Session R07: Programmable Self-Assembly: Particle, Interaction and Pathway Design (DNA Interactions)

Live

Directed drug delivery is crucial for targeting cells selectively based on their receptor profile on the surface. Theoretical work by Martinez-Veracoechea et. al. [1] suggests that multivalent probes can distinguish between different surfaces based on the composition of receptors and ligands, also known as superselectivity. We test these predictions experimentally with a model system consisting of colloidal particles and a flat surface, both functionalized with mobile DNA linkers, as the ligand/receptor system [2,3]. With increasing ligand/receptor concentration we observe the formation of a binding patch and a rise in the number of bound particles. The transition between unbound and bound particles depends strongly on the interaction strength of individual ligand-receptor interactions. By introducing very weak interactions, we can tune the system such that we have an almost “on-off” binding behavior. To conclude we show that weak interactions in a model ligand-receptor system lead to superselective particle binding. Our findings will contribute to the design of directed drug delivery systems.

[1] F. J. Martinez-Veracoechea and D. Frenkel, PNAS, 108 (2011)
[2] S. A. J van der Meulen and M. E. Leunissen, JACS, 135 (2013)
[3] I. Chakraborty et al. Nanoscale, 9 (2017)   

Live

We present a systematic method for computing the ground state phase behavior of multicomponent colloidal materials. In two-dimensions there are exactly 17 “wallpaper groups” which represent distinct combinations of isometries of the Euclidean plane. Using properties of these groups, we develop an algorithm to cover the plane with a fixed number of arbitrary components in all ways that satisfy a desired stoichiometric ratio. These combined symmetry-stoichiometry rules dramatically reduce the number of possible configurations, which generally suffer from a so-called “combinatorial explosion” otherwise making extensive, random structure searching computationally infeasible. With subsequent continuum relaxation, this enumeration approach can predict crystal structures in silico for multicomponent colloidal mixtures. We use this approach to investigate the ground state phase behavior of multicomponent systems inspired by DNA-coated colloidal mixtures, with a focus on stable, low-density “open” crystals. We demonstrate the approach for binary and ternary mixtures at zero ambient pressure to explore how complexity can be achieved through the combination of several components with simple interactions rather than a single component with a more complicated interaction potential.   

Live

Nonequilibrium conditions lead to novel effective interactions and dynamics during colloidal self-assembly, resulting in new structural and fluxional phases of functional materials. Automated inverse design algorithms for self-assembly protocols out-of-equilibrium are constrained due to the corresponding configurational probability distributions being non-Boltzmann. We have developed an optimization algorithm to discover nonequilibrium inverse design principles based on a trajectory ensemble formalism. The optimization procedure uses explicit stochastic gradients within a nonequilibrium steady-state. We use this algorithm to discover optimal control forces in molecular dynamics simulations of DNA-labeled colloids, for the self-assembly of various target structures and dynamical states.   

Live

Solid-binding peptides provide remarkable opportunities for controlling hierarchical material assembly, but much remains to be learned about the fundamental mechanisms. Here, we use a bifunctional solid-binding protein containing two genetically engineered silica-binding peptides Car9 on opposite sides of a sfGFP protein scaffold to show that with a molar ratio of protein to silica nanoparticle (SiNP) of 5:1, aggregates formed at a pH of 7.5 can be repeatedly dissociated and reformed through cycles of pH between 7.5 and 8.5. We develop a multi-scale simulation framework to link the underlying molecular-scale features of the protein/SiNP interface with experimental observations, with the goal to predict aggregation pathways and kinetics. Interparticle interactions are calculated using atomistic molecular dynamics simulation and colloidal theory, based on which we construct coarse-grained (CG) rigid body simulations to obtain characteristic timescale for forming an aggregate of ~10² nm. We then bridge CG results with experiments using Smoluchowski theory for Brownian aggregation. We successfully simulate a pH-mediated reversible assembly that reproduces experimental results and identify crucial parameters that tune pathways and kinetics.   

