Density of states-based molecular simulations

Pressure-induced structural phase transitions of zirconium: anab initiostudy based on statistical ensemble theory

Recently, we put forward a direct integral approach to solve the partition function with ultrahigh efficiency and precision, which enables the rigorous ensemble theory to investigate phase behaviors of realistic condensed matters and has been successfully applied to the phase transition of vanadium metal (Ninget al2022J. Phys.: Condens. Matter34425404). In this work, the approach is applied to the structural phase transitions of zirconium metal under compressions up to 160 GPa and ultrahigh calculation precision is achieved. For the obtained equation of state with pressure over 40 GPa, the deviations from latest experiments are within0.7%and the computed transition pressure ofα→ωis 6.93 GPa, which is about five times larger than previous theoretical predictions and in excellent agreement with the measured range of 5-15 GPa. Our results support the argument that there is no existence of the isostructural phase transition of Zr metal that was asserted by recent experimental observations.

Semiflexible oligomers crystallize via a cooperative phase transition

Semicrystalline polymers are ubiquitous, yet despite their fundamental and industrial importance, the theory of homogeneous nucleation from a melt remains a subject of debate. A key component of the controversy is that polymer crystallization is a non-equilibrium process, making it difficult to distinguish between effects that are purely kinetic and those that arise from the underlying thermodynamics. Due to computational cost constraints, simulations of polymer crystallization typically employ non-equilibrium molecular dynamics techniques with large degrees of undercooling that further exacerbate the coupling between thermodynamics and kinetics. In a departure from this approach, in this study, we isolate the near-equilibrium nucleation behavior of a simple model of a melt of short, semiflexible oligomers. We employ several Monte Carlo methods and compute a phase diagram in the temperature-density plane along with two-dimensional free energy landscapes (FELs) that characterize the nucleation behavior. The phase diagram shows the existence of ordered nematic and crystalline phases in addition to the disordered melt phase. The minimum free energy path in the FEL for the melt-crystal transition shows a cooperative transition, where nematic order and monomer positional order move in tandem as the system crystallizes. This near-equilibrium phase transition mechanism broadly agrees with recent evidence that polymer stiffness plays an important role in crystallization but differs in the specifics of the mechanism from several recent theories. We conclude that the computation of multidimensional FELs for models that are larger and more fine-grained will be important for evaluating and refining theories of homogeneous nucleation for polymer crystallization.

Rejection-free cluster Wang-Landau algorithm for hard-core lattice gases

We introduce a rejection-free, flat histogram, cluster algorithm to determine the density of states of hard-core lattice gases. We show that the algorithm is able to efficiently sample low entropy states that are usually difficult to access, even when the excluded volume per particle is large. The algorithm is based on simultaneously evaporating all the particles in a strip and reoccupying these sites with a new appropriately chosen configuration. We implement the algorithm for the particular case of the hard-core lattice gas in which the first k next-nearest neighbors of a particle are excluded from being occupied. It is shown that the algorithm is able to reproduce the known results for k=1,2,3 both on the square and cubic lattices. We also show that, in comparison, the corresponding flat histogram algorithms with either local moves or unbiased cluster moves are less accurate and do not converge as the system size increases.

A molecular view of plasticization of polyvinyl alcohol

Although macromolecules such as polymers are in widespread industrial use, pure formulations rarely have precisely the properties new applications demand. Pure polymer is often too brittle and inflexible, necessitating plasticizers to soften or toughen films and bulk polymer materials. In practice, new formulations are developed by extensive trial-and-error methods, as no general molecular explanations exist for the mechanism of plasticization to aid in determining the optimal structure and concentration of plasticizers. Here, through atomistic molecular simulations augmented with advanced sampling techniques, we develop an atomic-level picture of the processes in plasticization by directly calculating free energies that govern the interaction between polymers and small-molecule plasticizers. This work focuses on the influence of two common plasticizer molecules-glycerol and sorbitol-interacting with polyvinyl alcohol (PVA), a frequently used component of polymer films. In particular, we focus on conformational and hydrogen bond structure changes induced in globules of PVA by the plasticizer molecules, with the hypothesis that hydrogen bonding plays a role in the incorporation of these plasticizers into PVA and, thus, in the observed mechanical properties. While we focus on nanoscopic systems, we observe distinct preferences in the conformational free energy that can be connected to the performance of polymer materials at laboratory and industrial scales. This work presents a new molecular perspective from which effective plasticizers can be developed and presents a firm basis from which important analyses of plasticization in complex chemical environments relevant to industry may be developed.

