Virus-Shaped Mesoporous Silica Nanostars to Improve the Transport of Drugs across the Blood-Brain Barrier.

Conditions affecting the brain are the second leading cause of death globally. One of the main challenges for drugs targeting brain diseases is passing the blood-brain barrier (BBB). Here, the effectiveness of mesoporous silica nanostars (MSiNSs) with two different spike lengths to cross an in vitro BBB multicellular model was evaluated and compared to spherical nanoparticles (MSiNP). A modified sol-gel single-micelle epitaxial growth was used to produce MSiNS, which showed no cytotoxicity or immunogenicity at concentrations of up to 1 µg mL-1 in peripheral blood mononuclear and neuronal cells. The nanostar MSiNS effectively penetrated the BBB model after 24 h, and MSiNS-1 with a shorter spike length (9 ± 2 nm) crossed the in vitro BBB model more rapidly than the MSiNS-2 with longer spikes (18 ± 4 nm) or spherical MSiNP at 96 h, which accumulated in the apical and basolateral sides, respectively. Molecular dynamic simulations illustrated an increase in configurational flexibility of the lipid bilayer during contact with the MSiNS, resulting in wrapping, whereas the MSiNP suppressed membrane fluctuations. This work advances an effective brain drug delivery system based on virus-like shaped MSiNS for the treatment of different brain diseases and a mechanism for their interaction with lipid bilayers.

Boundary Lubrication Performance of Polyelectrolyte-Surfactant Complexes on Biomimetic Surfaces.

Aqueous mixtures of oppositely charged polyelectrolytes and surfactants are useful in many industrial applications, such as shampoos and hair conditioners. In this work, we investigate the friction between biomimetic hair surfaces in the presence of adsorbed complexes formed from cationic polyelectrolytes and anionic surfactants in an aqueous solution. We apply nonequilibrium molecular dynamics (NEMD) simulations using the coarse-grained MARTINI model. We first developed new MARTINI parameters for cationic guar gum (CGG), a functionalized, plant-derived polysaccharide. The complexation of CGG and the anionic surfactant sodium dodecyl sulfate (SDS) on virgin and chemically damaged biomimetic hair surfaces was studied using a sequential adsorption approach. We then carried out squeeze-out and sliding NEMD simulations to assess the boundary lubrication performance of the CGG-SDS complex compressed between two hair surfaces. At low pressure, we observe a synergistic friction behavior for the CGG-SDS complex, which gives lower shear stress than either pure CGG or SDS. Here, friction is dominated by viscous dissipation in an interfacial layer comprising SDS and water. At higher pressures, which are probably beyond those usually experienced during hair manipulation, SDS and water are squeezed out, and friction increases due to interdigitation. The outcomes of this work are expected to be beneficial to fine-tune and screen sustainable hair care formulations to provide low friction and therefore a smooth feel and reduced entanglement.

Valency of Ligand-Receptor Binding from Pair Potentials.

Coarse grained molecular dynamics simulations have been crucial for investigating the dynamics of nanoparticle uptake by cell membranes via ligand-receptor interactions. These models have enabled researchers to evaluate the effects of nanoparticle size, shape, and ligand distribution on cellular uptake. However, when pair potentials are used to represent ligand-receptor interactions, the number of receptors interacting with one ligand, valency, may vary. We demonstrate that the curvature of a nanoparticle, strength of ligand-receptor interactions, and ligand or receptor concentration change the valency, ranging from 3.4 to 5.1 in this study. Such a change in valency can create inaccurate comparisons between nanoparticles or even result in the uptake of smaller nanoparticles than would be expected. To rectify this inconsistency, we propose the adoption of a model based on bond formation and use it to determine the extent to which previous studies may have been affected. This work recommends avoiding pair potentials for modeling ligand-receptor interactions to ensure methodological consistency in nanoparticle studies.

Effects of surfactant adsorption on the wettability and friction of biomimetic surfaces.

