photothermal therapy, and photodynamic therapy. These unique applications for tumor are due to the multi-variable synthesis of 2D materials and the structural characteristics of good ductility different from microsphere. Based on the above considerations, the application of 2D materials in cancer is mainly carried out in the following three aspects: 1) In terms of accurate and rapid screening of tumor patients, we will focus on the enrichment of serum markers and sensitive signal transformation of 2D materials; 2) The progress of 2D nanomaterials in tumor MRI and CT imaging was described by comparing the performance of traditional contrast agents; 3) In the most important aspect, we will focus on the progress of 2D materials in the field of precision drug delivery and collaborative therapy, such as photothermal ablation, sonodynamic therapy, chemokinetic therapy, etc. In summary, this review provides a comprehensive overview of the advances in the application of 2D layer materials for tumor diagnosis and treatment, and emphasizes the performance difference between 2D materials and other types of nanoparticles (mainly spherical). With further research and development, these multifunctional layer materials hold great promise in the prospects, and challenges of 2D materials development are discussed.

The benefits of clustering in TNF receptor superfamily signaling

The tumor necrosis factor (TNF) receptor superfamily is a structurally and functionally related group of cell surface receptors that play crucial roles in various cellular processes, including apoptosis, cell survival, and immune regulation. This review paper synthesizes key findings from recent studies, highlighting the importance of clustering in TNF receptor superfamily signaling. We discuss the underlying molecular mechanisms of signaling, the functional consequences of receptor clustering, and potential therapeutic implications of targeting surface structures of receptor complexes.

Massively parallel protein-protein interaction measurement by sequencing (MP3-seq) enables rapid screening of protein heterodimers

Protein-protein interactions (PPIs) regulate many cellular processes, and engineered PPIs have cell and gene therapy applications. Here we introduce massively parallel protein-protein interaction measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast-two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs, and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Finally, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics simulation energy terms to predict MP3-seq values. We find that AF-M and AF-M complex prediction-based models could be valuable for pre-screening interactions, but that measuring interactions experimentally remains necessary to rank their strengths quantitatively.

Spatiotemporal Landscape for the Sophisticated Transformation of Protein Assemblies Defined by Multiple Supramolecular Interactions

Precise protein assemblies not only constitute a series of living machineries but also provide an advanced class of biomaterials. Previously, we developed the inducing ligand strategy to generate various fixed protein assemblies, without the formation of noncovalent interactions between proteins. Here, we demonstrated that controlling the symmetry and number of supramolecular interactions introduced on protein surfaces could direct the formation of unspecific interactions between proteins and induce various nanoscale assemblies, including coiling nanowires, nanotubes, and nanosheets, without manipulation of the protein's native surfaces. More importantly, these nanoscale assemblies could spontaneously evolve into more ordered architectures, crystals. We further showed that the transformation from the introduced supramolecular interactions to the interactions formed between proteins was crucial for pathway selection and outcomes of evolution. These findings reveal a transformation mechanism of protein self-assembly that has not been exploited before and may provide an approach to generate complex and transformable biomacromolecular self-assemblies.

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.

Functional DNA as a Molecular Tool in Regulating Immunoreceptor-Ligand Interactions

During immune responses, activating ligands would trigger dynamic spatiotemporal organization of immunoreceptors at the cell interface, governing the fate and effector functions of immune cells. To understand the biophysical mechanisms of immunoreceptor signaling, diverse tools, including DNA technologies, have been developed to manipulate receptor-ligand interactions during the immune activation process. With great capability in the controllable assembly of biomolecules, functional DNA-based precise arrangement of immune molecules at cell interfaces has provided a powerful means in revealing the principles of immunoreceptor triggering, even at the single-molecule level. In addition, precisely regulating immunoreceptor-ligand interactions with functional DNA has been applied in immunotherapies of major diseases. This Perspective will focus on the recent advances in exploring immunoreceptor signaling with functional DNA as the molecular tool as well as the applications of functional DNA mediated regulation of immunoreceptor activation. We also outline the challenges and opportunities of applying functional DNA in immune modulation and immunotherapy.