Efficient approaches to solutions of partition function for condensed matters

The key problem of statistical physics standing over one hundred years is how to exactly calculate the partition function (or free energy), which severely hinders the theory to be applied to predict the thermodynamic properties of condensed matters. Very recently, we developed a direct integral approach (DIA) to the solutions and achieved ultrahigh computational efficiency and precision. In the present work, the background and the limitations of DIA were examined in details, and another method with the same efficiency was established to overcome the shortage of DIA for condensed system with lower density. The two methods were demonstrated with empirical potentials for solid and liquid cooper, solid argon and C₆₀ molecules by comparing the derived internal energy or pressure with the results of vast molecular dynamics simulations, showing that the precision is about ten times higher than previous methods in a temperature range up to melting point. The ultrahigh efficiency enables the two methods to be performed with ab initio calculations and the experimental equation of state of solid copper up to ∼600 GPa was well reproduced, for the first time, from the partition function via density functional theory implemented.

Stochastic approximation Monte Carlo with a dynamic update factor

We present a Monte Carlo algorithm based on the stochastic approximation Monte Carlo (SAMC) algorithm for directly calculating the density of states. The proposed method is stochastic approximation with a dynamic update factor (SAD), which dynamically adjusts the update factor γ_{t} during the course of the simulation. We test this method on a square-well fluid and a 31-atom Lennard-Jones cluster and compare the convergence behavior of several related Monte Carlo methods. We find that both the SAD and 1/t-Wang-Landau (1/t-WL) methods rapidly converge to the correct density of states without the need for the user to specify an arbitrary tunable parameter t_{0} as in the case of SAMC. SAD requires as input the temperature range of interest, in contrast with 1/t-WL, which requires that the user identify the interesting range of energies. The convergence of the 1/t-WL method is very sensitive to the energy range chosen for the low-temperature heat capacity of the Lennard-Jones cluster. Thus, SAD is more powerful in the common case in which the range of energies is not known in advance.

Comparison of Two Efficient Methods for Calculating Partition Functions

In the long-time pursuit of the solution to calculating the partition function (or free energy) of condensed matter, Monte-Carlo-based nested sampling should be the state-of-the-art method, and very recently, we established a direct integral approach that works at least four orders faster. In present work, the above two methods were applied to solid argon at temperatures up to 300 K. The derived internal energy and pressure were compared with the molecular dynamics simulation as well as experimental measurements, showing that the calculation precision of our approach is about 10 times higher than that of the nested sampling method.

Novel elastic response in twist-bend nematic models

Bent-shaped liquid crystals have attracted significant attention recently due to their novel mesostructure and the intriguing behavior of their elastic constants, which are strongly anisotropic and have an unusual temperature dependence. Though theories explain the onset of the twist-bend nematic phase (NTB) through spontaneous symmetry breaking concomitant with transition to a negative bend (K3) elastic constant, this has not been observed as yet in experiments. There, the small bend elastic constant has a strongly non-monotonic temperature dependence, which first increases after crossing the isotropic (I)-nematic (N) transition, then dips near the nematic (N)-twist-bend (NTB) transition before it increases again as the transition is crossed. The molecular mechanisms responsible for this exotic behavior are unclear. Here, we utilize density of states algorithms in Monte Carlo simulation applied to a variant of the Lebwohl-Lasher model which includes bent-shaped-like interactions to analyze the mechanism behind elastic response in this novel mesostructure and understand the temperature dependence of its Frank-Oseen elastic constants.

