Computational design of protein self-assembly

A Closer Look at Type I Left-Handed β-Helices Provides a Better Understanding in Their Sequence-Structure Relationship: Toward Their Rational Design

Understanding the sequence-structure relationship in protein is of fundamental interest, but has practical applications such as the rational design of peptides and proteins. This relationship in the Type I left-handed β-helix containing proteins is updated and revisited in this study. Analyzing the available experimental structures in the Protein Data Bank, we could describe, further in detail, the structural features that are important for the stability of this fold, as well as its nucleation and termination. This study is meant to complete previous work, as it provides a separate analysis of the N-terminal and C-terminal rungs of the helix. Particular sequence motifs of these rungs are described along with the structural element they form.

Self-assembling peptides: Perspectives regarding biotechnological applications and vaccine development

Self-assembly involves a set of molecules spontaneously interacting in a highly coordinated and dynamic manner to form a specific supramolecular structure having new and clearly defined properties. Many examples of this occur in nature and many more came from research laboratories, with their number increasing every day via ongoing research concerning complex biomolecules and the possibility of harnessing it when developing new applications. As a phenomenon, self-assembly has been described on very different types of molecules (biomolecules including), so this review focuses on what is known about peptide self-assembly, its origins, the forces behind it, how the properties of the resulting material can be tuned in relation to experimental considerations, some biotechnological applications (in which the main protagonists are peptide sequences capable of self-assembly) and what is yet to be tuned regarding their research and development.

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.

Protein-protein interaction prediction with deep learning: A comprehensive review

Most proteins perform their biological function by interacting with themselves or other molecules. Thus, one may obtain biological insights into protein functions, disease prevalence, and therapy development by identifying protein-protein interactions (PPI). However, finding the interacting and non-interacting protein pairs through experimental approaches is labour-intensive and time-consuming, owing to the variety of proteins. Hence, protein-protein interaction and protein-ligand binding problems have drawn attention in the fields of bioinformatics and computer-aided drug discovery. Deep learning methods paved the way for scientists to predict the 3-D structure of proteins from genomes, predict the functions and attributes of a protein, and modify and design new proteins to provide desired functions. This review focuses on recent deep learning methods applied to problems including predicting protein functions, protein-protein interaction and their sites, protein-ligand binding, and protein design.

Predictive Modeling of Neurotoxic α-Synuclein Polymorphs

Assembly of monomeric α-synuclein (αS) into aggregation-resistant helically folded tetramers and related multimers is a key target for Parkinson's disease (PD). Protein dynamics hampers experimental characterization of the polymorphism of these structures and so computational modeling and simulation is providing a complementary approach to obtain high-resolution structural information on the assembly of αS and interactions with biological surfaces. These computational techniques are particularly valuable for intrinsically disordered proteins (IDPs) and short-lived peptide and protein assemblies with as yet undetermined 3D structures. Experimental observables such as NMR J-coupling constants and chemical shifts can be predicted directly from simulation data, and compared with available experimental data to generate the most physically realistic atomic-resolution structure. For appropriately validated and benchmarked computational models, macroscopic aggregation properties can be related to the calculated thermodynamic properties at an atomic level. In this chapter, we describe a useful protocol for designing helical αS multimers, especially tetramers, and scanning the peptide-membrane interface for cell-bound αS tetramers. These computationally modeled structures are validated by comparison with the range of available known experimental parameters at time of writing in early 2020, and used to generate predictive design rules to motivate and guide experiments.

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.

Peptide Design and Self-assembly into Targeted Nanostructure and Functional Materials

Peptides have been extensively utilized to construct nanomaterials that display targeted structure through hierarchical assembly. The self-assembly of both rationally designed peptides derived from naturally occurring domains in proteins as well as intuitively or computationally designed peptides that form β-sheets and helical secondary structures have been widely successful in constructing nanoscale morphologies with well-defined 1-d, 2-d, and 3-d architectures. In this review, we discuss these successes of peptide self-assembly, especially in the context of designing hierarchical materials. In particular, we emphasize the differences in the level of peptide design as an indicator of complexity within the targeted self-assembled materials and highlight future avenues for scientific and technological advances in this field.

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.