The properties of solid-liquid interfaces can be markedly altered by surfactant adsorption. Here, we use molecular dynamics (MD) simulations to study the adsorption of ionic surfactants at the interface between water and heterogeneous solid surfaces with randomly arranged hydrophilic and hydrophobic regions, which mimic the surface properties of human hair. We use the coarse-grained MARTINI model to describe both the hair surfaces and surfactant solutions. We consider negatively-charged virgin and bleached hair surface models with different grafting densities of neutral octadecyl and anionic sulfonate groups. The adsorption of cationic cetrimonium bromide (CTAB) and anionic sodium dodecyl sulfate (SDS) surfactants from water are studied above the critical micelle concentration. The simulated adsorption isotherms suggest that cationic surfactants adsorb to the surfaces via a two-stage process, initially forming monolayers and then bilayers at high concentrations, which is consistent with previous experiments. Anionic surfactants weakly adsorb via hydrophobic interactions, forming only monolayers on both virgin and medium bleached hair surfaces. We also conduct non-equilibrium molecular dynamics simulations, which show that applying cationic surfactant solutions to bleached hair successfully restores the low friction seen with virgin hair. Friction is controlled by the combined surface coverage of the grafted lipids and the adsorbed CTAB molecules. Treated surfaces containing monolayers and bilayers both show similar friction, since the latter are easily removed by compression and shear. Further wetting MD simulations show that bleached hair treated with CTAB increases the hydrophobicity to similar levels seen for virgin hair. Treated surfaces containing CTAB monolayers with the tailgroups pointing predominantly away from the surface are more hydrophobic than bilayers due to the electrostatic interactions between water molecules and the exposed cationic headgroups.

Dual-Action Heteromultivalent Glycopolymers Stringently Block and Arrest Influenza A Virus Infection In Vitro and Ex Vivo.

Here, we demonstrate the concerted inhibition of different influenza A virus (IAV) strains using a low-molecular-weight dual-action linear polymer. The 6'-sialyllactose and zanamivir conjugates of linear polyglycerol are optimized for simultaneous targeting of hemagglutinin and neuraminidase on the IAV surface. Independent of IAV subtypes, hemagglutination inhibition data suggest better adsorption of the heteromultivalent polymer than homomultivalent analogs onto the virus surface. Cryo-TEM images imply heteromultivalent compound-mediated virus aggregation. The optimized polymeric nanomaterial inhibits >99.9% propagation of various IAV strains 24 h postinfection in vitro at low nM concentrations and is up to 10000× more effective than the commercial zanamivir drug. In a human lung ex vivo multicyclic infection setup, the heteromultivalent polymer outperforms the commercial drug zanamivir and homomultivalent analogs or their physical mixtures. This study authenticates the translational potential of the dual-action targeting approach using small polymers for broad and high antiviral efficacy.

Nanoscale friction of biomimetic hair surfaces.

We investigate the nanoscale friction between biomimetic hair surfaces using chemical colloidal probe atomic force microscopy experiments and nonequilibrium molecular dynamics simulations. In the experiments, friction is measured between water-lubricated silica surfaces functionalised with monolayers formed from either octadecyl or sulfonate groups, which are representative of the surfaces of virgin and ultimately bleached hair, respectively. In the simulations, friction is monitored between coarse-grained model hair surfaces with different levels of chemical damage, where a specified amount of grafted octadecyl groups are randomly replaced with sulfonate groups. The sliding velocity dependence of friction in the simulations can be described using an extended stress-augmented thermally activation model. As the damage level increases in the simulations, the friction coefficient generally increases, but its sliding velocity-dependence decreases. At low sliding velocities, which are closer to those encountered experimentally and physiologically, we observe a monotonic increase of the friction coefficient with damage ratio, which is consistent with our new experiments using biomimetic surfaces and previous ones using real hair. This observation demonstrates that modified surface chemistry, rather than roughness changes or subsurface damage, control the increase in nanoscale friction of bleached or chemically damaged hair. We expect the methods and biomimetic surfaces proposed here to be useful to screen the tribological performance of hair care formulations both experimentally and computationally.

