A streamlined molecular-dynamics workflow for computing solubilities of molecular and ionic crystals.

Computing the solubility of crystals in a solvent using atomistic simulations is notoriously challenging due to the complexities and convergence issues associated with free-energy methods, as well as the slow equilibration in direct-coexistence simulations. This paper introduces a molecular-dynamics workflow that simplifies and robustly computes the solubility of molecular or ionic crystals. This method is considerably more straightforward than the state-of-the-art, as we have streamlined and optimised each step of the process.

Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation.

Our current understanding of biomolecular condensate formation is largely based on observing the final near-equilibrium condensate state. Despite expectations from classical nucleation theory, pre-critical protein clusters were recently shown to form under subsaturation conditions in vitro; if similar long-lived clusters comprising more than a few molecules are also present in cells, our understanding of the physical basis of biological phase separation may fundamentally change. Here, we combine fluorescence microscopy with photobleaching analysis to quantify the formation of clusters of NELF proteins in living, stressed cells.

Aromatic and arginine content drives multiphasic condensation of protein-RNA mixtures.

Multiphasic architectures are found ubiquitously in biomolecular condensates and are thought to have important implications for the organization of multiple chemical reactions within the same compartment. Many of these multiphasic condensates contain RNA in addition to proteins. Here, we investigate the importance of different interactions in multiphasic condensates comprising two different proteins and RNA using computer simulations with a residue-resolution coarse-grained model of proteins and RNA.

Thermodynamic origins of two-component multiphase condensates of proteins.

Intracellular condensates are highly multi-component systems in which complex phase behaviour can ensue, including the formation of architectures comprising multiple immiscible condensed phases. Relying solely on physical intuition to manipulate such condensates is difficult because of the complexity of their composition, and systematically learning the underlying rules experimentally would be extremely costly. We address this challenge by developing a computational approach to design pairs of protein sequences that result in well-separated multilayered condensates and elucidate the molecular origins of these compartments.

Phase diagrams-Why they matter and how to predict them.

Understanding the thermodynamic stability and metastability of materials can help us to, for example, gauge whether crystalline polymorphs in pharmaceutical formulations are likely to be durable. It can also help us to design experimental routes to novel phases with potentially interesting properties. In this Perspective, we provide an overview of how thermodynamic phase behavior can be quantified both in computer simulations and machine-learning approaches to determine phase diagrams, as well as combinations of the two.

Simulations of DNA-Origami Self-Assembly Reveal Design-Dependent Nucleation Barriers.

Nucleation is the rate-determining step in the kinetics of many self-assembly processes. However, the importance of nucleation in the kinetics of DNA-origami self-assembly, which involves both the binding of staple strands and the folding of the scaffold strand, is unclear. Here, using Monte Carlo simulations of a lattice model of DNA origami, we find that some, but not all, designs can have a nucleation barrier and that this barrier disappears at lower temperatures, rationalizing the success of isothermal assembly.

Thermodynamics of high-pressure ice phases explored with atomistic simulations.

Most experimentally known high-pressure ice phases have a body-centred cubic (bcc) oxygen lattice. Our large-scale molecular-dynamics simulations with a machine-learning potential indicate that, amongst these bcc ice phases, ices VII, VII' and X are the same thermodynamic phase under different conditions, whereas superionic ice VII″ has a first-order phase boundary with ice VII'. Moreover, at about 300 GPa, the transformation between ice X and the Pbcm phase has a sharp structural change but no apparent activation barrier, whilst at higher pressures the barrier gradually increases.

Physics-driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy.

Various physics- and data-driven sequence-dependent protein coarse-grained models have been developed to study biomolecular phase separation and elucidate the dominant physicochemical driving forces. Here, we present Mpipi, a multiscale coarse-grained model that describes almost quantitatively the change in protein critical temperatures as a function of amino-acid sequence. The model is parameterised from both atomistic simulations and bioinformatics data and accounts for the dominant role of - and hybrid cation-/- interactions and the much stronger attractive contacts established by arginines than lysines.

Targeted modulation of protein liquid-liquid phase separation by evolution of amino-acid sequence.