Bionanomaterials based on protein self-assembly: Design and applications in biotechnology

Elegant protein assembly to generate new biomaterials undergoes extremely rapid development for wide extension of biotechnology applications, which can be a powerful tool not only for creating nanomaterials but also for advancing understanding of the structure of life. Unique biological properties of proteins bestow these artificial biomaterials diverse functions that can permit them to be applied in encapsulation, bioimaging, biocatalysis, biosensors, photosynthetic apparatus, electron transport, magnetogenetic applications, vaccine development and antibodies design. This review gives a perspective view of the latest advances in the construction of protein-based nanomaterials. We initially start with distinguishable, specific interactions to construct sundry nanomaterials through protein self-assembly and concisely expound the assembly mechanism from the design strategy. And then, the design and construction of 0D, 1D, 2D, 3D protein assembled nanomaterials are especially highlighted. Furthermore, the potential applications have been discussed in detail. Overall, this review will illustrate how to fabricate highly sophisticated nanomaterials oriented toward applications in biotechnology based on the rules of supramolecular chemistry.

General Methods to Produce and Assemble Recombinant Spider Silk Proteins

Orb-weaving spiders are known to spin up to seven types of silks/glues from different silk glands. The inherent mechanical variety of these silks makes them attractive models for a variety of biomaterial design, from superglues to extremely strong and/or extendible fibers. Spider silk spinning is a process in which spinning dope stored in specific glands assembles into fibrils upon chemical and mechanical stimuli. The exploration of silk protein assembly into controllable filaments is vital for both uncovering biological functions and molecular structure relationship, as well as fabricating new biomaterials. This chapter describes the methods for biosynthesis and assembly of recombinant spider silk proteins, which will provide insights into the mechanism exploration of fiber formation and spider silk-based material manufacture.

Designed Artificial Protein Heterodimers With Coupled Functions Constructed Using Bio-Orthogonal Chemistry

The formation of protein complexes is central to biology, with oligomeric proteins more prevalent than monomers. The coupling of functionally and even structurally distinct protein units can lead to new functional properties not accessible by monomeric proteins alone. While such complexes are driven by evolutionally needs in biology, the ability to link normally functionally and structurally disparate proteins can lead to new emergent properties for use in synthetic biology and the nanosciences. Here we demonstrate how two disparate proteins, the haem binding helical bundle protein cytochrome b 562 and the β-barrel green fluorescent protein can be combined to form a heterodimer linked together by an unnatural triazole linkage. The complex was designed using computational docking approaches to predict compatible interfaces between the two proteins. Models of the complexes where then used to engineer residue coupling sites in each protein to link them together. Genetic code expansion was used to incorporate azide chemistry in cytochrome b 562 and alkyne chemistry in GFP so that a permanent triazole covalent linkage can be made between the two proteins. Two linkage sites with respect to GFP were sampled. Spectral analysis of the new heterodimer revealed that haem binding and fluorescent protein chromophore properties were retained. Functional coupling was confirmed through changes in GFP absorbance and fluorescence, with linkage site determining the extent of communication between the two proteins. We have thus shown here that is possible to design and build heterodimeric proteins that couple structurally and functionally disparate proteins to form a new complex with new functional properties.

Serum albumin guided plasmonic nanoassemblies with opposite chiralities

Chiral assemblies by combining natural biomolecules with plasmonic nanostructures hold great promise for plasmonic enhanced sensing, imaging, and catalytic applications. Herein, we demonstrate that human serum albumin (HSA) and porcine serum albumin (PSA) can guide the chiral assembly of gold nanorods (GNRs) with left-handed chiroptical responses opposite to those by a series of other homologous animal serum albumins (SAs) due to the difference of their surface charge distributions. Under physiological pH conditions, the assembly of HSA or PSA with GNRs yielded left-handed twisted aggregates, while bovine serum albumin (BSA), sheep serum albumin, and equine serum albumin behaved on the contrary. The driving force for the chiral assembly is mainly attributed to electrostatic interaction. The opposite chiroptical signals acquired are correlated with the chiral surface charge distributions of the tertiary structures of SAs. Moreover, the chirality of the assembly induced by both HSA and BSA can be enhanced or reversed by adjusting the pH values. This work provides new insights into the modulation of protein-induced chiral assemblies and promotes their applications.

