Browsing by Subject "Self-assembly"

The control of matter and phenomena at the nanoscale is fast becoming one of the most important challenges of the 21st century with wide-ranging applications from energy and health care to computing and material science. Conventional top-down approaches to nanotechnology, having served us well for long, are reaching their inherent limitations. Meanwhile, bottom-up methods such as self-assembly are emerging as viable alternatives for nanoscale fabrication and manipulation.

A particularly successful bottom up technique is DNA self-assembly where a set of carefully designed DNA strands form a nanoscale object as a consequence of specific, local interactions among the different components, without external direction. The final product of the self-assembly process might be a static nanostructure or a dynamic nanodevice that performs a specific function. Over the past two decades, DNA self-assembly has produced stunning nanoscale objects such as 2D and 3D lattices, polyhedra and addressable arbitrary shaped substrates, and a myriad of nanoscale devices such as molecular tweezers, computational circuits, biosensors and molecular assembly lines. In this dissertation we study multiple problems in the theory, simulations and experiments of DNA self-assembly.

We extend the Turing-universal mathematical framework of self-assembly known as the Tile Assembly Model by incorporating randomization during the assembly process. This allows us to reduce the tile complexity of linear assemblies. We develop multiple techniques to build linear assemblies of expected length N using far fewer tile types than previously possible.

We abstract the fundamental properties of DNA and develop a biochemical system, which we call meta-DNA, based entirely on strands of DNA as the only component molecule. We further develop various enzyme-free protocols to manipulate meta-DNA systems and provide strand level details along with abstract notations for these mechanisms.

We simulate DNA circuits by providing detailed designs for local molecular computations that involve spatially contiguous molecules arranged on addressable substrates via enzyme-free DNA hybridization reaction cascades. We use the Visual DSD simulation software in conjunction with localized reaction rates obtained from biophysical modeling to create chemical reaction networks of localized hybridization circuits that are then model checked using the PRISM model checking software.

We develop a DNA detection system employing the triggered self-assembly of a novel DNA dendritic nanostructure. Detection begins when a specific, single-stranded target DNA strand triggers a hybridization chain reaction between two distinct DNA hairpins. Each hairpin opens and hybridizes up to two copies of the other, and hence each layer of the growing dendritic nanostructure can in principle accommodate an exponentially increasing number of cognate molecules, generating a nanostructure with high molecular weight.

We build linear activatable assemblies employing a novel protection/deprotection strategy to strictly enforce the direction of tiling assembly growth to ensure the robustness of the assembly process. Our system consists of two tiles that can form a linear co-polymer. These tiles, which are initially protected such that they do not react with each other, can be activated to form linear co-polymers via the use of a strand displacing enzyme.

Traditional small molecule chemotherapeutics show limited effectiveness in the clinic as their poor pharmacokinetics lead to rapid clearance from circulation and their exposure to off-target tissues results in dose-limiting toxicity. The objective of this dissertation is to exploit a class of recombinant chimeric polypeptides (CPs) to actively target drugs to tumors as conjugation to macromolecular carriers has demonstrated improved efficacy by increasing plasma retention time, reducing uptake by healthy tissues, and enhancing tumor accumulation by exploiting the leaky vasculature and impaired lymphatic drainage characteristic of solid tumors. CPs consist of two principal components: (1) a thermally responsive elastin-like polypeptide (ELP) that displays a soluble-to-aggregate phase transition above a characteristic transition temperature (Tt); and (2) a cysteine-rich peptide fused to one end of the ELP to which small molecule therapeutics can be covalently attached (the conjugation domain). This work describes the development of CP drug-loaded nanoparticles that can be targeted to solid tumors by the external application of mild regional hyperthermia (39-43°C).

