Classical Molecular Simulations Research Articles

Vapour–liquid equilibrium using quantum chemical molecular dynamics simulation and radial distribution function analysis

AbstractInstead of the classical molecular simulation widely implemented for estimating the vapour–liquid equilibrium (VLE), a quantum chemical (QC) molecular dynamics simulation was applied to the VLE estimation in three typical systems that include a deep eutectic solvent (DES) and an ionic liquid (IL). In addition, a radial distribution function (RDF) was derived from the QC simulation to examine the molecular behaviour in the liquid phase. A mean absolute error of 2.72% was obtained from the QC simulation compared to the experimental data. The RDF analysis explains the relative volatility increase of the acetic acid and water binary system with the propyl acetate solvent. This analysis indicated that the DES mixture comprising glycerol and choline chloride facilitated the separation of water and i‐propanol. The interaction between water and ethyl sulphate pair with the help of 1‐ethyl‐3‐methylimidazolium as an IL is stronger than that between ethanol and water, which explains how the IL improves ethanol and water separation in the vapour phase.

The structural and electronic configuration of an amorphous silica surface, from its liquid to glassy state

Through classical molecular dynamics computational simulations, the surface of amorphous silica (vitreous silica) was generated for a system comprising 64 SiO2 molecules (192 atoms) via the classical three-body glass potential. Starting from the liquid state of silica at 3400 K, it was cooled in three different ways at intervals of 200, 400, and 2000 K, with a cooling rate of 4.4 K/ps and establishing relaxation at intermediate temperatures, yielding three groups of surfaces from 3400 to 1400 K. Subsequently, these systems underwent sudden cooling from 1400 to 300 K via the Andersen and Nosé‒Hoover thermostats, followed by relaxation at 300 K via a microcanonical ensemble (NVE constant). Each surface that underwent relaxation was analyzed through ab initio molecular dynamics for the following three physical properties, which are temperature dependent. The average electric charges of oxygen and silicon. Microstructures on the outermost part of the surface were observed and comprised nonbridging oxygen atoms, undercoordinated silicon, and N-membered rings (3 ≤ N ≤ 5). The radial distribution functions were analyzed for all surfaces. Below 2000 K, a type of freezing is observed in all the structures because of the glass transition. All analyses were performed at zero pressure.

Prediction of Thermochemical Properties of Long-Chain Alkanes Using Linear Regression: Application to Hydroisomerization.

Linear regression (LR) is used to predict thermochemical properties of alkanes at temperatures (0-1000) K to study chemical reaction equilibria inside zeolites. The thermochemical properties of C1 until C10 isomers reported by Scott are used as training data sets in the LR model which is used to predict these properties for alkanes longer than C10 isomers. Second-order groups are used as independent variables which account for the interactions between the neighboring groups of atoms. This model accurately predicts Gibbs free energies, enthalpies, Gibbs free energies of formation, and enthalpies of formation for alkanes which exceeds the chemical accuracy of 1 kcal/mol and outperforms the group contribution methods developed by Benson et al., Joback and Reid, and Constantinou and Gani. Predictions from our model are used to compute the reaction equilibrium distribution of hydroisomerization of C10 and C14 isomers in MTW-type zeolite. Calculation of reaction equilibrium distribution inside zeolites also requires Henry coefficients of the isomers which can be computed using classical force field-based molecular simulations using the RASPA2 software for which we created an automated workflow. The reaction equilibrium distribution for C10 isomers obtained using the LR model and the training data set for this model are in very good agreement. The tools developed in this study will enable the computational study of hydroisomerization of long-chain alkanes (>C10).

