M-Chem: a Modular Software Package for Molecular Simulation that Spans Scientific Domains.

We present a new software package called M-Chem that is designed from scratch in C++ and parallelized on shared-memory multi-core architectures to facilitate efficient molecular simulations. Currently, M-Chem is a fast molecular dynamics (MD) engine that supports the evaluation of energies and forces from two-body to many-body all-atom potentials, reactive force fields, coarse-grained models, combined quantum mechanics molecular mechanics (QM/MM) models, and external force drivers from machine learning, augmented by algorithms that are focused on gains in computational simulation times. M-Chem also includes a range of standard simulation capabilities including thermostats, barostats, multi-timestepping, and periodic cells, as well as newer methods such as fast extended Lagrangians and high quality electrostatic potential generation. At present M-Chem is a developer friendly environment in which we encourage new software contributors from diverse fields to build their algorithms, models, and methods in our modular framework. The long-term objective of M-Chem is to create an interdisciplinary platform for computational methods with applications ranging from biomolecular simulations, reactive chemistry, to materials research.

Oriented attachment kinetics for rod-like particles at a flat surface: Buffon's needle at the nanoscale.

The adsorption of large rod-like molecules or crystallites on a flat crystal face, similar to Buffon's needle, requires the rods to "land," with their binding sites in precise orientational alignment with matching sites on the surface. An example is provided by long, helical antifreeze proteins (AFPs), which bind at specific facets and orientations on the ice surface. The alignment constraint for adsorption, in combination with the loss in orientational freedom as the molecule diffuses toward the surface, results in an entropic barrier that hinders the adsorption. Prior kinetic models do not factor in the complete geometry of the molecule, nor explicitly enforce orientational constraints for adsorption. Here, we develop a diffusion-controlled adsorption theory for AFP molecules binding at specific orientations to flat ice surfaces. We formulate the diffusion equation with relevant boundary conditions and present analytical solutions to the attachment rate constant. The resulting rate constant is a function of the length and aspect ratio of the AFP, the distance threshold associated with binding, and solvent conditions such as temperature and viscosity. These results and methods of calculation may also be useful for predicting the kinetics of crystal growth through oriented attachment.

Protein Dynamics to Define and Refine Disordered Protein Ensembles.

Intrinsically disordered proteins and unfolded proteins have fluctuating conformational ensembles that are fundamental to their biological function and impact protein folding, stability, and misfolding. Despite the importance of protein dynamics and conformational sampling, time-dependent data types are not fully exploited when defining and refining disordered protein ensembles. Here we introduce a computational framework using an elastic network model and normal-mode displacements to generate a dynamic disordered ensemble consistent with NMR-derived dynamics parameters, including transverse R2 relaxation rates and Lipari-Szabo order parameters (S2 values). We illustrate our approach using the unfolded state of the drkN SH3 domain to show that the dynamical ensembles give better agreement than a static ensemble for a wide range of experimental validation data including NMR chemical shifts, J-couplings, nuclear Overhauser effects, paramagnetic relaxation enhancements, residual dipolar couplings, hydrodynamic radii, single-molecule fluorescence Förster resonance energy transfer, and small-angle X-ray scattering.

Diffusion Attachment Model for Long Helical Antifreeze Proteins to Ice.

Some of the most potent antifreeze proteins (AFPs) are approximately rigid helical structures that bind with one side in contact with the ice surface at specific orientations. These AFPs take random orientations in solution; however, most orientations become sterically inaccessible as the AFP approaches the ice surface. The effect of these inaccessible orientations on the rate of adsorption of AFP to ice has never been explored. Here, we present a diffusion-controlled theory of adsorption kinetics that accounts for these orientational restrictions to predict a rate constant for adsorption (kon, in m/s) as a function of the length and width of the AFP molecules. We find that kon decreases with length and diameter of the AFP and is almost proportional to the inverse of the area of the binding surface. We demonstrate that the restricted orientations create an entropic barrier to AFP adsorption, which we compute to be approximately 7 kBT for most AFPs and up to 9 kBT for Maxi, the largest known AFP. We compare the entropic resistance 1/kon to resistances for diffusion through boundary layers and across typical distances in the extracellular matrix and find that these entropic and diffusion resistances could become comparable in the small confined spaces of biological environments.