Solubility prediction from first principles: a density of states approach

Solubility is a fundamental property of widespread significance. Its accurate prediction remains a major challenge. We present a novel, efficient approach to solubility prediction for molecules over a range of conditions based on density of states.

Polymorphic phase transitions: Macroscopic theory and molecular simulation

Transformations in the solid state are of considerable interest, both for fundamental reasons and because they underpin important technological applications. The interest spans a wide spectrum of disciplines and application domains. For pharmaceuticals, a common issue is unexpected polymorphic transformation of the drug or excipient during processing or on storage, which can result in product failure. A more ambitious goal is that of exploiting the advantages of metastable polymorphs (e.g. higher solubility and dissolution rate) while ensuring their stability with respect to solid state transformation. To address these issues and to advance technology, there is an urgent need for significant insights that can only come from a detailed molecular level understanding of the involved processes. Whilst experimental approaches at best yield time- and space-averaged structural information, molecular simulation offers unprecedented, time-resolved molecular-level resolution of the processes taking place. This review aims to provide a comprehensive and critical account of state-of-the-art methods for modelling polymorph stability and transitions between solid phases. This is flanked by revisiting the associated macroscopic theoretical framework for phase transitions, including their classification, proposed molecular mechanisms, and kinetics. The simulation methods are presented in tutorial form, focusing on their application to phase transition phenomena. We describe molecular simulation studies for crystal structure prediction and polymorph screening, phase coexistence and phase diagrams, simulations of crystal-crystal transitions of various types (displacive/martensitic, reconstructive and diffusive), effects of defects, and phase stability and transitions at the nanoscale. Our selection of literature is intended to illustrate significant insights, concepts and understanding, as well as the current scope of using molecular simulations for understanding polymorphic transitions in an accessible way, rather than claiming completeness. With exciting prospects in both simulation methods development and enhancements in computer hardware, we are on the verge of accessing an unprecedented capability for designing and developing dosage forms and drug delivery systems in silico, including tackling challenges in polymorph control on a rational basis.

Quantum Chemical Methods for the Prediction of Energetic, Physical, and Spectroscopic Properties of Ionic Liquids

The accurate prediction of physicochemical properties of condensed systems is a longstanding goal of theoretical (quantum) chemistry. Ionic liquids comprising entirely of ions provide a unique challenge in this respect due to the diverse chemical nature of available ions and the complex interplay of intermolecular interactions among them, thus resulting in the wide variability of physicochemical properties, such as thermodynamic, transport, and spectroscopic properties. It is well understood that intermolecular forces are directly linked to physicochemical properties of condensed systems, and therefore, an understanding of this relationship would greatly aid in the design and synthesis of functionalized materials with tailored properties for an application at hand. This review aims to give an overview of how electronic structure properties obtained from quantum chemical methods such as interaction/binding energy and its fundamental components, dipole moment, polarizability, and orbital energies, can help shed light on the energetic, physical, and spectroscopic properties of semi-Coulomb systems such as ionic liquids. Particular emphasis is given to the prediction of their thermodynamic, transport, spectroscopic, and solubilizing properties.

Multidimensional stochastic approximation Monte Carlo

Stochastic Approximation Monte Carlo (SAMC) has been established as a mathematically founded powerful flat-histogram Monte Carlo method, used to determine the density of states, g(E), of a model system. We show here how it can be generalized for the determination of multidimensional probability distributions (or equivalently densities of states) of macroscopic or mesoscopic variables defined on the space of microstates of a statistical mechanical system. This establishes this method as a systematic way for coarse graining a model system, or, in other words, for performing a renormalization group step on a model. We discuss the formulation of the Kadanoff block spin transformation and the coarse-graining procedure for polymer models in this language. We also apply it to a standard case in the literature of two-dimensional densities of states, where two competing energetic effects are present g(E_{1},E_{2}). We show when and why care has to be exercised when obtaining the microcanonical density of states g(E_{1}+E_{2}) from g(E_{1},E_{2}).