Highly repetitive ELP polymers were assembled by Plasmid Reconstruction Recursive Directional Ligation (PRe-RDL), in which two halves of a parent plasmid, each containing a copy of an oligomer, were ligated together to dimerize the oligomer and reconstitute the functional plasmid. Chimeric polypeptides were constructed by fusing the ELP sequence to a (CGG)8 conjugation domain, expressed in Escherichia coli, and loaded with small molecule hydrophobes through site specific attachment to the conjugation domain. Drug attachment induced the assembly of nanoparticles that retained the thermal responsiveness of the parent ELP in that they experienced a phase transition from soluble nanoparticles to an aggregated phase above their Tt. Importantly, the Tt of these nanoparticles was near-independent of the CP concentration and the structure of the conjugated molecule as long as it displayed an octanol-water distribution coefficient (LogD) > 1.5.

A series of CP nanoparticles with varying ratios of alanine and valine in the guest residue position was used to develop a quantitative model that described the CP transition temperature in terms of three variables - sequence, chain length, and concentration - and the model was used to identify CPs of varying molecular weights that displayed transition temperatures between 39°C and 43°C. A murine dorsal skin fold window chamber model using a human tumor xenograft was used to validate that only the thermoresponsive CP nanoparticles (and not the controls) exhibited a micelle-to-aggregate phase transition between 39-43°C in vivo. Furthermore, quantitative analysis of the biodistribution profile demonstrated that accumulation of these thermoresponsive CP nanoparticles was significantly enhanced by applying heat in a cyclical manner. It is hoped that this work will provide a helpful resource for the use of thermoresponsive CP nanoparticles in a variety of biomedical applications.

Self-assembly is a pervasive natural phenomenon that gives rise to complex structures and functions. It describes processes in which a disordered system of components form organized structures as a consequence of specific, local interactions among the components themselves, without any external direction. Biological self-assembled systems, evolved over billions of years, are more intricate, more energy efficient and more functional than anything researchers have currently achieved at the nanoscale. A challenge for human designed physical self-assembled systems is to catch up with mother nature. I argue through examples that DNA is an apt material to meet this challenge. This work presents:

1. 3D self-assembled DNA nanostructures.

2. Illustrations of the simplicity and power of toehold-mediated strand displacement interactions.

3. Algorithmic constructs in the tile assembly model.

Pattern formation is a mysterious phenomenon occurring at all scales in nature. The beauty of the resulting structures and myriad of resulting properties occurring in naturally forming patterns have attracted great interest from scientists and engineers. One of the most convenient experimental models for studying pattern formation are colloidal particle suspensions, which can be used both to explore condensed matter phenomena and as a powerful fabrication technique for forming advanced materials. In my thesis, I have focused on the study of colloidal patterns, which can be conveniently tracked in an optical microscope yet can also be thermally equilibrated on experimentally relevant time scales, allowing for ground states and transitions between them to be studied with optical tracking algorithms.

In particular, I have focused on systems that spontaneously organize due to particle-surface and particle-particle interactions, paying close attention to systems that can be dynamically adjusted with an externally applied magnetic or acoustic field. In the early stages of my doctoral studies, I developed a magnetic field manipulation technique to quantify the adhesion force between particles and surfaces. This manipulation technique is based on the magnetic dipolar interactions between colloidal particles and their "image dipoles" that appear within planar substrate. Since the particles interact with their own images, this system enables massively parallel surface force measurements (>100 measurements) in a single experiment, and allows statistical properties of particle-surface adhesion energies to be extracted as a function of loading rate. With this approach, I was able to probe sub-picoNewton surface interactions between colloidal particles and several substrates at the lowest force loading rates ever achieved.