Computationally efficient approach for the identification of ice-binding surfaces and how they bind ice.

Recognition and binding of ice by proteins, crystals, and other surfaces is key for their control of the nucleation and growth of ice. Docking is the state-of-the-art computational method to identify ice-binding surfaces (IBS). However, docking methods require a priori knowledge of the ice plane to which the molecules bind and either neglect the competition of ice and water for the IBS or are computationally expensive. Here we present and validate a robust methodology for the identification of the IBS of molecules and crystals that is easy to implement and a hundred times computationally more efficient than the most advanced ice-docking approaches. The methodology is based on biased sampling with an order parameter that drives the formation of ice. We validate the method using all-atom and coarse-grained models of organic crystals and proteins. To our knowledge, this approach is the first to simultaneously identify the ice-binding surface as well as the plane of ice to which it binds, without the use of structure search algorithms. We show that biased simulations even identify surfaces that are too small or too weak to heterogeneously nucleate ice. The biasing simulations can be used to identify of IBS of antifreeze and ice nucleating proteins and to equilibrate ice seeds bound to an IBS for the calculation of heterogeneous ice nucleation rates using classical nucleation theory.

Slow Propagation of Ice Binding Limits the Ice-Recrystallization Inhibition Efficiency of PVA and Other Flexible Polymers.

Ice recrystallization inhibitors (IRI) are of critical importance in biology, cryopreservation of cells and organs, and frozen foods. Antifreeze glycoproteins (AFGPs) are the most potent IRI. Their cost and cytotoxicity drive the design of synthetic flexible polymers that mimic their function. Poly(vinyl alcohol) (PVA) is the most potent biomimetic found to date, although it is orders of magnitude less potent than AFGPs. A lack of molecular understanding of the factors that limit the IRI efficiency of PVA and other flexible ice-binding polymers hinders the design of more potent IRI. Here, we use molecular and numerical simulations to elucidate how the degree of polymerization (DP) and functionalization of PVA impact its IRI. Our simulations indicate that the onset of IRI activity of PVA occurs for 15 < DP < 20, in agreement with experiments. We predict that polymers with stronger binding to ice per monomer attain IRI activity at lower DP and identify this as a contributor to the higher IRI potency of AFGPs. The simulations reveal that the limiting step for binding of flexible molecules to ice is not the alignment of the molecule to the surface or the initiation of the binding but the propagation to reach its full binding potential. This distinguishes AFGPs and PVA from rigid antifreeze proteins and, we argue, is responsible for their different scaling of efficiencies with molecular size. We use the analysis of PVA to identify the factors that control the IRI activity of flexible polymers and assess the molecular characteristics that endow AFGPs with their exceptional IRI potency.

Can clathrates heterogeneously nucleate ice?

Methane hydrates can be preserved at ambient pressure, beyond their region of thermodynamic stability, by storing them at temperatures from 240 to 270 K. The origin of this anomalous self-preservation is the formation of an ice coating that covers the clathrate particles and prevents further loss of gas. While there have been several studies on self-preservation, the question of what is the mechanism by which ice nucleates on the decomposing clathrate hydrates has not yet been fully explained. Here, we use molecular simulations, thermodynamic analysis, and nucleation theory to investigate possible scenarios for the nucleation of ice: heterogeneous nucleation at the clathrate/vapor or clathrate/liquid interfaces and homogeneous nucleation from supercooled water. Our results indicate that clathrates cannot heterogeneously nucleate ice and that ice nucleation is due to the cooling of water at the decomposing clathrate/liquid interface, which suffices to trigger homogeneous ice nucleation. We find that the (111) face of the sII structure clathrate can bind to the (111) plane of cubic ice or the basal plane of hexagonal ice through domain matching, resulting in a weak binding that-while insufficient to promote heterogeneous ice nucleation-suffices to produce epitaxy and alignment between these crystals. We use thermodynamic relations, theory, and the contact angles of ice at the (111) sII clathrate/liquid interface to determine-for the first time-the interfacial free energy of this most favorable ice-clathrate interface, 59 ± 5 mJ/m2. We discuss the implications of our results for the feasibility of heterogeneous nucleation of gas clathrates at ice/vapor interfaces.