Structure-based design of novel polyhedral protein nanomaterials

Organizing matter at the atomic scale is a central goal of nanotechnology. Bottom-up approaches, in which molecular building blocks are programmed to assemble via supramolecular interactions, are a proven and versatile route to new and useful nanomaterials. Although a wide variety of molecules have been used as building blocks, proteins have several intrinsic features that present unique opportunities for designing nanomaterials with sophisticated functions. There has been tremendous recent progress in designing proteins to fold and assemble to highly ordered structures. Here we review the leading approaches to the design of closed polyhedral protein assemblies, highlight the importance of considering the assembly process itself, and discuss various applications and future directions for the field. We emphasize throughout the exciting opportunities presented by recent advances as well as challenges that remain.

A theoretical study of polymorphism in VQIVYK fibrils

The VQIVYK fragment from the Tau protein, also known as PHF6, is essential for aggregation of Tau into neurofibrillary lesions associated with neurodegenerative diseases. VQIVYK itself forms amyloid fibrils composed of paired β-sheets. Therefore, the full Tau protein and VQIVYK fibrils have been intensively investigated. A central issue in these studies is polymorphism, the ability of a protein to fold into more than one structure. Using all-atom molecular simulations, we generate five stable polymorphs of VQIVYK fibrils, establish their relative free energy with umbrella sampling methods, and identify the side chain interactions that provide stability. The two most stable polymorphs, which have nearly equal free energy, are formed by interdigitation of the mostly hydrophobic VIY "face" sides of the β-sheets. Another stable polymorph is formed by interdigitation of the QVK "back" sides. When we turn to examine structures from cryo-electron microscopy experiments on Tau filaments taken from diseased patients or generated in vitro, we find that the pattern of side chain interactions found in the two most stable face-to-face as well as the back-to-back polymorphs are recapitulated in amyloid structures of the full protein. Thus, our studies suggest that the interactions stabilizing PHF6 fibrils explain the amyloidogenicity of the VQIVYK motif within the full Tau protein and provide justification for the use of VQIVYK fibrils as a test bed for the design of molecules that identify or inhibit amyloid structures.

Recent progress in designing protein-based supramolecular assemblies

The design of protein-based assemblies is an emerging area in bionanotechnology with wide ranging applications, from vaccines to smart biomaterials. Design approaches have sought to mimic both the topologies of assemblies observed in nature, as well as their functionally relevant properties, such as being responsive to external cues. In the last few years, diverse design approaches have been used to construct assemblies with integer-dimensional (e.g. filaments, layers, lattices and polyhedra) and non-integer-dimensional (fractal) topologies. Supramolecular structures that assemble/disassemble in response to chemical and physical stimuli have also been built. Hybrid protein-DNA assemblies have expanded the set of building blocks used for generating supramolecular architectures. While still far from reproducing the sophistication of natural assemblies, these exciting results represent important steps towards the design of responsive and functional biomaterials built from the bottom up. As the complexity of topologies and diversity of building blocks increases, considerations of both thermodynamics and kinetics of assembly formation will play crucial roles in making the design of protein-based assemblies robust and useful.

Fabrication of Pascal-triangle Lattice of Proteins by Inducing Ligand Strategy

A protein Pascal triangle has been constructed as new type of supramolecular architecture by using the inducing ligand strategy that we previously developed for protein assemblies. Although mathematical studies on this famous geometry have a long history, no work on such Pascal triangles fabricated from native proteins has been reported so far due to their structural complexity. In this work, by carefully tuning the specific interactions between the native protein building block WGA and the inducing ligand R-SL, a 2D Pascal-triangle lattice with three types of triangular voids has been assembled. Moreover, a 3D crystal structure was obtained based on the 2D Pascal triangles. The distinctive carbohydrate binding sites of WGA and the intralayer as well as interlayer dimerization of RhB was the key to facilitate nanofabrication in solution. This strategy may be applied to prepare and explore various sophisticated assemblies based on native proteins.

Better together: building protein oligomers naturally and by design

Protein oligomers are more common in nature than monomers, with dimers being the most prevalent final structural state observed in known structures. From a biological perspective, this makes sense as it conserves vital molecular resources that may be wasted simply by generating larger single polypeptide units, and allows new features such as cooperativity to emerge. Taking inspiration from nature, protein designers and engineers are now building artificial oligomeric complexes using a variety of approaches to generate new and useful supramolecular protein structures. Oligomerisation is thus offering a new approach to sample structure and function space not accessible through simply tinkering with monomeric proteins.

