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.

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.

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.

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.

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.

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.

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.

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.

Interaction of Proteins with Polyelectrolytes: Comparison of Theory to Experiment.

We discuss recent investigations of the interaction of polyelectrolytes with proteins. In particular, we review our recent studies on the interaction of simple proteins such as human serum albumin (HSA) and lysozyme with linear polyelectrolytes, charged dendrimers, charged networks, and polyelectrolyte brushes. In all cases discussed here, we combined experimental work with molecular dynamics (MD) simulations and mean-field theories. In particular, isothermal titration calorimetry (ITC) has been employed to obtain the respective binding constants Kb and the Gibbs free energy of binding. MD simulations with explicit counterions but implicit water demonstrate that counterion release is the main driving force for the binding of proteins to strongly charged polyelectrolytes: patches of positive charges located on the surface of the protein become multivalent counterions of the polyelectrolyte, thereby releasing a number of counterions condensed on the polyelectrolyte. The binding Gibbs free energy due to counterion release is predicted to scale with the logarithm of the salt concentration in the system, which is verified by both simulations and experiment. In several cases, namely, for the interaction of proteins with linear polyelectrolytes and highly charged hydrophilic dendrimers, the binding constant could be calculated from simulations to very good approximation. This finding demonstrated that in these cases explicit hydration effects do not contribute to the Gibbs free energy of binding. The Gibbs free energy can also be used to predict the kinetics of protein uptake by microgels for a given system by applying dynamic density functional theory. The entire discussion demonstrates that the direct comparison of theory with experiments can lead to a full understanding of the interaction of proteins with charged polymers. Possible implications for applications, such as drug design, are discussed.

Nanoparticle Organization Controls Their Potency as Universal Glues for Gels.

Nanoparticles have been recently shown to act as universal glues for both synthetic and biological gels, providing a tunable, cheap, and general solution to the centuries-old problem of sticking soft materials together. The design of new adhesive solutions based on this platform, however, requires an understanding of how nanoparticles' design parameters concur to determine the final adhesion strength. Here, we use coarse-grained modeling and molecular dynamics simulations to investigate such links. Our main aim is to show that, at experimentally relevant concentrations, adhesion is strongly influenced by the way nanoparticles organize at the interface, resulting in non-monotonous reinforcement behavior. Our findings represent an important step toward rationalizing this new class of nanoparticle-based adhesives.

Exploiting Receptor Competition to Enhance Nanoparticle Binding Selectivity.

Nanoparticles functionalized with multiple ligands can be programed to bind biological targets depending on the receptors they express, providing a general mechanism exploited in various technologies, from selective drug delivery to biosensing. For binding to be highly selective, ligands should exclusively interact with specific targeted receptors, because the formation of bonds with other, untargeted ones would lead to nonspecific binding and potentially harmful behavior. This poses a particular problem for multivalent nanoparticles, because even very weak bonds can collectively lead to strong binding. A statistical mechanical model is used here to describe how competition between different receptors together with multivalent effects can be harnessed to design ligand-functionalized nanoparticles insensitive to the presence of untargeted receptors, preventing nonspecific binding.

Theory and simulation of DNA-coated colloids: a guide for rational design.

By exploiting the exquisite selectivity of DNA hybridization, DNA-coated colloids (DNACCs) can be made to self-assemble in a wide variety of structures. The beauty of this system stems largely from its exceptional versatility and from the fact that a proper choice of the grafted DNA sequences yields fine control over the colloidal interactions. Theory and simulations have an important role to play in the optimal design of self assembling DNACCs. At present, the powerful model-based design tools are not widely used, because the theoretical literature is fragmented and the connection between different theories is often not evident. In this Perspective, we aim to discuss the similarities and differences between the different models that have been described in the literature, their underlying assumptions, their strengths and their weaknesses. Using the tools described in the present Review, it should be possible to move towards a more rational design of novel self-assembling structures of DNACCs and, more generally, of systems where ligand-receptor are used to control interactions.

Reaction rate of a composite core-shell nanoreactor with multiple nanocatalysts.

We present a detailed theory for the total reaction rate constant of a composite core-shell nanoreactor, consisting of a central solid core surrounded by a hydrogel layer of variable thickness, where a given number of small catalytic nanoparticles are embedded at prescribed positions and are endowed with a prescribed surface reaction rate constant. Besides the precise geometry of the assembly, our theory accounts explicitly for the diffusion coefficients of the reactants in the hydrogel and in the bulk as well as for their transfer free energy jump upon entering the hydrogel shell. Moreover, we work out an approximate analytical formula for the overall rate constant, which is valid in the physically relevant range of geometrical and chemical parameters. We discuss in depth how the diffusion-controlled part of the rate depends on the essential variables, including the size of the central core. In particular, we derive some simple rules for estimating the number of nanocatalysts per nanoreactor for an efficient catalytic performance in the case of small to intermediate core sizes. Our theoretical treatment promises to provide a very useful and flexible tool for the design of superior performing nanoreactor geometries with optimized nanoparticle load.

Communication: Resonance reaction in diffusion-influenced bimolecular reactions.