A molecular simulation study on pore-scale behaviour of nitrogen-based fracking fluids for potential geo-energy applications

Molecular simulations are efficient tools in differentiating individual effects of fluid-fluid interactions and pore-fluid interactions on thermophysical properties of confined fluids; e.g. the molecular packing, adsorption mechanics and availability of accessible pore volume for confined fluids and therefore, indicate the rock fracturing phenomena as a function of geological conditions, fracking fluids nature, its composition and rock mineralogy. Presently, we have deployed the classical GCMC molecular simulations to quantify the adsorption of pure nitrogen and N2–H2O mixture (50%–50% and 30%–70%) inside porous silica rocks. While we found that adsorption and molecular packing of pure nitrogen inside silica slit pores are only a function of pore height, which quantifies the pore-fluid interactions; however, for N2–H2O mixture adsorption and molecular packing of N2 inside silica slit pores has been additionally affected by the water content in the equilibrium bulk mixture that as well describes fluid-fluid interactions inside pores. It is interestingly noted that water in N2–H2O mixture results in water-assisted nitrogen adsorption inside hydrophilic silica slit pores, which has been further proven through the radial distribution function data calculations inside each slit pore. Also, the hydrophilic nature of silica increases water adsorption and hence reduces N2 adsorption inside the smallest pore of H = 20 Å. Such a reduction in N2 adsorption density below its bulk density without layering effect, inside 20 Å pore, further initiates the possibility of negative excess adsorption density.

Molecular dynamics simulations for the prediction of thermophysical properties of plutonium-based molten salts

Molten salt nuclear reactors are promising technologies for sustainable energy sources. In this context, understanding the physicochemical properties of molten salts is essential to the development, usage, and maintenance of reactors. Classical molecular simulations allow estimating the macroscopic properties of molten salts at a relatively low computational cost. In this work, we develop a new force field for plutonium-based molten salts. We validate our classical model by comparing molecular dynamics results with experimental measurements, obtaining a quantitative agreement. Our work demonstrates the reliability and transferability of classical force fields to represent the physicochemical properties of molten salts.

Proton-coupled electron transfer dynamics in the alternative oxidase.

The alternative oxidase (AOX) is a membrane-bound di-iron enzyme that catalyzes O2-driven quinol oxidation in the respiratory chains of plants, fungi, and several pathogenic protists of biomedical and industrial interest. Yet, despite significant biochemical and structural efforts over the last decades, the catalytic principles of AOX remain poorly understood. We develop here multi-scale quantum and classical molecular simulations in combination with biochemical experiments to address the proton-coupled electron transfer (PCET) reactions responsible for catalysis in AOX from Trypanosoma brucei, the causative agent of sleeping sickness. We show that AOX activates and splits dioxygen via a water-mediated PCET reaction, resulting in a high-valent ferryl/ferric species and tyrosyl radical (Tyr220˙) that drives the oxidation of the quinol via electric field effects. We identify conserved carboxylates (Glu215, Asp100) within a buried cluster of ion-pairs that act as a transient proton-loading site in the quinol oxidation process, and validate their function experimentally with point mutations that result in drastic activity reduction and pK a-shifts. Our findings provide a key mechanistic understanding of the catalytic machinery of AOX, as well as a molecular basis for rational drug design against energy transduction chains of parasites. On a general level, our findings illustrate how redox-triggered conformational changes in ion-paired networks control the catalysis via electric field effects.

Electrochemical rewiring through quantum conductance effects in single metallic memristive nanowires.

Memristive devices have been demonstrated to exhibit quantum conductance effects at room temperature. In these devices, a detailed understanding of the relationship between electrochemical processes and ionic dynamic underlying the formation of atomic-sized conductive filaments and corresponding electronic transport properties in the quantum regime still represents a challenge. In this work, we report on quantum conductance effects in single memristive Ag nanowires (NWs) through a combined experimental and simulation approach that combines advanced classical molecular dynamics (MD) algorithms and quantum transport simulations (DFT). This approach provides new insights on quantum conductance effects in memristive devices by unravelling the intrinsic relationship between electronic transport and atomic dynamic reconfiguration of the nanofilment, by shedding light on deviations from integer multiples of the fundamental quantum of conductance depending on peculiar dynamic trajectories of nanofilament reconfiguration and on conductance fluctuations relying on atomic rearrangement due to thermal fluctuations.

A new computational methodology for the characterization of complex molecular environments using IR spectroscopy: bridging the gap between experiments and computations.