DNA Origami Tessellations

Molecular tessellation research aims to elucidate the underlying principles that govern intricate patterns in nature and to leverage these principles to create precise and ordered structures across multiple scales, thereby facilitating the emergence of novel functionalities. DNA origami nanostructures are excellent building blocks for constructing tessellation patterns. However, the size and complexity of DNA origami tessellation systems are currently limited by several unexplored factors relevant to the accuracy of essential design parameters, the applicability of design strategies, and the compatibility between different tiles. Here, we present a general method for creating DNA origami tiles that grow into tessellation patterns with micrometer-scale order and nanometer-scale precision. Interhelical distance (D) was identified as a critical design parameter determining tile conformation and tessellation outcome. Finely tuned D facilitated the accurate geometric design of monomer tiles with minimized curvature and improved tessellation capability, enabling the formation of single-crystalline lattices ranging from tens to hundreds of square micrometers. The general applicability of the design method was demonstrated by 9 tile geometries, 15 unique tile designs, and 12 tessellation patterns covering Platonic, Laves, and Archimedean tilings. Particularly, we took two strategies to increase the complexity of DNA origami tessellation, including reducing the symmetry of monomer tiles and coassembling tiles of different geometries. Both yielded various tiling patterns that rivaled Platonic tilings in size and quality, indicating the robustness of the optimized tessellation system. This study will promote DNA-templated, programmable molecular and material patterning and open up new opportunities for applications in metamaterial engineering, nanoelectronics, and nanolithography.

Design, synthesis, and application of some two-dimensional materials

Two-dimensional (2D) materials are widely used as key components in the fields of energy conversion and storage, optoelectronics, catalysis, biomedicine, etc. To meet the practical needs, molecular structure design and aggregation process optimization have been systematically carried out. The intrinsic correlation between preparation methods and the characteristic properties is investigated. This review summarizes the recent research achievements of 2D materials in the aspect of molecular structure modification, aggregation regulation, characteristic properties, and device applications. The design strategies to fabricate functional 2D materials starting from precursor molecules are introduced in detail referring to organic synthetic chemistry and self-assembly technology. It provides important research ideas for the design and synthesis of related materials.

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.

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.

Biosensor for Multimodal Characterization of an Essential ABC Transporter for Next-Generation Antibiotic Research

As the threat of antibiotic resistance increases, there is a particular focus on developing antimicrobials against pathogenic bacteria whose multidrug resistance is especially entrenched and concerning. One such target for novel antimicrobials is the ATP-binding cassette (ABC) transporter MsbA that is present in the plasma membrane of Gram-negative pathogenic bacteria where it is fundamental to the survival of these bacteria. Supported lipid bilayers (SLBs) are useful in monitoring membrane protein structure and function since they can be integrated with a variety of optical, biochemical, and electrochemical techniques. Here, we form SLBs containing Escherichia coli MsbA and use atomic force microscopy (AFM) and structured illumination microscopy (SIM) as high-resolution microscopy techniques to study the integrity of the SLBs and incorporated MsbA proteins. We then integrate these SLBs on microelectrode arrays (MEA) based on the conducting polymer poly(3,4-ethylenedioxy-thiophene) poly(styrene sulfonate) (PEDOT:PSS) using electrochemical impedance spectroscopy (EIS) to monitor ion flow through MsbA proteins in response to ATP hydrolysis. These EIS measurements can be correlated with the biochemical detection of MsbA-ATPase activity. To show the potential of this SLB approach, we observe not only the activity of wild-type MsbA but also the activity of two previously characterized mutants along with quinoline-based MsbA inhibitor G907 to show that EIS systems can detect changes in ABC transporter activity. Our work combines a multitude of techniques to thoroughly investigate MsbA in lipid bilayers as well as the effects of potential inhibitors of this protein. We envisage that this platform will facilitate the development of next-generation antimicrobials that inhibit MsbA or other essential membrane transporters in microorganisms.