In the later stages of my doctoral studies, I focused on studying patterns formed from particle-particle interaction, which serve as an experimental model of phase transitions in condensed matter systems that can be tracked with single particle resolution. Compared with other research on colloidal crystal formation, my research has focused on multi-component colloidal systems of magnetic and non-magnetic colloids immersed in a ferrofluid. Initially, I studied the types of patterns that form as a function of the concentrations of the different particles and ferrofluid, and I discovered a wide variety of chains, rings and crystals forming in bi-component and tri-component systems. Based on these results, I narrowed my focus to one specific crystal structure (checkerboard lattice) as a model of phase transformations in alloy. Liquid/solid phase transitions were studied by slowly adjusting the magnetic field strength, which serves to control particle-particle interactions in a manner similar to controlling the physical temperature of the fluid. These studies were used to determine the optimal conditions for forming large single crystal structures, and paved the way for my later work on solid/solid phase transitions when the angle of the external field was shifted away from the normal direction. The magnetostriction coefficient of these crystals was measured in low tilt angle of the applied field. At high tilt angles, I observed a variety of martensitic transformations, which followed different pathways depending on the crystal direction relative to the in-plane field.

In the last part of my doctoral studies, I investigated colloidal patterns formed in a superimposed acoustic and magnetic field. In this approach, the magnetic field mimics "temperature", while the acoustic field mimics "pressure". The ability to simultaneously tune both temperature and pressure allows for more efficient exploration of phase space. With this technique I demonstrated a large class of particle structures ranging from discrete molecule-like clusters to well ordered crystal phases. Additionally, I demonstrated a crosslinking strategy based on photoacids, which stabilized the structures after the external field was removed. This approach has potential applications in the fabrication of advanced materials.

My thesis is arranged as follows. In Chapter 1, I present a brief background of general pattern formation and why I chose to investigate patterns formed in colloidal systems. I also provide a brief review of field-assisted manipulation techniques in order to motivate why I selected magnetic and acoustic field to study colloidal patterns. In chapter 2, I present the theoretical background of magnetic manipulation, which is the main technique used in my research. In this chapter, I will introduce the basic knowledge on magnetic materials and theories behind magnetic manipulation. The underlining thermodynamic mechanisms and theoretical/computational approaches in colloidal pattern formation are also briefly reviewed. In Chapter 3, I focus on using these concepts to study adhesion forces between particle and surfaces. In Chapter 4, I focus on exploring the ground states of colloidal patterns formed from the anti-ferromagnetic interactions of mixtures of particles, as a function of the particle volume fractions. In Chapter 5, I discuss my research on phase transformations of the well-ordered checkerboard phase formed from the equimolar mixture of magnetic and non-magnetic beads in ferrofluid, and I focus mainly on phase transformations in a slowly varying magnetic field. In Chapter 6, I discuss my work on the superimposed magnetic and acoustic field to study patterns formed from monocomponent colloidal suspensions under vertical confinement. Finally, I conclude my thesis in Chapter 7 and discuss future directions and open questions that can be explored in magnetic field directed self-organization in colloidal systems.

DNA nanotechnology is a fascinating field that eschews using DNA as an information storage medium and instead uses it as a nanoscale structural material, taking advantage of the canonical base pairing rules to fold DNA into shapes, patterns, and mechanical devices 10,000 times smaller than a human hair. Over the 40 years of the field's existence, DNA nanotechnology has progressed from building simple wireframe structures to a full-blown nanoengineering ecosystem with the ability to construct logic-gated nanoscale drug delivery vehicles, computing devices, robots, and more. Key to the development of the field has been the growing ability to predict the behavior of DNA nanostructures. However, much is still not understood these devices' self-assembly and dynamic behaviors. The reason for this is that DNA interacts on a short length scale and a long timescale, and many processes occur far from equilibrium, both of which make modeling their behavior challenging. This dissertation presents three projects employing mesoscopic simulations, statistical mechanics, and numerical free energy landscape calculations to provide access to these length and time scales in order to better understand the self-assembly and organization of DNA nanostructures. Specifically, mesoscopic simulations are used to directly simulate the self-assembly of DNA nanostructures and understand the mechanism of their folding; lattice simulations are used to understand the phase behavior of arrays of molecular rotors made from DNA; and geometric calculations and Brownian dynamics simulations are used to computationally derive a bottom-up technique for templating heterogeneous DNA origami species on a single lithographically-defined template.