Amplified EQCM-D detection of extracellular vesicles using 2D gold nanostructured arrays fabricated by block copolymer self-assembly.

Extracellular vesicles (EVs) are routinely released from nearly all cell types as transport vehicles and for cell communication. Crucially, they contain biomolecular content for the identification of health and disease states that can be detected from readily accessible physiological fluids, including urine, plasma, or saliva. Despite their clinical utility within noninvasive diagnostic platforms such as liquid biopsies, the currently available portfolio of analytical approaches are challenged by EV heterogeneity in size and composition, as well as the complexity of native biofluids. Quartz crystal microbalance with dissipation monitoring (QCM-D) has recently emerged as a powerful alternative for the phenotypic detection of EVs, offering multiple modes of analyte discrimination by frequency and dissipation. While providing rich data for sensor development, further progress is required to reduce detection limits and fully exploit the technique's potential within biosensing. Herein, we investigate the impact of nanostructuring the sensor electrode surface for enhancing its detection capabilities. We employ self-assembly of the block copolymer polystyrene-block-poly(4-vinylpyridine) to create well defined 2D gold islands via selective impregnation of the pyridine domain with gold precursors and subsequent removal of the template. When matched to the EV length scale, we find a 4-fold improvement in sensitivity despite a 4-fold reduction in area for analyte and ligand anchoring in comparison to a flat sensor surface. Creation of tailored and confined sensing regions interspersed by non-binding silica provides optimal spatial orientation for EV capture with reduced steric effects and negative cooperativity of grafted antibodies, offering a promising route for facilitated binding and enhanced performance of sensor platforms.

The role of surface topography in the self-assembly of polymeric surfactants.

We propose a classical density functional theory model to study the self-assembly of polymeric surfactants on curved surfaces. We use this model to investigate the thermodynamics of phase separation of a binary mixture of size asymmetric miscible surfactants on cylindrical and spherical surfaces, and observe that phase separation driven by size alone is thermodynamically unfavorable on both cylindrical and spherical surfaces. We use the theory, supplemented by dissipative particle dynamics (DPD) simulations, to predict pattern formation on a non-uniform surface with regions of positive and negative curvature. Our results suggest potential ways to couple surface topography and polymeric surfactants to design surfaces coated with non-uniform patterns.

Modeling Au Nanostar Geometry in Bulk Solutions.

The findings within make it possible to reference gold nanostars based on their geometric properties, similar to how a radius describes a nanosphere, rather than just the LSPR of the structure-the current practice. The average tip approximation presented reduces the complexity of nanostars in discrete dipole approximation simulations. By matching the projected area and LSPR of the modeled nanostars to synthesized nanostars, the volume, surface area, and number of tips can be approximated without a lengthy characterization process. Knowing the nanoparticle geometry can determine drug carrier capacity, an approximate number of hot spots for EM imaging, and how the particle will interact with cells. The geometric data obtained will drive the biological application and increase the usability of this particle class.

Bimodal brush-functionalized nanoparticles selective to receptor surface density.

Nanoparticles or drug carriers which can selectively bind to cells expressing receptors above a certain threshold surface density are very promising for targeting cells overexpressing specific receptors under pathological conditions. Simulations and theoretical studies have suggested that such selectivity can be enhanced by functionalizing nanoparticles with a bimodal polymer monolayer (BM) containing shorter ligated chains and longer inert protective chains. However, a systematic study of the effect of these parameters under tightly controlled conditions is still missing. Here, we develop well-defined and highly specific platforms mimicking particle-cell interface using surface chemistry to provide a experimental proof of such selectivity. Using surface plasmon resonance and atomic force microscopy, we report the selective adsorption of BM-functionalized nanoparticles, and especially, a significant enhanced selective behavior by using a BM with longer protective chains. Furthermore, a model is also developed to describe the repulsive contribution of the protective brush to nanoparticle adsorption. This model is combined with super-selectivity theory to support experimental findings and shows that the observed selectivity is due to the steric energy barrier which requires a high number of ligand-receptor bonds to allow nanoparticle adsorption. Finally, the results show how the relative length and molar ratio of two chains can be tuned to target a threshold surface density of receptors and thus lay the foundation for the rational design of BM-functionalized nanoparticles for selective targeting.