Design, synthesis, and characterization of protein origami based on self-assembly of a brick and staple artificial protein pair

A versatile strategy to create an inducible protein assembly with predefined geometry is demonstrated. The assembly is triggered by a binding protein that staples two identical protein bricks together in a predictable spatial conformation. The brick and staple proteins are designed for mutual directional affinity and engineered by directed evolution from a synthetic modular repeat protein library. As a proof of concept, this article reports on the spontaneous, extremely fast and quantitative self-assembly of two designed alpha-repeat (αRep) brick and staple proteins into macroscopic tubular superhelices at room temperature. Small-angle X-ray scattering (SAXS) and transmission electron microscopy (TEM with staining agent and cryoTEM) elucidate the resulting superhelical arrangement that precisely matches the a priori intended 3D assembly. The highly ordered, macroscopic biomolecular construction sustains temperatures as high as 75 °C thanks to the robust αRep building blocks. Since the α-helices of the brick and staple proteins are highly programmable, their design allows encoding the geometry and chemical surfaces of the final supramolecular protein architecture. This work opens routes toward the design and fabrication of multiscale protein origami with arbitrarily programmed shapes and chemical functions.

Ligand-independent receptor clustering modulates transmembrane signaling: a new paradigm

Cell-surface receptors mediate communication between cells and their environment. Lateral membrane organization and dynamic receptor cluster formation are fundamental in signal transduction and cell signaling. However, it is not yet fully understood how receptor clustering modulates a wide variety of physiologically relevant processes. Recent growing evidence indicates that biological responses triggered by membrane receptors can be modulated even in the absence of the natural receptor ligand. We review the most recent findings on how ligand-independent receptor clustering can regulate transmembrane signaling. We discuss the latest technologies to control receptor assembly, such as DNA nanotechnology, optogenetics, and optochemistry, focusing on the biological relevance and unraveling of ligand-independent signaling.

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.

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature's own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and "smart" architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

Protein Design: From the Aspect of Water Solubility and Stability

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

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.

Fluorescent Nanoparticles for Super-Resolution Imaging

Super-resolution imaging techniques that overcome the diffraction limit of light have gained wide popularity for visualizing cellular structures with nanometric resolution. Following the pace of hardware developments, the availability of new fluorescent probes with superior properties is becoming ever more important. In this context, fluorescent nanoparticles (NPs) have attracted increasing attention as bright and photostable probes that address many shortcomings of traditional fluorescent probes. The use of NPs for super-resolution imaging is a recent development and this provides the focus for the current review. We give an overview of different super-resolution methods and discuss their demands on the properties of fluorescent NPs. We then review in detail the features, strengths, and weaknesses of each NP class to support these applications and provide examples from their utilization in various biological systems. Moreover, we provide an outlook on the future of the field and opportunities in material science for the development of probes for multiplexed subcellular imaging with nanometric resolution.

Nanoscale Features of Tunable Bacterial Outer Membrane Models Revealed by Correlative Microscopy

The rise of antibiotic resistance is a growing worldwide human health issue, with major socioeconomic implications. An understanding of the interactions occurring at the bacterial membrane is crucial for the generation of new antibiotics. Supported lipid bilayers (SLBs) made from reconstituted lipid vesicles have been used to mimic these membranes, but their utility has been restricted by the simplistic nature of these systems. A breakthrough in the field has come with the use of outer membrane vesicles derived from Gram-negative bacteria to form SLBs, thus providing a more physiologically relevant system. These complex bilayer systems hold promise but have not yet been fully characterized in terms of their composition, ratio of natural to synthetic components, and membrane protein content. Here, we use correlative atomic force microscopy (AFM) with structured illumination microscopy (SIM) for the accurate mapping of complex lipid bilayers that consist of a synthetic fraction and a fraction of lipids derived from Escherichia coli outer membrane vesicles (OMVs). We exploit the high resolution and molecular specificity that SIM can offer to identify areas of interest in these bilayers and the enhanced resolution that AFM provides to create detailed topography maps of the bilayers. We are thus able to understand the way in which the two different lipid fractions (natural and synthetic) mix within the bilayers, and we can quantify the amount of bacterial membrane incorporated into the bilayer. We prove the system's tunability by generating bilayers made using OMVs engineered to contain a green fluorescent protein (GFP) binding nanobody fused with the porin OmpA. We are able to directly visualize protein-protein interactions between GFP and the nanobody complex. Our work sets the foundation for accurately understanding the composition and properties of OMV-derived SLBs to generate a high-resolution platform for investigating bacterial membrane interactions for the development of next-generation antibiotics.