Limit-periodic (LP) structures exhibit a type of nonperiodic order yet to be found in a natural material. A recent result in tiling theory, however, has shown that LP order can spontaneously emerge in a two-dimensional (2D) lattice model with nearest-and next-nearest-neighbor interactions. In this dissertation, we explore the question of what types of interactions can lead to a LP state and address the issue of whether the formation of a LP structure in experiments is possible. We study emergence of LP order in three-dimensional (3D) tiling models and bring the subject into the physical realm by investigating systems with realistic Hamiltonians and low energy LP states. Finally, we present studies of the vibrational modes of a simple LP ball and spring model whose results indicate that LP materials would exhibit novel physical properties.

A 2D lattice model defined on a triangular lattice with nearest- and next-nearest-neighbor interactions based on the Taylor-Socolar (TS) monotile is known to have a LP ground state. The system reaches that state during a slow quench through an infinite sequence of phase transitions. Surprisingly, even when the strength of the next-nearest-neighbor interactions is zero, in which case there is a large degenerate class of both crystalline and LP ground states, a slow quench yields the LP state. The first study in this dissertation introduces 3D models closely related to the 2D models that exhibit LP phases. The particular 3D models were designed such that next-nearest-neighbor interactions of the TS type are implemented using only nearest-neighbor interactions. For one of the 3D models, we show that the phase transitions are first order, with equilibrium structures that can be more complex than in the 2D case.

In the second study, we investigate systems with physical Hamiltonians based on one of the 2D tiling models with the goal of stimulating attempts to create a LP structure in experiments. We explore physically realizable particle designs while being mindful of particular features that may make the assembly of a LP structure in an experimental system difficult. Through Monte Carlo (MC) simulations, we have found that one particle design in particular is a promising template for a physical particle; a 2D system of identical disks with embedded dipoles is observed to undergo the series of phase transitions which leads to the LP state.

LP structures are well ordered but nonperiodic, and hence have nontrivial vibrational modes. In the third section of this dissertation, we study a ball and spring model with a LP pattern of spring stiffnesses and identify a set of extended modes with arbitrarily low participation ratios, a situation that appears to be unique to LP systems. The balls that oscillate with large amplitude in these modes live on periodic nets with arbitrarily large lattice constants. By studying periodic approximants to the LP structure, we present numerical evidence for the existence of such modes, and we give a heuristic explanation of their structure.

While anisotropic nanoparticles provide unique building blocks for self-assembling useful nanodevices and nanomaterials ranging from plasmonic sensors to chiral metamaterials, controlling their self-assembly process to achieve targeted structure remains challenging. Recently, surface functionalization of nanoparticles with polymer grafts was shown to be a powerful strategy for tuning the orientation-dependent interactions of the nanoparticles. This technique allows modulation of the interaction between nanoparticles as grafted polymers can provide both repulsive interactions arising from their steric hindrance as well as attractive interactions due to their adsorption to the particle surfaces. Utilizing this approach, experiments have successfully assembled nanoparticles into large structures with highly uniform interparticle orientations. However, many challenges remain in fabricating desired nanostructures with the polymer-grafted anisotropic nanoparticles. First, much of the underlying physics governing assembly of such nanoparticles is not well understood and is difficult to discern using experimental techniques due to the nanoscopic nature of the self-assembly process. Second, the relevant parameter space that affects the particle assembly is vast and investigation of such large parameter space is costly in terms of both time and expenses. Third, computationally investigating the behavior of anisotropic nanoparticles is difficult as calculation of their interaction energies is computationally expensive due to the lack of analytical expressions for these energies.In this dissertation, I tackle these challenges in self-assembly of anisotropic nanoparticles through computational modeling, focusing specifically on polymer-grafted nanocubes and DNA-grafted nanorods. For both systems, computational methods and analytical models for efficiently calculating the interaction energies between the anisotropic nanoparticles are first developed. Using such methods as well as advanced Monte Carlo simulations and atomistic calculations, free-energy landscapes describing the assembly of these anisotropic nanoparticles are obtained. Analysis of the free-energy landscapes demonstrates that understanding the interplay between the different interaction components of the systems as well as their dependencies on the relative configurations of the assembled particles is crucial. Specifically for the nanocubes, the competition between the attractive interactions between the inorganic particle cores lead to face-face type of configurations while the repulsive interactions due to the polymer corona induce edge-edge configurations. For the DNA-grafted nanorods, the competition between attractive and repulsive interactions interplay with the chirality of the bridging DNA to induce chiral assembly of the nanorods. Based on these results, material design rules for assembling both the nanocubes and the nanorods into desired configurations are suggested. These results were not only in agreement with many previous experimental studies but also provided the underlying mechanism that explain such assembly behaviors. In summary, the results presented in this dissertation should both aid in fabrication of nanodevices with precisely controlled particle assemblies as well as provide efficient computational methods for future investigation of anisotropic nanoparticles.