Elastic response and phase behavior in binary liquid crystal mixtures

Utilizing density-of-states simulations, we perform a full mapping of the phase behavior and elastic responses of binary liquid crystalline mixtures represented by the multicomponent Lebwohl-Lasher model. Our techniques are able to characterize the complete phase diagram, including nematic-nematic phase separation predicted by mean-field theories, but previously not observed in simulations. Mapping this phase diagram permits detailed study of elastic properties across the miscible nematic region. Importantly, we observe for the first time local phase separation and disordering driven by the application of small linear perturbations near the transition temperature and more significantly through nonlinear stresses. These findings are of key importance in systems of blended nematics which contain particulate inclusions, or are otherwise confined.

Nested sampling of isobaric phase space for the direct evaluation of the isothermal-isobaric partition function of atomic systems

Nested Sampling (NS) is a powerful athermal statistical mechanical sampling technique that directly calculates the partition function, and hence gives access to all thermodynamic quantities in absolute terms, including absolute free energies and absolute entropies. NS has been used predominately to compute the canonical (NVT) partition function. Although NS has recently been used to obtain the isothermal-isobaric (NPT) partition function of the hard sphere model, a general approach to the computation of the NPT partition function has yet to be developed. Here, we describe an isobaric NS (IBNS) method which allows for the computation of the NPT partition function of any atomic system. We demonstrate IBNS on two finite Lennard-Jones systems and confirm the results through comparison to parallel tempering Monte Carlo. Temperature-entropy plots are constructed as well as a simple pressure-temperature phase diagram for each system. We further demonstrate IBNS by computing part of the pressure-temperature phase diagram of a Lennard-Jones system under periodic boundary conditions.

Thermodynamics and structure of macromolecules from flat-histogram Monte Carlo simulations

Over the last decade flat-histogram Monte Carlo simulations, especially multi-canonical and Wang-Landau simulations, have emerged as a strong tool to study the statistical mechanics of polymer chains. These investigations have focused on coarse-grained models of polymers on the lattice and in the continuum. Phase diagrams of chains in bulk as well as chains attached to surfaces were studied, for homopolymers as well as for protein-like models. Also, aggregation behavior in solution of these models has been investigated. We will present here the theoretical background for these simulations, explain the algorithms used and discuss their performance and give an overview over the systems studied with these methods in the literature, where we will limit ourselves to studies of coarse-grained model systems. Implementations of these algorithms on parallel computers will be also briefly described. In parallel to the development of these simulation methods, the power of a micro-canonical analysis of such simulations has been recognized, and we present the current state of the art in applying the micro-canonical analysis to phase transitions in nanoscopic polymer systems.

An Analysis of Biomolecular Force Fields for Simulations of Polyglutamine in Solution

Polyglutamine (polyQ) peptides are a useful model system for biophysical studies of protein folding and aggregation, both for their intriguing aggregation properties and their own relevance to human disease. The genetic expansion of a polyQ tract triggers the formation of amyloid aggregates associated with nine neurodegenerative diseases. Several clearly identifiable and separable factors, notably the length of the polyQ tract, influence the mechanism of aggregation, its associated kinetics, and the ensemble of structures formed. Atomistic simulations are well positioned to answer open questions regarding the thermodynamics and kinetics of polyQ folding and aggregation. The additional, explicit representation of water permits deeper investigation of the role of solvent dynamics, and it permits a direct comparison of simulation results with infrared spectroscopy experiments. The generation of meaningful simulation results hinges on satisfying two essential criteria: achieving sufficient conformational sampling to draw statistically valid conclusions, and accurately reproducing the intermolecular forces that govern system structure and dynamics. In this work, we examine the ability of 12 biomolecular force fields to reproduce the properties of a simple, 30-residue polyQ peptide (Q30) in explicit water. In addition to secondary and tertiary structure, we consider generic structural properties of polymers that provide additional dimensions for analysis of the highly degenerate disordered states of the molecule. We find that the 12 force fields produce a wide range of predictions. We identify AMBER ff99SB, AMBER ff99SB*, and OPLS-AA/L to be most suitable for studies of polyQ folding and aggregation.