De novo protein design, a retrospective

Proteins are molecular machines whose function depends on their ability to achieve complex folds with precisely defined structural and dynamic properties. The rational design of proteins from first-principles, or de novo, was once considered to be impossible, but today proteins with a variety of folds and functions have been realized. We review the evolution of the field from its earliest days, placing particular emphasis on how this endeavor has illuminated our understanding of the principles underlying the folding and function of natural proteins, and is informing the design of macromolecules with unprecedented structures and properties. An initial set of milestones in de novo protein design focused on the construction of sequences that folded in water and membranes to adopt folded conformations. The first proteins were designed from first-principles using very simple physical models. As computers became more powerful, the use of the rotamer approximation allowed one to discover amino acid sequences that stabilize the desired fold. As the crystallographic database of protein structures expanded in subsequent years, it became possible to construct proteins by assembling short backbone fragments that frequently recur in Nature. The second set of milestones in de novo design involves the discovery of complex functions. Proteins have been designed to bind a variety of metals, porphyrins, and other cofactors. The design of proteins that catalyze hydrolysis and oxygen-dependent reactions has progressed significantly. However, de novo design of catalysts for energetically demanding reactions, or even proteins that bind with high affinity and specificity to highly functionalized complex polar molecules remains an importnant challenge that is now being achieved. Finally, the protein design contributed significantly to our understanding of membrane protein folding and transport of ions across membranes. The area of membrane protein design, or more generally of biomimetic polymers that function in mixed or non-aqueous environments, is now becoming increasingly possible.

Bioengineering oligomerization and monomerization of enzymes: learning from natural evolution to matching the demands for industrial applications

It is generally accepted that oligomeric enzymes evolve from their monomeric ancestors, and the evolution process generates superior structural benefits for functional advantages. Furthermore, adjusting the transition between different oligomeric states is an important mechanism for natural enzymes to regulate their catalytic functions for adapting environmental fluctuations in nature, which inspires researchers to mimic such a strategy to develop artificially oligomerized enzymes through protein engineering for improved performance under specific conditions. On the other hand, transforming oligomeric enzymes into their monomers is needed in fundamental research for deciphering catalytic mechanisms as well as exploring their catalytic capacities for better industrial applications. In this article, strategies for developing artificially oligomerized and monomerized enzymes are reviewed and highlighted by their applications. Furthermore, advances in the computational prediction of oligomeric structures are introduced, which would accelerate the systematic design of oligomeric and monomeric enzymes. Finally, the current challenges and future directions in this field are discussed.

Self-assembly of a dimer system

In the self-assembly process which drives the formation of cellular membranes, micelles, and capsids, a collection of separated subunits spontaneously binds together to form functional and more ordered structures. In this work, we study the statistical physics of self-assembly in a simpler scenario: the formation of dimers from a system of monomers. The properties of the model allow us to frame the microstate counting as a combinatorial problem whose solution leads to an exact partition function. From the associated equilibrium conditions, we find that such dimer systems come in two types: "search-limited" and "combinatorics-limited," only the former of which has states where partial assembly can be dominated by correct contacts. Using estimates of biophysical quantities in systems of single-stranded DNA dimerization, transcription factor and DNA interactions, and protein-protein interactions, we find that all of these systems appear to be of the search-limited type, i.e., their fully correct dimerization regimes are more limited by the ability of monomers to find one another in the constituent volume than by the combinatorial disadvantage of correct dimers. We derive the parameter requirements for fully correct dimerization and find that rather than the ratio of particle number and volume (i.e., number density) being the relevant quantity, it is the product of particle diversity and volume that is constrained. Ultimately, this work contributes to an understanding of self-assembly by using the simple case of a system of dimers to analytically study the combinatorics of assembly.

The de novo design of α-helical peptides for supramolecular self-assembly

One approach to designing de novo proteinaceous assemblies and materials is to develop simple, standardised building blocks and then to combine these symmetrically to construct more-complex higher-order structures. This has been done extensively using β-structured peptides to produce peptide fibres and hydrogels. Here, we focus on building with de novo α-helical peptides. Because of their self-contained, well-defined structures and clear sequence-to-structure relationships, α helices are highly programmable making them robust building blocks for biomolecular construction. The progress made with this approach over the past two decades is astonishing and has led to a variety of de novo assemblies, including discrete nanoscale objects, and fibrous, nanotube, sheet and colloidal materials. This body of work provides an exceptionally strong foundation for advancing the field beyond in vitro design and into in vivo applications including what we call protein design in cells.