We investigate the influence of a stochastically fluctuating step-barrier potential on bimolecular reaction rates by exact analytical theory and stochastic simulations. We demonstrate that the system exhibits a new "resonant reaction" behavior with rate enhancement if an appropriately defined fluctuation decay length is of the order of the system size. Importantly, we find that in the proximity of resonance, the standard reciprocal additivity law for diffusion and surface reaction rates is violated due to the dynamical coupling of multiple kinetic processes. Together, these findings may have important repercussions on the correct interpretation of various kinetic reaction problems in complex systems, as, e.g., in biomolecular association or catalysis.

Communication: Simple approach for calculating the binding free energy of a multivalent particle.

We present a simple yet accurate numerical approach to compute the free energy of binding of multivalent objects on a receptor-coated surface. The method correctly accounts for the fact that one ligand can bind to at most one receptor. The numerical approach is based on a saddle-point approximation to the computation of a complex residue. We compare our theory with the powerful Valence-Limited Interaction Theory (VLIT) [P. Varilly et al., J. Chem. Phys. 137, 094108 (2012); S. Angioletti-Uberti et al., ibid. 138, 021102 (2013)] and find excellent agreement in the regime where that theory is expected to work. However, the present approach even works for low receptor/ligand densities, where VLIT breaks down.

Epitope mapping of monoclonal antibody HPT-101: a study combining dynamic force spectroscopy, ELISA and molecular dynamics simulations.

By combining enzyme-linked immunosorbent assay (ELISA) and optical tweezers-assisted dynamic force spectroscopy (DFS), we identify for the first time the binding epitope of the phosphorylation-specific monoclonal antibody (mAb) HPT-101 to the Alzheimer's disease relevant peptide tau[pThr231/pSer235] on the level of single amino acids. In particular, seven tau isoforms are synthesized by replacing binding relevant amino acids by a neutral alanine (alanine scanning). From the binding between mAb HPT-101 and the alanine-scan derivatives, we extract specific binding parameters such as bond lifetime τ0, binding length x(ts), free energy of activation ΔG (DFS) and affinity constant K(a) (ELISA, DFS). Based on these quantities, we propose criteria to identify essential, secondary and non-essential amino acids, being representative of the antibody binding epitope. The obtained results are found to be in full accord for both experimental techniques. In order to elucidate the microscopic origin of the change in binding parameters, we perform molecular dynamics (MD) simulations of the free epitope in solution for both its parent and modified form. By taking the end-to-end distance d(E-E) and the distance between the α-carbons d(C-C) of the phosphorylated residues as gauging parameters, we measure how the structure of the epitope depends on the type of substitution. In particular, whereas d(C-C) is sometimes conserved between the parent and modified form, d(E-E) strongly changes depending on the type of substitution, correlating well with the experimental data. These results are highly significant, offering a detailed microscopic picture of molecular recognition.

Mobile linkers on DNA-coated colloids: valency without patches.

Colloids coated with single-stranded DNA (ssDNA) can bind selectively to other colloids coated with complementary ssDNA. The fact that DNA-coated colloids (DNACCs) can bind to specific partners opens the prospect of making colloidal "molecules." However, in order to design DNACC-based molecules, we must be able to control the valency of the colloids, i.e., the number of partners to which a given DNACC can bind. One obvious, but not very simple approach is to decorate the colloidal surface with patches of single-stranded DNA that selectively bind those on other colloids. Here we propose a design principle that exploits many-body effects to control the valency of otherwise isotropic colloids. Using a combination of theory and simulation, we show that we can tune the valency of colloids coated with mobile ssDNA, simply by tuning the nonspecific repulsion between the particles. Our simulations show that the resulting effective interactions lead to low-valency colloids self-assembling in peculiar open structures, very different from those observed in DNACCs with immobile DNA linkers.

Dynamic density functional theory of protein adsorption on polymer-coated nanoparticles.

We present a theoretical model for the description of the adsorption kinetics of globular proteins onto charged core-shell microgel particles based on Dynamic Density Functional Theory (DDFT). This model builds on a previous description of protein adsorption thermodynamics [Yigit et al., Langmuir, 2012, 28], shown to well interpret the available calorimetric experimental data of binding isotherms. In practice, a spatially-dependent free-energy functional including the same physical interactions is built, and used to study the kinetics via a generalised diffusion equation. To test this model, we apply it to the case study of lysozyme adsorption on PNIPAM coated nanoparticles, and show that the dynamics obtained within DDFT is consistent with that extrapolated from experiments. We also perform a systematic study of the effect of various parameters in our model, and investigate the loading dynamics as a function of proteins' valence and hydrophobic adsorption energy, as well as their concentration and that of the nanoparticles. Although we concentrated here on the case of adsorption for a single protein type, the model's generality allows to study multi-component system, providing a reliable instrument for future studies of competitive and cooperative adsorption effects often encountered in protein adsorption experiments.

Designing stimulus-sensitive colloidal walkers.

Colloidal particles with DNA "legs" that can bind reversibly to receptors on a surface can be made to 'walk' if there is a gradient in receptor concentration. We use a combination of theory and Monte Carlo simulations to explore how controllable parameters, e.g. coating density and binding strength, affect the dynamics of such colloids. We find that competition between thermodynamic and kinetic trends imply that there is an optimal value for both the binding strength and the number of "legs" for which transport is the fastest. Using available thermodynamic data on DNA binding, we indicate how directionally reversible, temperature-controlled transport of colloidal walkers can be achieved. In particular, the present results should make it possible to design a chromatographic technique that can be used to separate colloids with different DNA functionalizations.