First-order phase transition and tricritical scaling behavior of the Blume-Capel model: A Wang-Landau sampling approach

We investigate the tricritical scaling behavior of the two-dimensional spin-1 Blume-Capel model by using the Wang-Landau method of measuring the joint density of states for lattice sizes up to 48×48 sites. We find that the specific heat deep in the first-order area of the phase diagram exhibits a double-peak structure of the Schottky-like anomaly appearing with the transition peak. The first-order transition curve is systematically determined by employing the method of field mixing in conjunction with finite-size scaling, showing a significant deviation from the previous data points. At the tricritical point, we characterize the tricritical exponents through finite-size-scaling analysis including the phenomenological finite-size scaling with thermodynamic variables. Our estimation of the tricritical eigenvalue exponents, yt=1.804(5), yg=0.80(1), and yh=1.925(3), provides the first Wang-Landau verification of the conjectured exact values, demonstrating the effectiveness of the density-of-states-based approach in finite-size scaling study of multicritical phenomena.

Secondary Structure of Rat and Human Amylin across Force Fields

The aggregation of human amylin has been strongly implicated in the progression of Type II diabetes. This 37-residue peptide forms a variety of secondary structures, including random coils, α-helices, and β-hairpins. The balance between these structures depends on the chemical environment, making amylin an ideal candidate to examine inherent biases in force fields. Rat amylin differs from human amylin by only 6 residues; however, it does not form fibrils. Therefore it provides a useful complement to human amylin in studies of the key events along the aggregation pathway. In this work, the free energy of rat and human amylin was determined as a function of α-helix and β-hairpin content for the Gromos96 53a6, OPLS-AA/L, CHARMM22/CMAP, CHARMM22*, Amberff99sb*-ILDN, and Amberff03w force fields using advanced sampling techniques, specifically bias exchange metadynamics. This work represents a first systematic attempt to evaluate the conformations and the corresponding free energy of a large, clinically relevant disordered peptide in solution across force fields. The NMR chemical shifts of rIAPP were calculated for each of the force fields using their respective free energy maps, allowing us to quantitatively assess their predictions. We show that the predicted distribution of secondary structures is sensitive to the choice of force-field: Gromos53a6 is biased towards β-hairpins, while CHARMM22/CMAP predicts structures that are overly α-helical. OPLS-AA/L favors disordered structures. Amberff99sb*-ILDN, AmberFF03w and CHARMM22* provide the balance between secondary structures that is most consistent with available experimental data. In contrast to previous reports, our findings suggest that the equilibrium conformations of human and rat amylin are remarkably similar, but that subtle differences arise in transient alpha-helical and beta-strand containing structures that the human peptide can more readily adopt. We hypothesize that these transient states enable dynamic pathways that facilitate the formation of aggregates and, eventually, amyloid fibrils.

The liquid-liquid transition in supercooled ST2 water: a comparison between umbrella sampling and well-tempered metadynamics