Materials informatics approach using domain modelling for exploring structure-property relationships of polymers

In the development of polymer materials, it is an important issue to explore the complex relationships between domain structure and physical properties. In the domain structure analysis of polymer materials, ¹H-static solid-state NMR (ssNMR) spectra can provide information on mobile, rigid, and intermediate domains. But estimation of domain structure from its analysis is difficult due to the wide overlap of spectra from multiple domains. Therefore, we have developed a materials informatics approach that combines the domain modeling (http://dmar.riken.jp/matrigica/) and the integrated analysis of meta-information (the elements, functional groups, additives, and physical properties) in polymer materials. Firstly, the ¹H-static ssNMR data of 120 polymer materials were subjected to a short-time Fourier transform to obtain frequency, intensity, and T₂ relaxation time for domains with different mobility. The average T₂ relaxation time of each domain is 0.96 ms for Mobile, 0.55 ms for Intermediate (Mobile), 0.32 ms for Intermediate (Rigid), and 0.11 ms for Rigid. Secondly, the estimated domain proportions were integrated with meta-information such as elements, functional group and thermophysical properties and was analyzed using a self-organization map and market basket analysis. This proposed method can contribute to explore structure–property relationships of polymer materials with multiple domains.

Engineering microbial systems for the production and functionalization of biomaterialsBiomaterials engineering with microorganisms

A new trend in biomaterials synthesis is harnessing the production of microorganisms, owing to the low cost and sustainability. Because microorganisms use DNA as a production code, it is possible for humans to reprogram these cells and thus build living factories for the production of biomaterials. Over the past decade, advances in genetic engineering have enabled the development of various intriguing biomaterials with useful properties, with commercially available biomaterials representing only a few of these. In this review, we discuss the common strategies for the production of bulk and commodity biogenic polymers, and highlight several notable approaches such as modular protein engineering and pathway optimization in achieving these goals. We finally investigate the available synthetic biology tools that allow engineering of living materials, and discuss how this emerging class of materials has expanded the application scope of biomaterials.

Mimetic Neural Networks: A Unified Framework for Protein Design and Folding

Recent advancements in machine learning techniques for protein structure prediction motivate better results in its inverse problem–protein design. In this work we introduce a new graph mimetic neural network, MimNet, and show that it is possible to build a reversible architecture that solves the structure and design problems in tandem, allowing to improve protein backbone design when the structure is better estimated. We use the ProteinNet data set and show that the state of the art results in protein design can be met and even improved, given recent architectures for protein folding.

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.

Bottom-up supramolecular assembly in two dimensions

The self-assembly of molecules in two dimensions (2D) is gathering attention from all disciplines across the chemical sciences. Attracted by the interesting properties of two-dimensional inorganic analogues, monomers of different chemical natures are being explored for the assembly of dynamic 2D systems. Although many important discoveries have been already achieved, great challenges are still to be addressed in this field. Hierarchical multicomponent assembly, directional non-covalent growth and internal structural control are a just a few of the examples that will be discussed in this perspective about the exciting present and the bright future of two-dimensional supramolecular assemblies.

The self-assembly of molecules in two dimensions (2D) is gathering attention from all disciplines across the chemical sciences. This perspective discusses the main strategies to direct the supramolecular self-assembly of organic monomers in 2D.

Protein Needles Designed to Self-Assemble through Needle Tip Engineering

The dynamic process of formation of protein assemblies is essential to form highly ordered structures in biological systems. Advances in structural and synthetic biology have led to the construction of artificial protein assemblies. However, development of design strategies exploiting the anisotropic shape of building blocks of protein assemblies has not yet been achieved. Here, the 2D assembly pattern of protein needles (PNs) is controlled by regulating their tip-to-tip interactions. The PN is an anisotropic needle-shaped protein composed of β-helix, foldon, and His-tag. Three different types of tip-modified PNs are designed by deleting the His-tag and foldon to change the protein-protein interactions. Observing their assembly by high-speed atomic force microscopy (HS-AFM) reveals that PN, His-tag deleted PN, and His-tag and foldon deleted PN form triangular lattices, the monomeric state with nematic order, and fiber assemblies, respectively, on a mica surface. Their assembly dynamics are observed by HS-AFM and analyzed by the theoretical models. Monte Carlo (MC) simulations indicate that the mica-PN interactions and the flexible and multipoint His-tag interactions cooperatively guide the formation of the triangular lattice. This work is expected to provide a new strategy for constructing supramolecular protein architectures by controlling directional interactions of anisotropic shaped proteins.