The molecular interactions and dynamics of complex liquid solutions are now routinely measured using IR and 2DIR spectroscopy. In particular, the use of the latter allows the determination of the frequency fluctuation correlation function (FFCF), while the former provides us with the average frequency. In turn, the FFCF can be used to quantify the vibrational dynamics of a molecule in a solution, and the center frequency provides details about the chemical environment, solvatochromism, of the vibrational mode. In simple solutions, the IR methodology can be used to unambiguously assign the interactions and dynamics observed by a molecule in solution. However, in complex environments with molecular heterogeneities, this assignment is not simple. Therefore, a method that allows for such an assignment is essential. Here, a parametrization free method, called Instantaneous Frequencies of Molecules or IFM, is presented. The IFM method, when coupled to classical molecular simulations, can predict the FFCF of a molecule in solutions. Here, N-methylacetamide (NMA) in seven different chemical environments, both simple and complex, is used to test this new method. The results show good agreement with experiments for the NMA solvatochromism and FFCF dynamics, including characteristic times and amplitudes of fluctuations. In addition, the new method shows equivalent or improved results when compared to conventional frequency maps. Overall, the use of the new method in conjunction with molecular dynamics simulations allows unlocking the full potential of IR spectroscopy to generate molecular maps from vibrational observables, capable of describing the interaction landscape of complex molecular systems.

Accessible Molecular System Creator: Building Molecular Configurations Based on the Inaccessible Molecular Volume and Accessible Molecular Surface via Static Monte Carlo Sampling.

Monte Carlo (MC) stochastic sampling is a powerful tool in classical molecular simulations that directly connects the observable macroscopic properties of matter and the underlying atomistic interactions. This connection operates within the framework of the statistical mechanics proposed by Gibbs. Most MC simulations are "dynamic," creating statistical ensembles of microstates via a Markovian chain, where each microstate in the ensemble depends only on its previous microstate. Herein, we re-examine an alternative form of MC that generates ensemble members through a "static" approach, building molecular systems stepwise. The basic theory for such an approach traces back to Rosenbluth and Rosenbluth, who proposed "static" stepwise sampling of a polymeric chain. It is almost as old as the Metropolis importance sampling approach used in dynamic MC, although the latter has been considerably more popular than the former. Herein, we address the main obstacle in static MC that has hindered the widespread adoption of Rosenbluth-based approaches in atomistic simulations. The obstacle lies in mapping the molecular accessible volume for adding a molecule in a Rosenbluth-like static sampling of atomistic configurations. We demonstrate a breakthrough by leveraging the ability to analytically map the inaccessible molecular volume and the accessible molecular surface owing to interatomically excluded volume interactions. This advance substantially enhances the ability to create molecular samples using a Rosenbluth-like static building process. The proposed approach can be used as a tool for creating initial configurations in MC or molecular dynamics simulations─a field where Rosenbluth-like static building has been applied. Additionally, this approach can be used as the first step in a perturbation scheme that accurately estimates free energy differences by estimating the chemical work related to molecule addition, removal, or reinsertion within the context of free energy perturbation schemes employed in molecular simulations.

MBX: A many-body energy and force calculator for data-driven many-body simulations.

Many-Body eXpansion (MBX) is a C++ library that implements many-body potential energy functions (PEFs) within the "many-body energy" (MB-nrg) formalism. MB-nrg PEFs integrate an underlying polarizable model with explicit machine-learned representations of many-body interactions to achieve chemical accuracy from the gas to the condensed phases. MBX can be employed either as a stand-alone package or as an energy/force engine that can be integrated with generic software for molecular dynamics and Monte Carlo simulations. MBX is parallelized internally using Open Multi-Processing and can utilize Message Passing Interface when available in interfaced molecular simulation software. MBX enables classical and quantum molecular simulations with MB-nrg PEFs, as well as hybrid simulations that combine conventional force fields and MB-nrg PEFs, for diverse systems ranging from small gas-phase clusters to aqueous solutions and molecular fluids to biomolecular systems and metal-organic frameworks.

