Tine Curk

Superselective Targeting Using Multivalent Polymers

Despite their importance for material and life sciences, multivalent interactions between polymers and surfaces remain poorly understood. Combining recent achievements of synthetic chemistry and surface characterization, we have developed a well-defined and highly specific model system based on host/guest interactions. We use this model to study the binding of hyaluronic acid functionalized with host molecules to tunable surfaces displaying different densities of guest molecules. Remarkably, we find that the surface density of bound polymer increases faster than linearly with the surface density of binding sites. Based on predictions from a simple analytical model, we propose that this superselective behavior arises from a combination of enthalpic and entropic effects upon binding of nanoobjects to surfaces, accentuated by the ability of polymer chains to interpenetrate.

Designing multivalent probes for tunable superselective targeting

Significance A basic requirement in biomedical research is the ability to specifically target cells and tissues. Targeting typically relies on the specific binding of a “ligand” on a tailor-made probe to a “receptor” on the desired cell/tissue. Conventional probes efficiently distinguish a biological entity displaying the receptor from others that do not, but exhibit limited selectivity when the entities to be distinguished display a given receptor at different densities. Multivalent probes that bind several receptors simultaneously potentially can sharply discriminate between different receptor densities. We demonstrate how such “superselective” binding can be tuned through probe design to target a desired receptor density, and thus lay the foundation for the rational design of a new generation of analytical, diagnostic, and therapeutic probes. Specific targeting is common in biology and is a key challenge in nanomedicine. It was recently demonstrated that multivalent probes can selectively target surfaces with a defined density of surface binding sites. Here we show, using a combination of experiments and simulations on multivalent polymers, that such “superselective” binding can be tuned through the design of the multivalent probe, to target a desired density of binding sites. We develop an analytical model that provides simple yet quantitative predictions to tune the polymer’s superselective binding properties by its molecular characteristics such as size, valency, and affinity. This work opens up a route toward the rational design of multivalent probes with defined superselective targeting properties for practical applications, and provides mechanistic insight into the regulation of multivalent interactions in biology. To illustrate this, we show how the superselective targeting of the extracellular matrix polysaccharide hyaluronan to its main cell surface receptor CD44 is controlled by the affinity of individual CD44–hyaluronan interactions.

Liquid-crystalline ordering of antimicrobial peptide–DNA complexes controls TLR9 activation

Double-stranded DNA (dsDNA) can trigger the production of type I interferon (IFN) in plasmacytoid dendritic cells (pDCs) by binding to endosomal Toll-like receptor-9 (TLR9; refs 1-5). It is also known that the formation of DNA-antimicrobial peptide complexes can lead to autoimmune diseases via amplification of pDC activation. Here, by combining X-ray scattering, computer simulations, microscopy and measurements of pDC IFN production, we demonstrate that a broad range of antimicrobial peptides and other cationic molecules cause similar effects, and elucidate the criteria for amplification. TLR9 activation depends on both the inter-DNA spacing and the multiplicity of parallel DNA ligands in the self-assembled liquid-crystalline complex. Complexes with a grill-like arrangement of DNA at the optimum spacing can interlock with multiple TLR9 like a zipper, leading to multivalent electrostatic interactions that drastically amplify binding and thereby the immune response. Our results suggest that TLR9 activation and thus TLR9-mediated immune responses can be modulated deterministically.

On the Origin and Characteristics of Noise-Induced Lévy Walks of E. Coli

Lévy walks as a random search strategy have recently attracted a lot of attention, and have been described in many animal species. However, very little is known about one of the most important issues, namely how Lévy walks are generated by biological organisms. We study a model of the chemotaxis signaling pathway of E. coli, and demonstrate that stochastic fluctuations and the specific design of the signaling pathway in concert enable the generation of Lévy walks. We show that Lévy walks result from the superposition of an ensemble of exponential distributions, which occurs due to the shifts in the internal enzyme concentrations following the stochastic fluctuations. With our approach we derive the power-law analytically from a model of the chemotaxis signaling pathway, and obtain a power-law exponent , which coincides with experimental results. This work provides a means to confirm Lévy walks as natural phenomenon by providing understanding on the process through which they emerge. Furthermore, our results give novel insights into the design aspects of biological systems that are capable of translating additive noise on the microscopic scale into beneficial macroscopic behavior.

A new configurational bias scheme for sampling supramolecular structures

We present a new simulation scheme which allows an efficient sampling of reconfigurable supramolecular structures made of polymeric constructs functionalized by reactive binding sites. The algorithm is based on the configurational bias scheme of Siepmann and Frenkel and is powered by the possibility of changing the topology of the supramolecular network by a non-local Monte Carlo algorithm. Such a plan is accomplished by a multi-scale modelling that merges coarse-grained simulations, describing the typical polymer conformations, with experimental results accounting for free energy terms involved in the reactions of the active sites. We test the new algorithm for a system of DNA coated colloids for which we compute the hybridisation free energy cost associated to the binding of tethered single stranded DNAs terminated by short sequences of complementary nucleotides. In order to demonstrate the versatility of our method, we also consider polymers functionalized by receptors that bind a surface decorated by ligands. In particular, we compute the density of states of adsorbed polymers as a function of the number of ligand-receptor complexes formed. Such a quantity can be used to study the conformational properties of adsorbed polymers useful when engineering adsorption with tailored properties. We successfully compare the results with the predictions of a mean field theory. We believe that the proposed method will be a useful tool to investigate supramolecular structures resulting from direct interactions between functionalized polymers for which efficient numerical methodologies of investigation are still lacking.