How Do Surfactants Control the Agglomeration of Clathrate Hydrates?

Clathrate hydrates can spontaneously form under typical conditions found in oil and gas pipelines. The agglomeration of clathrates into large solid masses plugs the pipelines, posing adverse safety, economic, and environmental threats. Surfactants are customarily used to prevent the aggregation of clathrate particles and their coalescence with water droplets. It is generally assumed that a large contact angle between the surfactant-covered clathrate and water is a key predictor of the antiagglomerant performance of the surfactant. Here we use molecular dynamic simulations to investigate the structure and dynamics of surfactant films at the clathrate-oil interface, and their impact on the contact angle and coalescence between water droplets and hydrate particles. In agreement with the experiments, the simulations predict that surfactant-covered clathrate-oil interfaces are oil wet but super-hydrophobic to water. Although the water contact angle determines the driving force for coalescence, we find that a large contact angle is not sufficient to predict good antiagglomerant performance of a surfactant. We conclude that the length of the surfactant molecules, the density of the interfacial film, and the strength of binding of its molecules to the clathrate surface are the main factors in preventing the coalescence and agglomeration of clathrate particles with water droplets in oil. Our analysis provides a molecular foundation to guide the molecular design of effective clathrate antiagglomerants.

The Clathrate-Water Interface Is Oleophilic.

The slow nucleation of clathrate hydrates is a central challenge for their use in the storage and transportation of natural gas. Molecules that strongly adsorb to the clathrate-water interface decrease the crystal-water surface tension, lowering the barrier for clathrate nucleation. Surfactants are widely used to promote the nucleation and growth of clathrate hydrates. It has been proposed that these amphiphilic molecules bind to the clathrate surface via hydrogen bonding. However, recent studies reveal that PVCap, an amphiphilic polymer, binds to clathrates through hydrophobic moieties. Here we use molecular dynamic simulations and theory to investigate the mode and strength of binding of surfactants to the clathrate-water interface and their effect on the nucleation rate. We find that the surfactants bind to the clathrate-water interface exclusively through their hydrophobic tails. The binding is strong, driven by the entropy of dehydration of the alkyl chain, as it penetrates empty cavities at the hydrate surface. The hydrophobic attraction of alkyl groups to the clathrate surface also results in strong adsorption of alkanes. We identify two regimes for the binding of surfactants as a function of their density at the hydrate surface, which we interpret to correspond to the two steps of the Langmuir adsorption isotherm observed in experiments. Our results indicate that hydrophobic attraction to the clathrate-water interface is key for the design of soluble additives that promote the nucleation of hydrates. We use the calculated adsorption coefficients to estimate the concentration of sodium dodecyl sulfate (SDS) required to reach nucleation rates for methane hydrate consistent with those measured in experiments. To our knowledge, this study is the first to quantify the effect of surfactant concentration in the nucleation rate of clathrate hydrates.

What Controls the Limit of Supercooling and Superheating of Pinned Ice Surfaces?

Cold-adapted organisms produce antifreeze proteins and glycoproteins to control the growth, melting and recrystallization of ice. It has been proposed that these molecules pin the crystal surface, creating a curvature that arrests the growth and melting of the crystal. Here we use thermodynamic modeling and molecular simulations to demonstrate that the curvature of the superheated or supercooled surface depends on the temperature and distances between ice-binding molecules, but not the details of their interactions with ice. We perform simulations of ice pinned with the antifreeze protein TmAFP, polyvinyl alcohol with different degrees of polymerization, and model ice-binding molecules to determine the thermal hystereses on melting and freezing, i.e. the maximum curvature that can be attained before, respectively, ice melts or grows irreversibly over the ice-binding molecules. We find that the thermal hysteresis is controlled by the bulkiness of the ice-binding molecules and their footprint at the ice surface. We elucidate the origin of the asymmetry between freezing and melting hysteresis found in experiments and propose guidelines to design synthetic antifreeze molecules with potent thermal hysteresis activity.