We investigate the metastable phase behaviour of the ST2 water model under deeply supercooled conditions. The phase behaviour is examined using umbrella sampling (US) and well-tempered metadynamics (WT-MetaD) simulations to compute the reversible free energy surface parameterized by density and bond-orientation order. We find that free energy surfaces computed with both techniques clearly show two liquid phases in coexistence, in agreement with our earlier US and grand canonical Monte Carlo calculations [Y. Liu, J. C. Palmer, A. Z. Panagiotopoulos and P. G. Debenedetti, J Chem Phys, 2012, 137, 214505; Y. Liu, A. Z. Panagiotopoulos and P. G. Debenedetti, J Chem Phys, 2009, 131, 104508]. While we demonstrate that US and WT-MetaD produce consistent results, the latter technique is estimated to be more computationally efficient by an order of magnitude. As a result, we show that WT-MetaD can be used to study the finite-size scaling behaviour of the free energy barrier separating the two liquids for systems containing 192, 300 and 400 ST2 molecules. Although our results are consistent with the expected N(2/3) scaling law, we conclude that larger systems must be examined to provide conclusive evidence of a first-order phase transition and associated second critical point.

A molecular simulation protocol to avoid sampling redundancy and discover new states

BACKGROUND

For biomacromolecules or their assemblies, experimental knowledge is often restricted to specific states. Ambiguity pervades simulations of these complex systems because there is no prior knowledge of relevant phase space domains, and sampling recurrence is difficult to achieve. In molecular dynamics methods, ruggedness of the free energy surface exacerbates this problem by slowing down the unbiased exploration of phase space. Sampling is inefficient if dwell times in metastable states are large.

METHODS

We suggest a heuristic algorithm to terminate and reseed trajectories run in multiple copies in parallel. It uses a recent method to order snapshots, which provides notions of "interesting" and "unique" for individual simulations. We define criteria to guide the reseeding of runs from more "interesting" points if they sample overlapping regions of phase space.

RESULTS

Using a pedagogical example and an α-helical peptide, the approach is demonstrated to amplify the rate of exploration of phase space and to discover metastable states not found by conventional sampling schemes. Evidence is provided that accurate kinetics and pathways can be extracted from the simulations.

CONCLUSIONS

The method, termed PIGS for Progress Index Guided Sampling, proceeds in unsupervised fashion, is scalable, and benefits synergistically from larger numbers of replicas. Results confirm that the underlying ideas are appropriate and sufficient to enhance sampling.

GENERAL SIGNIFICANCE

In molecular simulations, errors caused by not exploring relevant domains in phase space are always unquantifiable and can be arbitrarily large. Our protocol adds to the toolkit available to researchers in reducing these types of errors. This article is part of a Special Issue entitled "Recent developments of molecular dynamics".

Practical Aspects of Free-Energy Calculations: A Review

Free-energy calculations in the framework of classical molecular dynamics simulations are nowadays used in a wide range of research areas including solvation thermodynamics, molecular recognition, and protein folding. The basic components of a free-energy calculation, that is, a suitable model Hamiltonian, a sampling protocol, and an estimator for the free energy, are independent of the specific application. However, the attention that one has to pay to these components depends considerably on the specific application. Here, we review six different areas of application and discuss the relative importance of the three main components to provide the reader with an organigram and to make nonexperts aware of the many pitfalls present in free energy calculations.

An experimentally-informed coarse-grained 3-Site-Per-Nucleotide model of DNA: structure, thermodynamics, and dynamics of hybridization

A new 3-Site-Per-Nucleotide coarse-grained model for DNA is presented. The model includes anisotropic potentials between bases involved in base stacking and base pair interactions that enable the description of relevant structural properties, including the major and minor grooves. In an improvement over available coarse-grained models, the correct persistence length is recovered for both ssDNA and dsDNA, allowing for simulation of non-canonical structures such as hairpins. DNA melting temperatures, measured for duplexes and hairpins by integrating over free energy surfaces generated using metadynamics simulations, are shown to be in quantitative agreement with experiment for a variety of sequences and conditions. Hybridization rate constants, calculated using forward-flux sampling, are also shown to be in good agreement with experiment. The coarse-grained model presented here is suitable for use in biological and engineering applications, including nucleosome positioning and DNA-templated engineering.