Infinite Assembly of Folded Proteins in Evolution, Disease, and Engineering

Mutations and changes in a protein's environment are well known for their potential to induce misfolding and aggregation, including amyloid formation. Alternatively, such perturbations can trigger new interactions that lead to the polymerization of folded proteins. In contrast to aggregation, this process does not require misfolding and, to highlight this difference, we refer to it as agglomeration. This term encompasses the amorphous assembly of folded proteins as well as the polymerization in one, two, or three dimensions. We stress the remarkable potential of symmetric homo-oligomers to agglomerate even by single surface point mutations, and we review the double-edged nature of this potential: how aberrant assemblies resulting from agglomeration can lead to disease, but also how agglomeration can serve in cellular adaptation and be exploited for the rational design of novel biomaterials.

Synthetic Biology for Multiscale Designed Biomimetic Assemblies: From Designed Self-Assembling Biopolymers to Bacterial Bioprinting

Nature is based on complex self-assembling systems that span from the nanoscale to the macroscale. We have already begun to design biomimetic systems with properties that have not evolved in nature, based on designed molecular interactions and regulation of biological systems. Synthetic biology is based on the principle of modularity, repurposing diverse building modules to design new types of molecular and cellular assemblies. While we are currently able to use techniques from synthetic biology to design self-assembling molecules and re-engineer functional cells, we still need to use guided assembly to construct biological assemblies at the macroscale. We review the recent strategies for designing biological systems ranging from molecular assemblies based on self-assembly of (poly)peptides to the guided assembly of patterned bacteria, spanning 7 orders of magnitude.

Bioinspired genetic engineering of supramolecular assembled formate dehydrogenase with enhanced biocatalysis activities

A bioinspired strategy for the synthesis of supramolecular and biocatalytical materials was developed base on protein-protein supramolecular interaction and genetic engineering. Formate dehydrogenase (FDH) and its functional fragments were separately fused to form a multi-function domain. The fusion proteins and functional fragments self-assembled into the expanded and controllable supramolecular interaction networks. Morphology characterization by scanning-electron microscopy showed that the assembled functional fragments and fusion proteins formed multi-dimensional (3D) and two-dimensional (2D) layer-like structures. Moreover, the oligomeric biocatalysts exhibited higher structural stability and NAD(H) recycling efficiency than the unassembled structures when they were applied to a co-enzyme regeneration system. These results suggest that the bioinspired strategy provides a promising approach for the fabrication of supramolecular FDH materials via genetic engineering and self-assembly. The significant improvement on the biocatalytical activity reveals the essential role of supramolecular interface design in their biocatalysis applications.

On the ubiquity of helical α-synuclein tetramers

The stability of oligomers linearly increases from dimers to octamers, but assembly of oligomers larger than tetramers requires high activation energies.

Self-Assembly of Ferritin: Structure, Biological Function and Potential Applications in Nanotechnology

Protein cages are normally formed by the self-assembly of multiple protein subunits and ferritin is a typical example of a protein cage structure. Ferritin is a ubiquitous multi-subunit iron storage protein formed by 24 polypeptide chains that self-assemble into a hollow, roughly spherical protein cage. Ferritin has external and internal diameters of approximately 12 nm and 8 nm, respectively. Functionally, ferritin performs iron sequestration and is highly conserved in evolution. The interior cavity of ferritin provides a unique reaction vessel to carry out reactions separated from the exterior environment. In nature, the cavity is utilized for sequestration of iron and bio-mineralization as a mechanism to render iron inert and safe from the external environment. Material scientists have been inspired by this system and exploited a range of ferritin superfamily proteins as supramolecular templates to encapsulate different carrier molecules ranging from cancer drugs to therapeutic proteins, in addition to using ferritin proteins as well-defined building blocks for fabrication. Besides the interior cavity, the exterior surface and sub-unit interface of ferritin can be modified without affecting ferritin assembly.