Live

Particles with sticky feet - or nanoscale caterpillars - in biological or artificial systems, beat the paradigm of standard diffusion to achieve complex functions. Some cells (like leucocytes) use ligand-receptor contacts (sticky feet) to crawl and roll along vessels. Sticky DNA (another type of sticky feet) is coated on colloids to design programmable interactions and self-assembly. Predicting the dynamics of such sticky motion is challenging since sticky events (attaching/detaching) often occur on very short time scales compared to the overall motion of the particle. Even understanding the equilibrium statistics of these systems (how many feet are attached in average) is largely uncharted. Yet, controlling the dynamics of such particles is critical to achieve these advanced functions -- for example facilitating rolling is critical for long-range alignment of DNA coated-colloids crystals. Here we present advanced theory and experimental results on a model system. We rationalize what parameters control average feet attachment and how they can be compared to other existing systems. We investigate furthermore how various motion modes (rolling, sliding or skipping) may be favored over one another.   

Live

Recent advances in encoding specific interactions on microscopic particles allow programming self-assembly of complex multiscale structures. However, this programming is currently limited by two factors: off-target particle binding, or cross-talk, and lack of computational tools for design of heterogeneous particle sets. Here we use statistical mechanics, combinatorics, and spectral methods to directly relate the properties of particle sets to the yields of all structures they self-assemble. We derive analytical limits on the largest structures reliably assembled for a given level of cross-talk. These results allow us to formulate specific design rules for particle sets that optimally self-assemble structures of two different topologies: rings and chains.   

Live

The spontaneous assembly of individual objects not just to rafts or clusters, but to complex structures in two or three dimensions is an important goal of both fundamental and applied research, providing insight into processes like protein folding and the synthesis of branched macromolecules. To control this process, one has to control the valence of the constitutive objects. It is shown here that microscale droplets uniformly coated with mobile DNA molecules bind to each other reversibly with well-defined valence determined by the overall DNA coverage of each droplet. This experimental finding is explained by a purely thermodynamic theory, demonstrating that proper accounting of free energy contributions from molecular interactions and entropy predicts selection of a preferred number of binding patches. The theory shows how varying the properties of binder molecules and droplets allows for customization of valence, and thus of the self-assembled structures.   

Live

DNA functionalization of particles and droplets has recently emerged as a new tool to achieve programmable sequential self-assembly of colloidal structures. The hybridization of complementary DNA strands is temperature-dependent, and above its melting temperature, the bonds unbind. The temperature-dependent binding allows for tempering and control over the binding strength. Moreover, DNA strands' recruitment on a mobile interface renders the interaction between droplet surface time and history-dependent. We present results on the interaction between DNA-mediated emulsion droplets using time-shared optical tweezers. To this end, we trap two droplets with the optical tweezers and move them close to contact. Then the interaction potential between the droplets is measured by tracking their center-to-center distance. We find a weak, short-range attraction between droplets with complementary DNA strands at higher temperatures. The attraction strength increases when lowering the temperature from 50 to 25°C. In some measurements, we observe that the droplets form a "permanent bond" that cannot be broken by the optical tweezer force.   

Live

The pathways to colloidal self-assembly could be more complicated than we might naively expect. While the classical picture predicts that a crystal assembles by a fluctuation that kicks the system over a single free-energy barrier, a growing body of evidence shows that this process can proceed via multiple transformations of metastable structures towards the thermodynamic minimum. In this talk, I will present results of an experimental and computational study of the crystallization of a binary mixture of DNA-coated colloids. We observe both classical one-step pathways, and non-classical two-step pathways that proceed via a solid-solid transformation. We use enhanced sampling to compute free energy landscapes corresponding to our experiments, and find that both one- and two-step pathways are driven by thermodynamics alone. Specifically, the two-step transition is governed by a competition between different crystal phases with free energies that depend on the crystal size. These results extend our understanding of available pathways to crystallization and may provide new approaches to programming the self-assembly of materials made from colloids.   