A Genetically Engineered, Chain Mail-Like Nanostructured Protein Material with Increased Fatigue Resistance and Enhanced Self-Healing

Protein-based nanostructured materials are being developed for many biomedical and nanotechnological applications. Despite their many desirable features, protein materials are highly susceptible to disruption by mechanical stress and fatigue. This study is aimed to increase fatigue resistance and enhance self-healing of a natural protein-based supramolecular nanomaterial through permanent genetic modification. The authors envisage the conversion of a model nanosheet, formed by a regular array of noncovalently bound human immunodeficiency virus capsid protein molecules, into a supramolecular "chain mail." Rationally engineered mutations allow the formation of a regular network of disulfide bridges in the protein lattice. This network links each molecule in the lattice to each adjacent molecule through one covalent bond, analogous to the rivetting of interlinked iron rings in the chain mail of a medieval knight. The engineered protein nanosheet shows greatly increased thermostability and resistance to mechanical stress and fatigue in particular, as well as enhanced self-healing, without undesirable stiffening compared to the original material. The results provide proof of concept for a genetic design to permanently increase fatigue resistance and enhance self-healing of protein-based nanostructured materials. They also provide insights into the molecular basis for fatigue of protein materials.

Lysate-based pipeline to characterize microtubule-associated proteins uncovers unique microtubule behaviours

The microtubule cytoskeleton forms complex macromolecular assemblies with a range of microtubule-associated proteins (MAPs) that have fundamental roles in cell architecture, division and motility. Determining how an individual MAP modulates microtubule behaviour is an important step in understanding the physiological roles of various microtubule assemblies. To characterize how MAPs control microtubule properties and functions, we developed an approach allowing for medium-throughput analyses of MAPs in cell-free conditions using lysates of mammalian cells. Our pipeline allows for quantitative as well as ultrastructural analyses of microtubule-MAP assemblies. Analysing 45 bona fide and potential mammalian MAPs, we uncovered previously unknown activities that lead to distinct and unique microtubule behaviours such as microtubule coiling or hook formation, or liquid-liquid phase separation along the microtubule lattice that initiates microtubule branching. We have thus established a powerful tool for a thorough characterization of a wide range of MAPs and MAP variants, thus opening avenues for the determination of mechanisms underlying their physiological roles and pathological implications.

Genetically engineered materials: Proteins and beyond

Information-rich molecules provide opportunities for evolution. Genetically engineered materials are superior in that their properties are coded within genetic sequences and could be fine-tuned. In this review, we elaborate the concept of genetically engineered materials (GEMs) using examples ranging from engineered protein materials to engineered living materials. Protein-based materials are the materials of choice by nature. Recent progress in protein engineering has led to opportunities to tune their sequences for optimal material performance. Proteins also play a central role in living materials where they act in concert with other biological components as well as nonbiological cofactors, giving rise to living features. While the existing GEMs are often limited to those constructed by building blocks of biological origin, being genetically engineerable does not preclude nonbiologic or synthetic materials, the latter of which have yet to be fully explored.

Mutant libraries reveal negative design shielding proteins from supramolecular self-assembly and relocalization in cells

Genetic mutations fuel organismal evolution but can also cause disease. As proteins are the cell’s workhorses, the ways in which mutations can disrupt their structure, stability, function, and interactions have been studied extensively. However, proteins evolve and function in a cellular context, and our ability to relate changes in protein sequence to cell-level phenotypes remains limited. In particular, the molecular mechanism underlying most disease-associated mutations is unknown. Here, we show that mutations changing a protein’s surface chemistry can dramatically impact its supramolecular self-assembly and localization in the cell. These results highlight the complex nature of genotype–phenotype relationships with a simple system.