Engineering and evaluation of amyloid assemblies as a nanovaccine against the Chikungunya virus

The design of nanoparticles exposing a high density of antigens constitutes a promising strategy to address safety concerns of conventional life-attenuated vaccines as well as to increase the immunogenicity of subunit vaccines. In this study, we developed a fully synthetic nanovaccine based on an amyloid peptide sequence with high self-assembling properties. The immunogenic epitope E2EP3 from the E2 glycoprotein of the Chikungunya virus was used to evaluate the potential of a 10-mer peptide derived from an endogenous amyloidogenic polypeptide as a novel vaccine platform. Chimeric peptides, comprising the peptide antigen attached to the amyloid core by a short flexible linker, were prepared by solid phase synthesis. As observed using atomic force microscopy, these polypeptides self-assembled into linear and unbranched fibrils with a diameter ranging from 6 to 8 nm. A quaternary conformation rich in cross-β-sheets characterized these assemblies, as demonstrated by circular dichroism spectroscopy and thioflavin T fluorescence. ELISA assays and transmission electronic microscopy of immunogold labeled-fibrils revealed a high density of the Chikungunya virus E2 glycoprotein derived epitope exposed on the fibril surface. These amyloid fibrils were cytocompatible and were efficiently uptaken by macrophages. Mice immunization revealed a robust IgG response against the E2EP3 epitope, which was dependent on self-assembly and did not require co-injection of the Alhydrogel adjuvant. These results indicate that cross-β-sheet amyloid assemblies constitute suitable synthetic self-adjuvanted assemblies to anchor antigenic determinants and to increase the immunogenicity of peptide epitopes.

Fibrous Protein Self-Assembly in Biomimetic Materials

Protein self-assembly processes, by which polypeptides interact and independently form multimeric structures, lead to a wide array of different endpoints. Structures formed range from highly ordered molecular crystals to amorphous aggregates. Order arises in the system from a balance between many low-energy processes occurring due to a set of interactions between residues in a chain, between residues in different chains, and between solute and solvent. In Nature, self-assembling protein systems have evolved over millions of years to organize into supramolecular structures, optimized for specific functions, with this propensity determined by the sequence of their constituent amino acids, of which only 20 are encoded in DNA. The structural materials that arise from biological self-assembly can display remarkable mechanical properties, often as a result of hierarchical structure on the nano- and microscales, and much research has been devoted to mimicking and exploiting these properties for a variety of end uses. This work presents a review of a range of studies in which biological functions are effectively reproduced through the design of self-assembling fibrous protein systems.

Bioengineering Strategies for Protein-Based Nanoparticles

In recent years, the practical application of protein-based nanoparticles (PNPs) has expanded rapidly into areas like drug delivery, vaccine development, and biocatalysis. PNPs possess unique features that make them attractive as potential platforms for a variety of nanobiotechnological applications. They self-assemble from multiple protein subunits into hollow monodisperse structures; they are highly stable, biocompatible, and biodegradable; and their external components and encapsulation properties can be readily manipulated by chemical or genetic strategies. Moreover, their complex and perfect symmetry have motivated researchers to mimic their properties in order to create de novo protein assemblies. This review focuses on recent advances in the bioengineering and bioconjugation of PNPs and the implementation of synthetic biology concepts to exploit and enhance PNP's intrinsic properties and to impart them with novel functionalities.

Engineering the entropy-driven free-energy landscape of a dynamic nanoporous protein assembly

De novo design and construction of stimuli-responsive protein assemblies that predictably switch between discrete conformational states remains an essential but highly challenging goal in biomolecular design. We previously reported synthetic, two-dimensional protein lattices self-assembled via disulfide bonding interactions, which endows them with a unique capacity to undergo coherent conformational changes without losing crystalline order. Here, we carried out all-atom molecular dynamics simulations to map the free-energy landscape of these lattices, validated this landscape through extensive structural characterization by electron microscopy and established that it is predominantly governed by solvent reorganization entropy. Subsequent redesign of the protein surface with conditionally repulsive electrostatic interactions enabled us to predictably perturb the free-energy landscape and obtain a new protein lattice whose conformational dynamics can be chemically and mechanically toggled between three different states with varying porosities and molecular densities.

Computational Protein Design with Deep Learning Neural Networks

Computational protein design has a wide variety of applications. Despite its remarkable success, designing a protein for a given structure and function is still a challenging task. On the other hand, the number of solved protein structures is rapidly increasing while the number of unique protein folds has reached a steady number, suggesting more structural information is being accumulated on each fold. Deep learning neural network is a powerful method to learn such big data set and has shown superior performance in many machine learning fields. In this study, we applied the deep learning neural network approach to computational protein design for predicting the probability of 20 natural amino acids on each residue in a protein. A large set of protein structures was collected and a multi-layer neural network was constructed. A number of structural properties were extracted as input features and the best network achieved an accuracy of 38.3%. Using the network output as residue type restraints improves the average sequence identity in designing three natural proteins using Rosetta. Moreover, the predictions from our network show ~3% higher sequence identity than a previous method. Results from this study may benefit further development of computational protein design methods.