Live

While the spontaneous self-assembly of colloidal building blocks into opal-like crystals has long been considered a promising route for the fabrication of meta-materials, rather few structures have been demonstrated to form. Here we find that, contrary to simulations, binary DNA-grafted microspheres often simultaneously nucleate and grow different crystal forms (polymorphs) in the same sample, and that these unstable ‘floppy’ crystals, during slow cooling, transform into still more crystal structures. Remarkably, up to seven different crystal structures could be observed in a single sample. Varying the interactions and particle sizes, we found a total of ten different crystalline structures, including 6 not previously predicted or observed. Simulations with validated potentials predict that such transformations should result only in poorly ordered final states. We find that the crystals transform in a coherent manner into well-ordered final structures across all the parameters we explored, presumably controlled by kinetic factors, such as hydrodynamic interactions and the kinetics of the DNA bridges between particles. Our results indicate that a previously unsuspected range of crystal structures are accessible if the physics controlling their formation can be understood.   

Live

An immense challenge in materials sciences is to find a way to construct materials with absolute control over the placement of each building block to tailor properties for given applications. DNA coated colloids offer the possibility of realizing programmable self-assembly, which in principle can assemble almost any structure in equilibrium, while remains challenging experimentally. Here we propose a new system of linker-mediated mobile DNA coated colloids (mDNACCs), in which the interaction between mDNACCs is induced by the bridging of free DNA linkers in solution, whose two single stranded DNA (ssDNA) tails can bind with specific ssDNA receptors of complementary sequence coated on the colloids. We formulate a mean field theory to efficiently calculate the effective interaction between mDNACCs mediated by free linkers, in which the entropy of DNA linkers plays a non-trivial role. Especially, when the binding between free linkers in solution and the corresponding receptors on mDNACCs is very strong, the linker-mediated colloidal interaction is determined by the linker entropy, which depends on the concentration of free linkers. As the concentration of free linkers can be precisely controlled in experiments, this suggests a new way for experimentally designed assembly of DNACCs.   

Live

DNA origami is a method by which a single-stranded DNA scaffold is folded into some prescribed shape by hundreds of user-designed DNA ‘staple’ strands. Historically, this process has been used to make intricate 3D nanostructures with sub-nanometer precision. In this talk, I will discuss a new route for using DNA origami to make colloidal particles that then self-assemble into well-defined geometrical structures. More specifically, we use DNA origami to make triangular subunits and control their binding angles to program the assembly of nanotubes. The nanotubes are assembled from one type of triangle whose three edges bind to themselves at prescribed dihedral angles and are programmed by the DNA sequence design. We show that DNA origami triangles, which are each roughly 50 nanometers in size, can assemble into rigid tubules reaching a few micrometers in length. This scale corresponds to roughly 10 giga-Daltons—one of the largest assemblies made from DNA origami. Interestingly, we find that there is a distribution in the width and the chirality of the assembled tubes, suggesting that our DNA origami colloids could be flexible or that the kinetic pathway toward tube closure plays an important role in determining the final structure.   

Live

Colloidal particles coated with DNA can self-assemble into an amazing diversity of ordered structures; yet the dynamic pathways leading from the disordered state to the ordered state are comparatively unexplored. In this talk, I will present some of the first direct measurements of nucleation and growth of DNA-programmed crystallization. We use a microfluidic droplet-based technique to quantify the pathway to crystallization in hundreds of individual droplets simultaneously. We find that nucleation is governed by a single temperature-dependent free-energy barrier. The nucleation rate changes by orders of magnitude over 0.5 degrees and follows the predictions of classical nucleation theory. We also find that the rate of crystal growth is determined by a balance between the rate at which particles diffuse to the growing crystal surface and the rate at which they unbind from the crystal interface. Together, these results provide an explanation for why it’s been difficult to crystallize DNA-coated particles, and suggest ways to control the nucleation and growth rates to design new assembly pathways that yield large, single crystals.