Self-assembling polypeptides such as elastin-like polypeptides are already used extensively for drug delivery and other applications. However, the current generation of polypeptide drug delivery vehicles was engineered and selected based on a phenomenological rather than molecular-level understanding of polypeptide self-assembly. In order to rationally design the next generation of self-assembling polypeptide drug delivery vehicles, it is necessary to develop a deeper understanding of the rules governing self-assembly.

This work consists of the synthesis of systematically designed families of recombinant polypeptides and their characterization using nanoscale soft-matter characterization techniques. Block copolypeptides synthesized were based on elastin-like and resilin-like polypeptides, and formed a range of micelles, highly ordered bulk phases, and surface self-assemblies. Polypeptide phase-behavior and self-assembly were characterized by thermal turbidimetry, light scattering, small angle scattering (X-ray and neutron), and cryogenic transmission electron microscopy. This systematic synthesis of polypeptides coupled with detailed characterization allowed for a deeper, molecular-level understanding of the forces governing polypeptide self-assembly, which in turn will inform (and in fact has already informed) the future use of self-assembling polypeptides as drug delivery vehicles.

Inspired by the beauty of various materials with distinct structures and functions in nature, researchers have been dedicating themselves to discover new ways of creating functional artificial materials to fulfill the increasingly various needs in life. Self-assembly, categorized into the ‘bottom-up’ method, is an important approach in building man-made crystals. Elegant and useful structures have been obtain by colloidal self-assembly, including triangular, kagome and square lattices in two- dimensional systems and hexagonal layered structures and color-tunable structures in three-dimensional systems. However, the self-assembly process itself has not yet been fully understood, both thermodynamically and dynamically. Three major challenges in this field are: a) given a set of conditions and parameters of the system, what is the equilibrium assembly structure? b) given a predetermined structure, how should we design particles to self-assemble it? c) how to avoid possible kinetic barriers to assembly complex structures? This dissertation will focus on answering some of the above questions using statistical mechanics approaches and then provide some guidance to colloidal experiments. More specifically, we first study a quasi- two-dimensional, binary colloidal alloy that exhibits liquid—solid and solid—solid phase transitions, focusing on the kinetics of a diffusionless transformation between two crystal phases. Experiments are conducted on a monolayer of magnetic and nonmagnetic spheres suspended in a thin layer of ferrofluid and exposed to a tun- able magnetic field. A theoretical model of hard spheres with point dipoles at their centers is used to guide the choice of experimental parameters and characterize the underlying materials physics. When the applied field is normal to the fluid layer, a checkerboard crystal forms; when the angle between the field and the normal is sufficiently large, a striped crystal assembles. As the field is slowly tilted away from the normal, we find that the transformation pathway between the two phases de- pends strongly on crystal orientation, field strength, and degree of confinement of the monolayer. In some cases, the pathway occurs by smooth magnetostrictive shear, while in others it involves the sudden formation of