Optimal multivalent targeting of membranes with many distinct receptors

Significance A key challenge in biomedical research is the ability to specifically target cells and tissues. Targeting typically relies on identifying a suitable marker, e.g., a highly expressed receptor, and choosing a ligand that strongly and specifically binds to the marker. However, this procedure fails when a suitable marker unique to the targeted cells cannot be identified, notably in many forms of cancer. We show that properly designed multivalent targeting of multiple cognate receptor types results in a specificity toward a chosen receptor density profile, thus demonstrating a general route toward targeting cells without particularly dominant markers. Cells can often be recognized by the concentrations of receptors expressed on their surface. For better (targeted drug treatment) or worse (targeted infection by pathogens), it is clearly important to be able to target cells selectively. A good targeting strategy would result in strong binding to cells with the desired receptor profile and barely binding to other cells. Using a simple model, we formulate optimal design rules for multivalent particles that allow them to distinguish target cells based on their receptor profile. We find the following: (i) It is not a good idea to aim for very strong binding between the individual ligands on the guest (delivery vehicle) and the receptors on the host (cell). Rather, one should exploit multivalency: High sensitivity to the receptor density on the host can be achieved by coating the guest with many ligands that bind only weakly to the receptors on the cell surface. (ii) The concentration profile of the ligands on the guest should closely match the composition of the cognate membrane receptors on the target surface. And (iii) irrespective of all details, the effective strength of the ligand–receptor interaction should be of the order of the thermal energy kBT, where T is the absolute temperature and kB is Boltzmann’s constant. We present simulations that support the theoretical predictions. We speculate that, using the above design rules, it should be possible to achieve targeted drug delivery with a greatly reduced incidence of side effects.

Collective ordering of colloids in grafted polymer layers

We present Monte Carlo simulations of colloidal particles pulled into grafted polymer layers by an external force. The insertion free energy for penetration of a single colloid into a polymer layer is qualitatively different for surfaces with an ordered and a disordered distribution of grafting points and the tendency of colloidal particles to traverse the grafting layer is strongly size dependent. In dense colloidal suspensions, under the influence of sufficiently strong external forces, colloids penetrate and form internally ordered, columnar structures spanning the polymer layer. The competition between the tendency for macro-phase separation of colloids and polymers and the elastic-like penalty for deforming the grafted layer results in the micro-phase separation, i.e. finite colloidal clusters characterized by a well-defined length scale. Depending on the conditions, these clusters are isolated or laterally percolating. The morphology of the observed patterns can be controlled by the external fields, which opens up new routes for the design of thin structured films.

Layering, freezing, and re-entrant melting of hard spheres in soft confinement.

Confinement can have a dramatic effect on the behavior of all sorts of particulate systems, and it therefore is an important phenomenon in many different areas of physics and technology. Here, we investigate the role played by the softness of the confining potential. Using grand canonical Monte Carlo simulations, we determine the phase diagram of three-dimensional hard spheres that in one dimension are constrained to a plane by a harmonic potential. The phase behavior depends strongly on the density and on the stiffness of the harmonic confinement. While we find the familiar sequence of confined hexagonal and square-symmetric packings, we do not observe any of the usual intervening ordered phases. Instead, the system phase separates under strong confinement, or forms a layered re-entrant liquid phase under weaker confinement. It is plausible that this behavior is due to the larger positional freedom in a soft confining potential and to the contribution that the confinement energy makes to the total free energy. The fact that specific structures can be induced or suppressed by simply changing the confinement conditions (e.g., in a dielectrophoretic trap) is important for applications that involve self-assembled structures of colloidal particles.

The Effect of Attractive Interactions and Macromolecular Crowding on Crystallins Association

In living systems proteins are typically found in crowded environments where their effective interactions strongly depend on the surrounding medium. Yet, their association and dissociation needs to be robustly controlled in order to enable biological function. Uncontrolled protein aggregation often causes disease. For instance, cataract is caused by the clustering of lens proteins, i.e., crystallins, resulting in enhanced light scattering and impaired vision or blindness. To investigate the molecular origins of cataract formation and to design efficient treatments, a better understanding of crystallin association in macromolecular crowded environment is needed. Here we present a theoretical study of simple coarse grained colloidal models to characterize the general features of how the association equilibrium of proteins depends on the magnitude of intermolecular attraction. By comparing the analytic results to the available experimental data on the osmotic pressure in crystallin solutions, we identify the effective parameters regimes applicable to crystallins. Moreover, the combination of two models allows us to predict that the number of binding sites on crystallin is small, i.e. one to three per protein, which is different from previous estimates. We further observe that the crowding factor is sensitive to the size asymmetry between the reactants and crowding agents, the shape of the protein clusters, and to small variations of intermolecular attraction. Our work may provide general guidelines on how to steer the protein interactions in order to control their association.

A review of immune amplification via ligand clustering by self-assembled liquid-crystalline DNA complexes.

We examine how the interferon production of plasmacytoid dendritic cells is amplified by the self-assembly of liquid-crystalline antimicrobial peptide/DNA complexes. These specialized dendritic cells are important for host defense because they quickly release large quantities of type I interferons in response to infection. However, their aberrant activation is also correlated with autoimmune diseases such as psoriasis and lupus. In this review, we will describe how polyelectrolyte self-assembly and the statistical mechanics of multivalent interactions contribute to this process. In a more general compass, we provide an interesting conceptual corrective to the common notion in molecular biology of a dichotomy between specific interactions and non-specific interactions, and show examples where one can construct exquisitely specific interactions using non-specific interactions.