Understanding the molecular consequences of mutations in proteins is essential to map genotypes to phenotypes and interpret the increasing wealth of genomic data. While mutations are known to disrupt protein structure and function, their potential to create new structures and localization phenotypes has not yet been mapped to a sequence space. To map this relationship, we employed two homo-oligomeric protein complexes in which the internal symmetry exacerbates the impact of mutations. We mutagenized three surface residues of each complex and monitored the mutations’ effect on localization and assembly phenotypes in yeast cells. While surface mutations are classically viewed as benign, our analysis of several hundred mutants revealed they often trigger three main phenotypes in these proteins: nuclear localization, the formation of puncta, and fibers. Strikingly, more than 50% of random mutants induced one of these phenotypes in both complexes. Analyzing the mutant’s sequences showed that surface stickiness and net charge are two key physicochemical properties associated with these changes. In one complex, more than 60% of mutants self-assembled into fibers. Such a high frequency is explained by negative design: charged residues shield the complex from self-interacting with copies of itself, and the sole removal of the charges induces its supramolecular self-assembly. A subsequent analysis of several other complexes targeted with alanine mutations suggested that such negative design is common. These results highlight that minimal perturbations in protein surfaces’ physicochemical properties can frequently drive assembly and localization changes in a cellular context.

Reconfigurable asymmetric protein assemblies through implicit negative design

Asymmetric multiprotein complexes that undergo subunit exchange play central roles in biology but present a challenge for design because the components must not only contain interfaces that enable reversible association but also be stable and well behaved in isolation. We use implicit negative design to generate β sheet-mediated heterodimers that can be assembled into a wide variety of complexes. The designs are stable, folded, and soluble in isolation and rapidly assemble upon mixing, and crystal structures are close to the computational models. We construct linearly arranged hetero-oligomers with up to six different components, branched hetero-oligomers, closed C4-symmetric two-component rings, and hetero-oligomers assembled on a cyclic homo-oligomeric central hub and demonstrate that such complexes can readily reconfigure through subunit exchange. Our approach provides a general route to designing asymmetric reconfigurable protein systems.

Tiling a tubule: how increasing complexity improves the yield of self-limited assembly

The ability to design and synthesize ever more complicated colloidal particles opens the possibility of self-assembling a zoo of complex structures, including those with one or more self-limited length scales. An undesirable feature of systems with self-limited length scales is that thermal fluctuations can lead to the assembly of nearby, off-target states. We investigate strategies for limiting off-target assembly by using multiple types of subunits. Using simulations and energetics calculations, we explore this concept by considering the assembly of tubules built from triangular subunits that bind edge to edge. While in principle, a single type of triangle can assemble into tubules with a monodisperse width distribution, in practice, the finite bending rigidity of the binding sites leads to the formation of off-target structures. To increase the assembly specificity, we introduce tiling rules for assembling tubules from multiple species of triangles. We show that the selectivity of the target structure can be dramatically improved by using multiple species of subunits, and provide a prescription for choosing the minimum number of subunit species required for near-perfect yield. Our approach of increasing the system's complexity to reduce the accessibility of neighboring structures should be generalizable to other systems beyond the self-assembly of tubules.

Signal Amplification in Highly Ordered Networks Is Driven by Geometry

Here, we hypothesize that, in biological systems such as cell surface receptors that relay external signals, clustering leads to substantial improvements in signaling efficiency. Representing cooperative signaling networks as planar graphs and applying Euler’s polyhedron formula, we can show that clustering may result in an up to a 200% boost in signaling amplitude dictated solely by the size and geometry of the network. This is a fundamental relationship that applies to all clustered systems regardless of its components. Nature has figured out a way to maximize the signaling amplitude in receptors that relay weak external signals. In addition, in cell-to-cell interactions, clustering both receptors and ligands may result in maximum efficiency and synchronization. The importance of clustering geometry in signaling efficiency goes beyond biological systems and can inform the design of amplifiers in nonbiological systems.

SARS-CoV-2 nucleocapsid protein adheres to replication organelles before viral assembly at the Golgi/ERGIC and lysosome-mediated egress

Despite being the target of extensive research efforts due to the COVID-19 (coronavirus disease 2019) pandemic, relatively little is known about the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication within cells. We investigate and characterize the tightly orchestrated virus assembly by visualizing the spatiotemporal dynamics of the four structural SARS-CoV-2 proteins at high resolution. The nucleoprotein is expressed first and accumulates around folded endoplasmic reticulum (ER) membranes in convoluted layers that contain viral RNA replication foci. We find that, of the three transmembrane proteins, the membrane protein appears at the Golgi apparatus/ER-to-Golgi intermediate compartment before the spike and envelope proteins. Relocation of a lysosome marker toward the assembly compartment and its detection in transport vesicles of viral proteins confirm an important role of lysosomes in SARS-CoV-2 egress. These data provide insights into the spatiotemporal regulation of SARS-CoV-2 assembly and refine the current understanding of SARS-CoV-2 replication.