Rationally and efficiently modifying the amino-acid sequence of proteins to control their ability to undergo liquid-liquid phase separation (LLPS) on demand is not only highly desirable, but can also help to elucidate which protein features are important for LLPS. Here, we propose a computational method that couples a genetic algorithm to a sequence-dependent coarse-grained protein model to evolve the amino-acid sequences of phase-separating intrinsically disordered protein regions (IDRs), and purposely enhance or inhibit their capacity to phase-separate. We validate the predicted critical solution temperatures of the mutated sequences with ABSINTH, a more accurate all-atom model.

Quantum-mechanical exploration of the phase diagram of water.

The set of known stable phases of water may not be complete, and some of the phase boundaries between them are fuzzy. Starting from liquid water and a comprehensive set of 50 ice structures, we compute the phase diagram at three hybrid density-functional-theory levels of approximation, accounting for thermal and nuclear fluctuations as well as proton disorder. Such calculations are only made tractable because we combine machine-learning methods and advanced free-energy techniques.

Numerical calculation of free-energy barriers for entangled polymer nucleation.

The crystallization of entangled polymers from their melt is investigated using computer simulation with a coarse-grained model. Using hybrid Monte Carlo simulations enables us to probe the behavior of long polymer chains. We identify solid-like beads with a centrosymmetry local order parameter and compute the nucleation free-energy barrier at relatively high supercooling with adaptive-bias windowed umbrella sampling.

Predicting the phase diagram of titanium dioxide with random search and pattern recognition.

Predicting phase stabilities of crystal polymorphs is central to computational materials science and chemistry. Such predictions are challenging because they first require searching for potential energy minima and then performing arduous free-energy calculations to account for entropic effects at finite temperatures. Here, we develop a framework that facilitates such predictions by exploiting all the information obtained from random searches of crystal structures.

Programming the Nucleation of DNA Brick Self-Assembly with a Seeding Strand.

Recently, the DNA brick strategy has provided a highly modular and scalable approach for the construction of complex structures, which can be used as nanoscale pegboards for the precise organization of molecules and nanoparticles for many applications. Despite the dramatic increase of structural complexity provided by the DNA brick method, the assembly pathways are still poorly understood. Herein, we introduce a "seed" strand to control the crucial nucleation and assembly pathway in DNA brick assembly.

Microscopic analysis of thermo-orientation in systems of off-centre Lennard-Jones particles.

When fluids of anisotropic molecules are placed in temperature gradients, the molecules may align themselves along the gradient: this is called thermo-orientation. We discuss the theory of this effect in a fluid of particles that interact by a spherically symmetric potential, where the particles' centres of mass do not coincide with their interaction centres. Starting from the equations of motion of the molecules, we show how a simple assumption of local equipartition of energy can be used to predict the thermo-orientation effect, recovering the result of Wirnsberger et al.

Lattice models and Monte Carlo methods for simulating DNA origami self-assembly.

The optimal design of DNA origami systems that assemble rapidly and robustly is hampered by the lack of a model for self-assembly that is sufficiently detailed yet computationally tractable. Here, we propose a model for DNA origami that strikes a balance between these two criteria by representing these systems on a lattice at the level of binding domains. The free energy of hybridization between individual binding domains is estimated with a nearest-neighbour model.

Direct observation and rational design of nucleation behavior in addressable self-assembly.

To optimize a self-assembly reaction, it is essential to understand the factors that govern its pathway. Here, we examine the influence of nucleation pathways in a model system for addressable, multicomponent self-assembly based on a prototypical "DNA-brick" structure. By combining temperature-dependent dynamic light scattering and atomic force microscopy with coarse-grained simulations, we show how subtle changes in the nucleation pathway profoundly affect the yield of the correctly formed structures.

Investigating the role of boundary bricks in DNA brick self-assembly.

In the standard DNA brick set-up, distinct 32-nucleotide strands of single-stranded DNA are each designed to bind specifically to four other such molecules. Experimentally, it has been demonstrated that the overall yield is increased if certain bricks which occur on the outer faces of target structures are merged with adjacent bricks. However, it is not well understood by what mechanism such 'boundary bricks' increase the yield, as they likely influence both the nucleation process and the final stability of the target structure.