martensitic plates. Secondly, we examine the densest packing structures and their assembly dynamics for hard spheres of diameter σ within cylinders of diameter D. We extend the identification of close packings up to D = 4.00σ by adapting Torquato—Jiao’s adaptive-shrinking-cell formulation and sequential-linear-programming (SLP) technique. We identify 17 new structures, almost all of them chiral. Beyond D ≈ 2.85σ, most of the structures consist of an outer shell and an inner core that compete for being close packed. In some cases, the shell adopts its own maximum density configuration, and the stack- ing of core spheres within it is quasiperiodic. In other cases, an interplay between the two components is observed, which may result in simple periodic structures. In yet other cases, the very distinction between the core and shell vanishes, resulting in more exotic packing geometries, including some that are three-dimensional extensions of structures obtained from packing hard disks in a circle. Although in such a system phase transitions formally do not exist, marked structural crossovers can nonetheless be observed. Over the range σ ≤ D ≤ 2.82σ, we find in simulations that structural crossovers echo the structural changes to the densest packing sequence. We also observe that the out-of-equilibrium self-assembly depends on the compression rate. Slow compression approximates equilibrium results, while fast compression can skip intermediate structures. Crossovers for which no continuous line-slip exists are found to be dynamically unfavorable, which is the source of this difference. Results from colloidal sedimentation experiments at low diffusion rate are found to be consistent with the results of fast compressions, as long as appropriate boundary conditions are used. The similitude between compression and sedimentation results suggests that the assembly pathway does not here sensitively depend on the nature of the out-of-equilibrium dynamics. We also examine the behavior of different correlation lengths in such quasi-one-dimensional systems via transfer matrix method. Non-monotonicity of the correlation lengths is observed, as has been identified in the assembly simulations. For the quantities that have a Delta distribution function at in- finite pressure, the corresponding correlation lengths vanish as the pressure increases, due to the suppression of fluctuations. For quantities that grow non-monotonically, the decrease of correlation lengths always corresponds to the structural crossovers in the system. As another approach to obtain quasi-one-dimensional assemblies, we examine the focusing of nanoparticles in acoustic standing waves. To perform this study, we build an acoustic focusing chamber containing opposing piezoelectric transducers to rapidly focus particles of different size into highly parallel patterns and visualized this process in real time using dark field microscopy. We select gold as a model material because its high density and low compressibility, making it an ideal candidate for investigating the limits of particle acoustophoresis. To extend our results, we use our theoretical model to estimate, for the first time, the minimum pressure amplitude necessary to concentrate nanoparticles of any composition. Finally, to overcome the limitations of focusing of acoustic standing waves, we develop a simple UV light-based method to controllably induce the aggregation of particles for their rapid concentration below the theoretical size limit at a given pressure amplitude. Lastly, we study the Gardner transition in polydisperse crystals and identify the aging effect by measuring the mean squared displacement as a function of time.