Polymer brushes for friction control: Contributions of molecular simulations.

When polymer chains are grafted to solid surfaces at sufficiently high density, they form brushes that can modify the surface properties. In particular, polymer brushes are increasingly being used to reduce friction in water-lubricated systems close to the very low levels found in natural systems, such as synovial joints. New types of polymer brush are continually being developed to improve with lower friction and adhesion, as well as higher load-bearing capacities. To complement experimental studies, molecular simulations are increasingly being used to help to understand how polymer brushes reduce friction. In this paper, we review how molecular simulations of polymer brush friction have progressed from very simple coarse-grained models toward more detailed models that can capture the effects of brush topology and chemistry as well as electrostatic interactions for polyelectrolyte brushes. We pay particular attention to studies that have attempted to match experimental friction data of polymer brush bilayers to results obtained using molecular simulations. We also critically look at the remaining challenges and key limitations to overcome and propose future modifications that could potentially improve agreement with experimental studies, thus enabling molecular simulations to be used predictively to modify the brush structure for optimal friction reduction.

Binding of Proteins to Copolymers of Varying Charges and Hydrophobicity: A Molecular Mechanism and Computational Strategies.

Because of their ability to selectively bind to a target protein, copolymer nanoparticles (NPs) containing a selected combination of hydrophobic and charged groups have been frequently reported as potent antibody-like analogues. However, due to the intrinsic disorder of the copolymer NP in terms of its random monomer sequence and the cross-linked copolymer matrix, the copolymer NP is indeed strikingly different from a well-folded protein antibody and the complexation between the copolymer NP and a target protein is likely not due to a lock-key type of interaction but possibly due to a novel and unexplored molecular mechanism. Here, we study a key biomarker protein, vimentin, interacting with a set of random copolymer chains using implicit-water explicit-ion coarse-grained (CG) molecular dynamics (MD) simulations along with biolayer interferometry (BLI) analysis. Due to the charge and hydrophobicity anisotropy on the vimentin dimer (VD) surface, a set of bound copolymers are found inhomogenously adsorbed on the VD, with energetic heterogeneity for different binding sites and cooperative effect in the adsorption. Increasing the charge or hydrophobicity of the copolymer may have different consequences on the adsorption. In this study, we found that with more copolymer charges, the protein coverage increases for copolymers of low hydrophobicity and decreases of high hydrophobicity, which is explained by the distribution and size of various functional patches on the VD in loading those copolymers. Employing a coverage-dependent Langmuir model, we propose a simulation protocol to address the full profile of the copolymer binding free energy through the fit to the simulated binding isotherm. The obtained results correlate well with those from the BLI experiment, indicating the significance of this method for the rational design of the copolymer NP with engineered protein binding affinity.

Coarse-grained molecular models of the surface of hair.

We present a coarse-grained molecular model of the surface of human hair, which consists of a supported lipid monolayer, in the MARTINI framework. Using coarse-grained molecular dynamics (MD) simulations, we identify a lipid grafting distance that yields a monolayer thickness consistent with both atomistic MD simulations and experimental measurements of the hair surface. Coarse-grained models for fully-functionalised, partially damaged, and fully damaged hair surfaces are created by randomly replacing neutral thioesters with anionic sulfonate groups. This mimics the progressive removal of fatty acids from the hair surface by bleaching and leads to chemically heterogeneous surfaces. Using molecular dynamics (MD) simulations, we study the island structures formed by the lipid monolayers at different degrees of damage in vacuum and in the presence of polar (water) and non-polar (n-hexadecane) solvents. We also use MD simulations to compare the wetting behaviour of water and n-hexadecane droplets on the model surfaces through contact angle measurements, which are compared to experiments using virgin and bleached hair. The model surfaces capture the experimentally-observed transition of the hair surface from hydrophobic (and oleophilic) to hydrophilic (and oleophobic) as the level of bleaching damage increases. By selecting surfaces with specific damage ratios, we obtain contact angles from the MD simulations that are in good agreement with experiments for both solvents on virgin and bleached human hairs. To negate the possible effects of microscale curvature and roughness of real hairs on wetting, we also conduct additional experiments using biomimetic surfaces that are co-functionalised with fatty acids and sulfonate groups. In both the MD simulations and experiments, the cosine of the water contact angle increases linearly with the sulfonate group surface coverage with a similar slope. We expect that the proposed systems will be useful for future molecular dynamics simulations of the adsorption and tribological behaviour of hair, as well as other chemically heterogeneous surfaces.