Self-assembly of two-dimensional binary quasicrystals: a possible route to a DNA quasicrystal.

We use Monte Carlo simulations and free-energy techniques to show that binary solutions of penta- and hexavalent two-dimensional patchy particles can form thermodynamically stable quasicrystals even at very narrow patch widths, provided their patch interactions are chosen in an appropriate way. Such patchy particles can be thought of as a coarse-grained representation of DNA multi-arm 'star' motifs, which can be chosen to bond with one another very specifically by tuning the DNA sequences of the protruding arms. We explore several possible design strategies and conclude that DNA star tiles that are designed to interact with one another in a specific but not overly constrained way could potentially be used to construct soft quasicrystals in experiment.

DNA brick self-assembly with an off-lattice potential.

We report Monte Carlo simulations of a simple off-lattice patchy-particle model for DNA 'bricks'. We relate the parameters that characterise this model with the binding free energy of pairs of single-stranded DNA molecules. We verify that an off-lattice potential parameterised in this way reproduces much of the behaviour seen with a simpler lattice model we introduced previously, although the relaxation of the geometric constraints leads to a more error-prone self-assembly pathway.

Effects of co-ordination number on the nucleation behaviour in many-component self-assembly.

We report canonical and grand-canonical lattice Monte Carlo simulations of the self-assembly of addressable structures comprising hundreds of distinct component types. The nucleation behaviour, in the form of free-energy barriers to nucleation, changes significantly as the co-ordination number of the building blocks is changed from 4 to 8 to 12. Unlike tetrahedral structures - which roughly correspond to DNA bricks that have been studied in experiments - the shapes of the free-energy barriers of higher co-ordination structures depend strongly on the supersaturation, and such structures require a very significant driving force for structure growth before nucleation becomes thermally accessible.

Rational design of self-assembly pathways for complex multicomponent structures.

The field of complex self-assembly is moving toward the design of multiparticle structures consisting of thousands of distinct building blocks. To exploit the potential benefits of structures with such "addressable complexity," we need to understand the factors that optimize the yield and the kinetics of self-assembly. Here we use a simple theoretical method to explain the key features responsible for the unexpected success of DNA-brick experiments, which are currently the only demonstration of reliable self-assembly with such a large number of components.

Communication: theoretical prediction of free-energy landscapes for complex self-assembly.

We present a technique for calculating free-energy profiles for the nucleation of multicomponent structures that contain as many species as building blocks. We find that a key factor is the topology of the graph describing the connectivity of the target assembly. By considering the designed interactions separately from weaker, incidental interactions, our approach yields predictions for the equilibrium yield and nucleation barriers.

Effects of surface interactions on heterogeneous ice nucleation for a monatomic water model.

Despite its importance in atmospheric science, much remains unknown about the microscopic mechanism of heterogeneous ice nucleation. In this work, we perform hybrid Monte Carlo simulations of the heterogeneous nucleation of ice on a range of generic surfaces, both flat and structured, in order to probe the underlying factors affecting the nucleation process. The structured surfaces we study comprise one basal plane bilayer of ice with varying lattice parameters and interaction strengths.

Numerical evidence for nucleated self-assembly of DNA brick structures.

The observation by Ke et al. [Science 338, 1177 (2012)] that large numbers of short, predesigned DNA strands can assemble into three-dimensional target structures came as a great surprise, as no colloidal self-assembling system has ever achieved the same degree of complexity. That failure seemed easy to rationalize: the larger the number of distinct building blocks, the higher the expected error rate for self-assembly.

Note: Homogeneous TIP4P/2005 ice nucleation at low supercooling.

We present a partial free energy profile for the homogeneous nucleation of ice using an all-atom model of water at low supercooling, at which ice growth dynamics are reasonably accessible to simulation. We demonstrate that the free energy profile is well described by classical nucleation theory, and that the nucleation barrier is entropic in origin. We also estimate to first order the temperature dependence of the interfacial free energy.