Molecular Dynamics in the Multicanonical Ensemble: Equivalence of Wang-Landau Sampling, Statistical Temperature Molecular Dynamics, and Metadynamics

We show a direct formal relationship between the Wang-Landau iteration [PRL 86, 2050 (2001)], metadynamics [PNAS 99, 12562 (2002)], and statistical temperature molecular dynamics (STMD) [PRL 97, 050601 (2006)] that are the major work-horses for sampling from generalized ensembles. We demonstrate that STMD, itself derived from the Wang-Landau method, can be made indistinguishable from metadynamics. We also show that Gaussian kernels significantly improve the performance of STMD, highlighting the practical benefits of this improved formal understanding.

Measuring liquid crystal elastic constants with free energy perturbations

A first principles method is proposed to calculate the Frank elastic constants of nematic liquid crystals. These include the constants corresponding to standard splay, twist and bend deformations, and an often-ignored surface-like contribution known as saddle-splay. The proposed approach is implemented on the widely studied Gay-Berne (3, 5, 2, 1) model [J. G. Gay and B. J. Berne, J. Chem. Phys., 1981, 74, 3316], and the effects of temperature and system size on the elastic constants are examined in the nematic phase. The results of simulations for splay, twist, and bend elastic constants are consistent with those from previous literature reports. The method is subsequently applied to the saddle-splay elastic constant k24 which is found to exist at the limits of the Ericksen inequalities governing positive definite free energy. Finally, extensions of the method are discussed that present a new paradigm for in silico measurements of elastic constants.

Liquid-crystal mediated nanoparticle interactions and gel formation

Colloidal particles embedded within nematic liquid crystals exhibit strong anisotropic interactions arising from preferential orientation of nematogens near the particle surface. Such interactions are conducive to forming branched, gel-like aggregates. Anchoring effects also induce interactions between colloids dispersed in the isotropic liquid phase, through the interactions of the pre-nematic wetting layers. Here we utilize computer simulation using coarse-grained mesogens to perform a molecular-level calculation of the potential of mean force between two embedded nanoparticles as a function of anchoring for a set of solvent conditions straddling the isotropic-nematic transition. We observe that strong, nontrivial interactions can be induced between particles dispersed in mesogenic solvent, and explore how such interactions might be utilized to induce a gel state in the isotropic and nematic phases.

Nematic-field-driven positioning of particles in liquid crystal droplets

Common nematic oils, such as 5CB, experience planar anchoring at aqueous interfaces. When these oils are emulsified, this anchoring preference and the resulting topological constraints lead to the formation of droplets that exhibit one or two point defects within the nematic phase. Here, we explore the interactions of adsorbed particles at the aqueous interface through a combination of experiments and coarse-grained modeling, and demonstrate that surface-active particles, driven by elastic forces in the droplet, readily localize to these defect regions in a programmable manner. When droplets include two nanoparticles, these preferentially segregate to the two poles, thereby forming highly regular dipolar structures that could serve for hierarchical assembly of functional structures. Addition of sufficient concentrations of surfactant changes the interior morphology of the droplet, but pins defects to the interface, resulting in aggregation of the two particles.

Effect of proline mutations on the monomer conformations of amylin

The formation of human islet amyloid polypeptide (hIAPP) is implicated in the loss of pancreatic β-cells in type II diabetes. Rat amylin, which differs from human amylin at six residues, does not lead to formation of amyloid fibrils. Pramlintide is a synthetic analog of human amylin that shares three proline substitutions with rat amylin. Pramlintide has a much smaller propensity to form amyloid aggregates and has been widely prescribed in amylin replacement treatment. It is known that the three prolines attenuate β-sheet formation. However, the detailed effects of these proline substitutions on full-length hIAPP remain poorly understood. In this work, we use molecular simulations and bias-exchange metadynamics to investigate the effect of proline substitutions on the conformation of the hIAPP monomer. Our results demonstrate that hIAPP can adopt various β-sheet conformations, some of which have been reported in experiments. The proline substitutions perturb the formation of long β-sheets and reduce their stability. More importantly, we find that all three proline substitutions of pramlintide are required to inhibit β conformations and stabilize the α-helical conformation. Fewer substitutions do not have a significant inhibiting effect.