Direct visualization of superselective colloid-surface binding mediated by multivalent interactions.

Reliably distinguishing between cells based on minute differences in receptor density is crucial for cell-cell or virus-cell recognition, the initiation of signal transduction, and selective targeting in directed drug delivery. Such sharp differentiation between different surfaces based on their receptor density can only be achieved by multivalent interactions. Several theoretical and experimental works have contributed to our understanding of this "superselectivity." However, a versatile, controlled experimental model system that allows quantitative measurements on the ligand-receptor level is still missing. Here, we present a multivalent model system based on colloidal particles equipped with surface-mobile DNA linkers that can superselectively target a surface functionalized with the complementary mobile DNA-linkers. Using a combined approach of light microscopy and Foerster resonance energy transfer (FRET), we can directly observe the binding and recruitment of the ligand-receptor pairs in the contact area. We find a nonlinear transition in colloid-surface binding probability with increasing ligand or receptor concentration. In addition, we observe an increased sensitivity with weaker ligand-receptor interactions, and we confirm that the timescale of binding reversibility of individual linkers has a strong influence on superselectivity. These unprecedented insights on the ligand-receptor level provide dynamic information into the multivalent interaction between two fluidic membranes mediated by both mobile receptors and ligands and will enable future work on the role of spatial-temporal ligand-receptor dynamics on colloid-surface binding.

Unraveling the Role of Architecture in Polymer-Based Glues for Hydrogels.

We investigate polymers of different architectures as potential candidates for the development of glues for hydrogels. Using a combination of coarse-grained modeling and molecular dynamics simulations, we systematically characterize the link between experimentally tunable parameters and adhesion energy. We find that, for a broad set of parameters, adhesion is controlled almost exclusively by the total amount of glue at the interface and by the glue-hydrogel affinity. Instead, it is largely independent of changes in polymer architecture and size, a conclusion that shines new light on previously observed experimental trends. Additionally, we show that the scaling behavior of the properties we measure can be explained by modeling the glue as an ensemble of ideal, noninteracting, and linear polymer segments. We expect that the fundamental insights herein provided will aid the design of new polymer-based adhesives for hydrogels.

Combinatorial entropy behaviour leads to range selective binding in ligand-receptor interactions.

From viruses to nanoparticles, constructs functionalized with multiple ligands display peculiar binding properties that only arise from multivalent effects. Using statistical mechanical modelling, we describe here how multivalency can be exploited to achieve what we dub range selectivity, that is, binding only to targets bearing a number of receptors within a specified range. We use our model to characterise the region in parameter space where one can expect range selective targeting to occur, and provide experimental support for this phenomenon. Overall, range selectivity represents a potential path to increase the targeting selectivity of multivalent constructs.

Computational design of probes to detect bacterial genomes by multivalent binding.

Rapid methods for diagnosis of bacterial infections are urgently needed to reduce inappropriate use of antibiotics, which contributes to antimicrobial resistance. In many rapid diagnostic methods, DNA oligonucleotide probes, attached to a surface, bind to specific nucleotide sequences in the DNA of a target pathogen. Typically, each probe binds to a single target sequence; i.e., target-probe binding is monovalent. Here we show using computer simulations that the detection sensitivity and specificity can be improved by designing probes that bind multivalently to the entire length of the pathogen genomic DNA, such that a given probe binds to multiple sites along the target DNA. Our results suggest that multivalent targeting of long pieces of genomic DNA can allow highly sensitive and selective binding of the target DNA, even if competing DNA in the sample also contains binding sites for the same probe sequences. Our results are robust to mild fragmentation of the bacterial genome. Our conclusions may also be relevant for DNA detection in other fields, such as disease diagnostics more broadly, environmental management, and food safety.