Recent advances in small-angle scattering and its expanding impact in structural biology

Applications of small-angle scattering (SAS) in structural biology have benefited from continuing developments in instrumentation, tools for data analysis, modeling capabilities, standards for data and model presentation, and data archiving. The interplay of these capabilities has enabled SAS to contribute to advances in structural biology as the field pushes the boundaries in studies of biomolecular complexes and assemblies as large as whole cells, membrane proteins in lipid environments, and dynamic systems on time scales ranging from femtoseconds to hours. This review covers some of the important advances in biomolecular SAS capabilities for structural biology focused on over the last 5 years and presents highlights of recent applications that demonstrate how the technique is exploring new territories.

Artificial protein assemblies with well-defined supramolecular protein nanostructures

Nature uses a wide range of well-defined biomolecular assemblies in diverse cellular processes, where proteins are major building blocks for these supramolecular assemblies. Inspired by their natural counterparts, artificial protein-based assemblies have attracted strong interest as new bio-nanostructures, and strategies to construct ordered protein assemblies have been rapidly expanding. In this review, we provide an overview of very recent studies in the field of artificial protein assemblies, with the particular aim of introducing major assembly methods and unique features of these assemblies. Computational de novo designs were used to build various assemblies with artificial protein building blocks, which are unrelated to natural proteins. Small chemical ligands and metal ions have also been extensively used for strong and bio-orthogonal protein linking. Here, in addition to protein assemblies with well-defined sizes, protein oligomeric and array structures with rather undefined sizes (but with definite repeat protein assembly units) also will be discussed in the context of well-defined protein nanostructures. Lastly, we will introduce multiple examples showing how protein assemblies can be effectively used in various fields such as therapeutics and vaccine development. We believe that structures and functions of artificial protein assemblies will be continuously evolved, particularly according to specific application goals.

Protein Assembly by Design

Proteins are nature's primary building blocks for the construction of sophisticated molecular machines and dynamic materials, ranging from protein complexes such as photosystem II and nitrogenase that drive biogeochemical cycles to cytoskeletal assemblies and muscle fibers for motion. Such natural systems have inspired extensive efforts in the rational design of artificial protein assemblies in the last two decades. As molecular building blocks, proteins are highly complex, in terms of both their three-dimensional structures and chemical compositions. To enable control over the self-assembly of such complex molecules, scientists have devised many creative strategies by combining tools and principles of experimental and computational biophysics, supramolecular chemistry, inorganic chemistry, materials science, and polymer chemistry, among others. Owing to these innovative strategies, what started as a purely structure-building exercise two decades ago has, in short order, led to artificial protein assemblies with unprecedented structures and functions and protein-based materials with unusual properties. Our goal in this review is to give an overview of this exciting and highly interdisciplinary area of research, first outlining the design strategies and tools that have been devised for controlling protein self-assembly, then describing the diverse structures of artificial protein assemblies, and finally highlighting the emergent properties and functions of these assemblies.

Complete atomic structure of a native archaeal cell surface

Many prokaryotic cells are covered by an ordered, proteinaceous, sheet-like structure called a surface layer (S-layer). S-layer proteins (SLPs) are usually the highest copy number macromolecules in prokaryotes, playing critical roles in cellular physiology such as blocking predators, scaffolding membranes, and facilitating environmental interactions. Using electron cryomicroscopy of two-dimensional sheets, we report the atomic structure of the S-layer from the archaeal model organism Haloferax volcanii. This S-layer consists of a hexagonal array of tightly interacting immunoglobulin-like domains, which are also found in SLPs across several classes of archaea. Cellular tomography reveal that the S-layer is nearly continuous on the cell surface, completed by pentameric defects in the hexagonal lattice. We further report the atomic structure of the SLP pentamer, which shows markedly different relative arrangements of SLP domains needed to complete the S-layer. Our structural data provide a framework for understanding cell surfaces of archaea at the atomic level.