Human Immunodeficiency Virus (HIV) is a vaccine target that has remained elusive for decades. In 2015, 1.1 million people died of HIV-related causes and 2.1 million new infections occurred. Although an effective HIV vaccine has long been a major goal of the World Health Organization (WHO), HIV has been an extraordinarily challenging vaccine target. This challenge is due to several compounding factors including the evolution of the virus within individuals and across geographic regions. This evolution makes it difficult to develop a universal HIV vaccine that will neutralize all strains of the virus. Furthermore, the virus is exceptionally efficient at mutating to evade the immune systems of infected individuals. The outer surface of the virus is densely glycosylated, making it difficult for the immune system to make effective antibodies against such a shielded structure. Consequently, most antibodies generated against the virus are either non-neutralizing or only partially neutralizing and are ineffective at clearing HIV infection. Thus, alternative strategies to direct the immune system towards making neutralizing antibodies are required for an effective HIV vaccine. Attempts at creating an effective HIV vaccine have centered around stimulating high-affinity antibodies that effectively bind genetically diverse strains of the virus. Through protein engineering, variable dosing regimens, and creation of new antigens, HIV researchers have identified the key factors required for the human immune system to raise functional anti-HIV antibodies. Primarily, the immune system must be directed towards the highly conserved and functional antigenic regions of HIV surface proteins to make protective antibodies. To steer the immune system towards specific, neutralizing epitopes from HIV-1, the repertoire of B cells activated by HIV vaccines must be altered from those elicited by natural infection or traditional immunization approaches. Two ways to alter the B cell populations activated upon immunization are explored in this dissertation. Firstly, lowering the activation threshold of activated B cells by arraying antigens on materials allows for a shift of antibody repertoires toward more epitope specificities and potentially broader binding of antibodies to mutated viral strains. Secondly, the immune system can be focused toward specific epitopes using heterologous immunization regimens where antibodies are selected toward a certain specificity, then evolved to bind native antigens, such as those that would be displayed on HIV virions. Though both of these approaches have been explored in other systems, the unique impact of self-assembling peptides in this space has yet to be explored. Peptide biomaterials with fibrillar morphologies such as β-sheet peptides, worm-like micelles, and peptide amphiphiles have been explored towards numerous biomedical applications including scaffolds for tissue repair, immunotherapies for infectious diseases, cancer, or inflammatory conditions, and depots for sustained drug delivery. Although these materials have shown promise in preclinical applications, the immunological effects of their length and ligand valency are poorly understood. Because both of these features can be utilized to tune immune responses, optimizing them in the context of HIV immunization has the potential to improve the magnitude and quality of antibodies elicited by nanofiber immunogens. To examine the impact of antigen valency and nanofiber size in HIV immunization, structural tools to control these features were developed. The ability to control nanofiber length was achieved in this body of work be engineering a set of peptides we have designed and characterized to stabilize self-assembling interfaces. This newfound control over nanofiber length allows size-based targeting of materials which was not previously possible. In addition to studying size-dependent immunogenicity, the role of glycans in immune responses to nanoscale are a newfound area of interest amongst the biomaterials community. Though some glycans can be readily conjugated to peptide and polymer assemblies, many carbohydrates, such as sialic acids are extremely difficult to functionalize chemically. To overcome this, glycomimetic peptides which resemble diverse glycans have been designed, but are implemented in few therapeutic contexts. This system capitalizes upon the synthetic advantages of utilizing glycomimetic peptides in peptide-based immunogens and represents a broadly applicable strategy to impart lectin-binding properties to peptide materials. Although it is appreciated that multivalency and nanomaterial shape and size can influence immunogenicity, these aspects have yet to be fully exploited in the context of a specific disease. To meet these challenges, we have designed a self-assembling peptide system with control over the lengthwise assembly of nanofibers and have studied the effect of antigen valency on immune responses to these materials in the context of HIV. As immunogens, peptide nanofibers have a unique ability to activate low-affinity B cells, such as those which react to autologous targets, will likely be advantageous for HIV vaccination, where low-affinity B cells are precursors to the induction of broadly neutralizing antibody (bnAb) responses. To determine the utility of peptide nanofibers as platforms for HIV vaccination, We first constructed nanofibers that are covalently linked to the HIV envelope antigen gp120 which demonstrated their ability to raise antibodies with broad binding profiles. As an alternative approach for raising immune responses against HIV antigens, we have explored the use of peptide nanofibers displaying short, linear HIV epitopes as priming immunogens. This approach capitalizes on the ability of nanofibers to generate antibodies against short epitopes and tailors the accumulation of nanofibers in lymph nodes to prime epitope-focused antibodies against HIV virions. Taken together, the studies described here utilize supramolecular control over antigen valency and immunogen size to generate antibody responses to HIV with high affinity and high binding breadth. The supramolecular tools described here provide morphological controls for spontaneously assembling materials which have not yet been utilized for these types of platforms. This tight control over morphology allows us to ask questions with levels of immunological precision that are not common in biomaterials literature.