On the design of precision nanomedicines.

Tight control on the selectivity of nanoparticles' interaction with biological systems is paramount for the development of targeted therapies. However, the large number of tunable parameters makes it difficult to identify optimal design "sweet spots" without guiding principles. Here, we combine superselectivity theory with soft matter physics into a unified theoretical framework and we prove its validity using blood brain barrier cells as target. We apply our approach to polymersomes functionalized with targeting ligands to identify the most selective combination of parameters in terms of particle size, brush length and density, as well as tether length, affinity, and ligand number. We show that the combination of multivalent interactions into multiplexed systems enable interaction as a function of the cell phenotype, that is, which receptors are expressed. We thus propose the design of a "bar-coding" targeting approach that can be tailor-made to unique cell populations enabling personalized therapies.

Precise Generation of Selective Surface-Confined Glycoprotein Recognition Sites.

Since glycoproteins have become increasingly recognized as key players in a wide variety of disease processes, there is an increasing need for advanced affinity materials for highly selective glycoprotein binding. Herein, for the first time, a surface-initiated controlled radical polymerization is integrated with supramolecular templating and molecular imprinting to yield highly reproducible synthetic recognition sites on surfaces with dissociation constants (K D) in the low micromolar range for target glycoproteins and minimal binding to nontarget glycoproteins. Importantly, it is shown that the synthetic strategy has a remarkable ability to distinguish the glycosylated and nonglycosylated forms of the same glycoprotein, with a >5-fold difference in binding affinity. The precise control over the polymer film thickness and positioning of multiple carbohydrate receptors plays a crucial role in achieving an enhanced affinity and selectivity. The generated functional materials of unprecedented glycoprotein recognition performance open up a wealth of opportunities in the biotechnological and biomedical fields.

Nonequilibrium Uptake Kinetics of Molecular Cargo into Hollow Hydrogels Tuned by Electrosteric Interactions.

Hollow hydrogels represent excellent nano- and microcarriers due to their ability to encapsulate and release large amounts of cargo molecules (cosolutes) such as reactants, drugs, and proteins. In this work, we use a combination of a phenomenological effective cosolute-hydrogel interaction potential and dynamic density functional theory to investigate the full nonequilibrium encapsulation kinetics of charged and dipolar cosolutes by an isolated charged hollow hydrogel immersed in a 1:1 electrolyte aqueous solution. Our analysis covers a broad spectrum of cosolute valences ( zc) and electric dipole moments (µc), as well as hydrogel swelling states and hydrogel charge densities. Our calculations show that, close to the collapsed state, the polar cosolutes are predominantly precluded and the encapsulation process is strongly hindered by the excluded-volume interaction exerted by the polymer network. Different equilibrium and kinetic sorption regimes (interface versus interior) are found depending on the value and sign of zc and the value of µc. For cosolutes of the same sign of charge as the gel, the superposition of steric and electrostatic repulsion leads to an "interaction-controlled" encapsulation process, in which the characteristic time to fill the empty core of the hydrogel grows exponentially with zc. On the other hand, for cosolutes oppositely charged to the gel, we find a "diffusion-controlled" kinetic regime, where cosolutes tend to rapidly absorb into the hydrogel membrane and the encapsulation rate depends only on the cosolute diffusion time across the membrane. Finally, we find that increasing µc promotes the appearance of metastable and stable surface adsorption states. For large enough µc, the kinetics enters an "adsorption-hindered diffusion", where the enhanced surface adsorption imposes a barrier and slows down the uptake. Our study represents the first attempt to systematically describe how the swelling state of the hydrogel and other leading physical interaction parameters determine the encapsulation kinetics and the final equilibrium distribution of polar molecular cargo.