Harnessing self-assembled peptide nanoparticles in epitope vaccine design

Vaccination has been one of the most successful breakthroughs in medical history. In recent years, epitope-based subunit vaccines have been introduced as a safer alternative to traditional vaccines. However, they suffer from limited immunogenicity. Nanotechnology has shown value in solving this issue. Different kinds of nanovaccines have been employed, among which virus-like nanoparticles (VLPs) and self-assembled peptide nanoparticles (SAPNs) seem very promising. Recently, SAPNs have attracted special interest due to their unique properties, including molecular specificity, biodegradability, and biocompatibility. They also resemble pathogens in terms of their size. Their multivalency allows an orderly repetitive display of antigens on their surface, which induces a stronger immune response than single immunogens. In vaccine design, SAPN self-adjuvanticity is regarded an outstanding advantage, since the use of toxic adjuvants is no longer required. SAPNs are usually composed of helical or β-sheet secondary structures and are tailored from natural peptides or de novo structures. Flexibility in subunit selection opens the door to a wide variety of molecules with different characteristics. SAPN engineering is an emerging area, and more novel structures are expected to be generated in the future, particularly with the rapid progress in related computational tools. The aim of this review is to provide a state-of-the-art overview of self-assembled peptide nanoparticles and their use in vaccine design in recent studies. Additionally, principles for their design and the application of computational approaches to vaccine design are summarized.

Symmetry-Directed Self-Assembly of a Tetrahedral Protein Cage Mediated by de Novo-Designed Coiled Coils

The organization of proteins into new hierarchical forms is an important challenge in synthetic biology. However, engineering new interactions between protein subunits is technically challenging and typically requires extensive redesign of protein-protein interfaces. We have developed a conceptually simple approach, based on symmetry principles, that uses short coiled-coil domains to assemble proteins into higher-order structures. Here, we demonstrate the assembly of a trimeric enzyme into a well-defined tetrahedral cage. This was achieved by genetically fusing a trimeric coiled-coil domain to its C terminus through a flexible polyglycine linker sequence. The linker length and coiled-coil strength were the only parameters that needed to be optimized to obtain a high yield of correctly assembled protein cages.

Archaeal Lsm rings as stable self-assembling tectons for protein nanofabrication

We have exploited the self-assembling properties of archaeal-derived protein Lsmα to generate new supramolecular forms based on its stable ring-shaped heptamer. We show that engineered ring tectons incorporating cysteine sidechains on obverse faces of the Lsmα₇ toroid are capable of forming paired and stacked formations. A Cys-modified construct, N10C/E61C-Lsmα, appears to organize into disulfide-mediated tube formations up to 45 nm in length. We additionally report fabrication of cage-like protein clusters through conjugation of Cu²⁺ to His-tagged variants of the Lsmα₇ tecton. These 400 kDa protein capsules are seen as cube particles with visible pores, and are reversibly dissembled into their component ring tectons by EDTA. The β-rich Lsmα supramolecular assemblies described are amenable to further fusion modifications, or for surface attachment, so providing potential for future applications that exploit the RNA-binding capacity of Lsm proteins, such as sensing applications.

Coiled-Coil Design: Updated and Upgraded

α-Helical coiled coils are ubiquitous protein-folding and protein-interaction domains in which two or more α-helical chains come together to form bundles. Through a combination of bioinformatics analysis of many thousands of natural coiled-coil sequences and structures, plus empirical protein engineering and design studies, there is now a deep understanding of the sequence-to-structure relationships for this class of protein architecture. This has led to considerable success in rational design and what might be termed in biro de novo design of simple coiled coils, which include homo- and hetero-meric parallel dimers, trimers and tetramers. In turn, these provide a toolkit for directing the assembly of both natural proteins and more complex designs in protein engineering, materials science and synthetic biology. Moving on, the increased and improved use of computational design is allowing access to coiled-coil structures that are rare or even not observed in nature, for example α-helical barrels, which comprise five or more α-helices and have central channels into which different functions may be ported. This chapter reviews all of these advances, outlining improvements in our knowledge of the fundamentals of coiled-coil folding and assembly, and highlighting new coiled coil-based materials and applications that this new understanding is opening up. Despite considerable progress, however, challenges remain in coiled-coil design, and the next decade promises to be as productive and exciting as the last.