Elastin-like polypeptides (ELPs) are thermally responsive polymers composed of the pentapeptide repeat Valine-Proline-Glycine-X-Glycine where X is any amino acid except proline. ELP diblocks have been engineered by creating two ELP blocks with hydrophilic and hydrophobic guest residues. The hydrophobic block desolvates at a lower temperature and forms the core of a micelle while the still hydrated hydrophilic block forms the corona. ELP micelles are promising drug delivery vehicles for cancer therapeutics. ELP diblocks offer a unique method to display targeting proteins multivalently on micelles to improve tumor cell uptake. As ELPs are genetically encoded, proteins can be seamlessly fused at the genetic level to the ELP diblock. The protein ELP diblock fusions can be synthesized as one polypeptide chain that is of precise molecular weight and highly monodisperse, and no post-synthesis modification is necessary. Self-assembly behavior of ELP diblocks is known to tolerate fusion to small peptides (< 10 amino acids) but their self-assembly behavior has not be examined when fused to proteins that are 100-200 amino acids. Here, we hypothesize that molecular weight of the protein and the surface properties of the protein will be factors in determining its effect on ELP diblock self-assembly. In addition, the ELP block lengths and composition are hypothesized to be factors in the self-assembly behavior of protein ELP diblock fusions. This hypothesis is tested by fusing four proteins with different properties to various ELP diblocks and characterizing their self-assembly behavior. The proteins were found to dominate the self-assembly behavior. Proteins that disrupted self-assembly did so for all ELP diblock lengths and compositions. Protein that did not disrupt self-assembly behavior affected the thermal behavior of the hydrophilic block. Hydrophilic proteins increased the micelle-to-aggregate transition temperature while hydrophobic proteins decreased it. We also sought to understand the self-assembly of ELP diblocks on a theoretical basis. A previously developed model for the self-assembly of synthetic polymers was applied to our polypeptide system. Two parameters, solvent quality of the corona and surface tension of the hydrophobic block, were experimentally measured and used to fit the model. Predictions of micelle radius and aggregation numbers were in good agreement with experimental data. However, the corona was found to be unstretched compared to its Gaussian size by this model. Therefore, a new model was developed describing what is termed as weak micelles in which the corona is not stretched but rather close to Gaussian size. The weak micelle model prediction were also in good agreement with experimental data suggesting that ELP micelles are in the crossover regime between the previous model and the new model.

The complexity of protein-protein interactions enables proteins to self-assemble into a rich array of structures, such as virus capsids, amyloid fibers, amorphous aggregates, and protein crystals. While some of these assemblies form under biological conditions, protein crystals, which are crucial for obtaining protein structures from diffraction methods, do not typically form readily. Crystallizing proteins thus requires significant trial and error, limiting the number of structures that can be obtained and studied. Understanding how proteins interact with one another and with their environment would allow us to elucidate the physicochemical processes that lead to crystal formation and provide insight into other self-assembly phenomena. This thesis explores this problem from a soft matter theory and simulation perspective.

We first attempt to reconstruct the water structure inside a protein crystal using all-atom molecular dynamics simulations with the dual goal of benchmarking empirical water models and increasing the information extracted from X-ray diffraction data. We find that although water models recapitulate the radial distribution of water around protein atoms, they fall short of reproducing its orientational distribution. Nevertheless, high-intensity peaks in water density are sufficiently well captured to detect the protonation states of certain solvent-exposed residues.

We next study a human gamma D-crystallin mutant, the crystals of which have inverted solubility. We parameterize a patchy particle and show that the temperature-dependence of the patch that contains the solubility inverting mutation reproduces the experimental phase diagram. We also consider the hypothesis that the solubility is inverted because of increased surface hydrophobicity, and show that even though this scenario is thermodynamically plausible, microscopic evidence for it is lacking, partly because our understanding of water as a biomolecular solvent is limited.

Finally, we develop computational methods to understand the self-assembly of a two-dimensional protein crystal and show that specialized Monte Carlo moves are necessary for proper sampling.