Adenosine triphosphate hydrolysis mechanism in kinesin studied by combined quantum-mechanical/molecular-mechanical metadynamics simulations

Kinesin is a molecular motor that hydrolyzes adenosine triphosphate (ATP) and moves along microtubules against load. While motility and atomic structures have been well-characterized for various members of the kinesin family, not much is known about ATP hydrolysis inside the active site. Here, we study ATP hydrolysis mechanisms in the kinesin-5 protein Eg5 by using combined quantum mechanics/molecular mechanics metadynamics simulations. Approximately 200 atoms at the catalytic site are treated by a dispersion-corrected density functional and, in total, 13 metadynamics simulations are performed with their cumulative time reaching ~0.7 ns. Using the converged runs, we compute free energy surfaces and obtain a few hydrolysis pathways. The pathway with the lowest free energy barrier involves a two-water chain and is initiated by the Pγ-Oβ dissociation concerted with approach of the lytic water to PγO3-. This immediately induces a proton transfer from the lytic water to another water, which then gives a proton to the conserved Glu270. Later, the proton is transferred back from Glu270 to HPO(4)2- via another hydrogen-bonded chain. We find that the reaction is favorable when the salt bridge between Glu270 in switch II and Arg234 in switch I is transiently broken, which facilitates the ability of Glu270 to accept a proton. When ATP is placed in the ADP-bound conformation of Eg5, the ATP-Mg moiety is surrounded by many water molecules and Thr107 blocks the water chain, which together make the hydrolysis reaction less favorable. The observed two-water chain mechanisms are rather similar to those suggested in two other motors, myosin and F1-ATPase, raising the possibility of a common mechanism.

α-helix to β-hairpin transition of human amylin monomer

The human islet amylin polypeptide is produced along with insulin by pancreatic islets. Under some circumstances, amylin can aggregate to form amyloid fibrils, whose presence in pancreatic cells is a common pathological feature of Type II diabetes. A growing body of evidence indicates that small, early stage aggregates of amylin are cytotoxic. A better understanding of the early stages of the amylin aggregation process and, in particular, of the nucleation events leading to fibril growth could help identify therapeutic strategies. Recent studies have shown that, in dilute solution, human amylin can adopt an α-helical conformation, a β-hairpin conformation, or an unstructured coil conformation. While such states have comparable free energies, the β-hairpin state exhibits a large propensity towards aggregation. In this work, we present a detailed computational analysis of the folding pathways that arise between the various conformational states of human amylin in water. A free energy surface for amylin in explicit water is first constructed by resorting to advanced sampling techniques. Extensive transition path sampling simulations are then employed to identify the preferred folding mechanisms between distinct minima on that surface. Our results reveal that the α-helical conformer of amylin undergoes a transformation into the β-hairpin monomer through one of two mechanisms. In the first, misfolding begins through formation of specific contacts near the turn region, and proceeds via a zipping mechanism. In the second, misfolding occurs through an unstructured coil intermediate. The transition states for these processes are identified. Taken together, the findings presented in this work suggest that the inter-conversion of amylin between an α-helix and a β-hairpin is an activated process and could constitute the nucleation event for fibril growth.

Isotropic-nematic phase transition in the Lebwohl-Lasher model from density of states simulations

Density of states Monte Carlo simulations have been performed to study the isotropic-nematic (IN) transition of the Lebwohl-Lasher model for liquid crystals. The IN transition temperature was calculated as a function of system size using expanded ensemble density of states simulations with histogram reweighting. The IN temperature for infinite system size was obtained by extrapolation of three independent measures. A subsequent analysis of the kinetics in the model showed that the transition occurs via spinodal decomposition through aggregation of clusters of liquid crystal molecules.