Interaction of Nitrite Ions with Hydrated Portlandite Surfaces: Atomistic Computer Simulation Study.

The nitrite admixtures in cement and concrete are used as corrosion inhibitors for steel reinforcement and also as anti-freezing agents. The characterization of the protective properties should account for the decrease in the concentration of free NO2- ions in the pores of cement concretes due to their adsorption. Here we applied the classical molecular dynamics computer simulation approach to quantitatively study the molecular scale mechanisms of nitrite adsorption from NaNO2 aqueous solution on a portlandite surface. We used a new parameterization to model the hydrated NO2- ions in combination with the recently upgraded ClayFF force field (ClayFF-MOH) for the structure of portlandite. The new NO2- parameterization makes it possible to reproduce the properties of hydrated NO2- ions in good agreement with experimental data. In addition, the ClayFF-MOH model improves the description of the portlandite structure by explicitly taking into account the bending of Ca-O-H angles in the crystal and on its surface. The simulations showed that despite the formation of a well-structured water layer on the portlandite (001) crystal surface, NO2- ions can be strongly adsorbed. The nitrite adsorption is primarily due to the formation of hydrogen bonds between the structural hydroxyls on the portlandite surface and both the nitrogen and oxygen atoms of the NO2- ions. Due to that, the ions do not form surface adsorption complexes with a single well-defined structure but can assume various local coordinations. However, in all cases, the adsorbed ions did not show significant surface diffusional mobility. Moreover, we demonstrated that the nitrite ions can be adsorbed both near the previously-adsorbed hydrated Na+ ions as surface ion pairs, but also separately from the cations.

Molecular simulations of alkali metal halide hydrates

It has been known that classical molecular simulations of concentrated aqueous electrolyte solutions are limited by the ability of microscopic models (force fields) to predict the correct values of salt solubility, which also requires their ability to faithfully model crystalline salts. Previous simulation studies have often focused on the solubility of anhydrous crystalline salts, but virtually never on crystalline hydrates, except for hydrohalite, NaCl⋅2H2O, despite there are at least 23 experimentally known different hydrates that can precipitate from alkali-halide solutions. This work attempts to fill this gap in hydrate simulation studies by systematically investigating the ability of the best force fields selected to qualitatively capture the stability of the individual phases of various alkali-halide hydrates and to quantitatively predict their lattice parameters. First, we show that the nonpolarizable force fields studied often fail to model hydrates containing the Li+ cations, whereas the polarizable force fields recently refined by us are able to model all the hydrates except for LiCl⋅H2O. Second, we further refine our FFs for Li+ to yield stable LiCl⋅H2O. Third, our simulations clarify the positions of the Li+ cations in the β phases of LiBr⋅H2O and LiI⋅H2O, whose distributions were previously described only as stochastic. As a byproduct, a simple and reliable simulation methodology suitable also for complex polarizable models and nonorthorhombic crystal lattices is proposed and tested, based on simulations of finite crystals floating in vacuum.

Disulfide bond reduction and exchange in C4 domain of von Willebrand factor undermines platelet binding

BackgroundThe von Willebrand factor (VWF) is a key player in regulating hemostasis through adhesion of platelets to sites of vascular injury. It is a large, multi-domain, mechano-sensitive protein that is stabilized by a net of disulfide bridges. Binding to platelet integrin is achieved by the VWF-C4 domain, which exhibits a fixed fold, even under conditions of severe mechanical stress, but only if critical internal disulfide bonds are closed. ObjectiveTo determine the oxidation state of disulfide bridges in the C4 domain of VWF and implications for VWF’s platelet binding function. MethodsWe combined classical molecular dynamics and quantum mechanical simulations, mass spectrometry, site-directed mutagenesis, and platelet binding assays. ResultsWe show that 2 disulfide bonds in the VWF-C4 domain, namely the 2 major force-bearing ones, are partially reduced in human blood. Reduction leads to pronounced conformational changes within C4 that considerably affect the accessibility of the integrin-binding motif, and thereby impair integrin-mediated platelet binding. We also reveal that reduced species in the C4 domain undergo specific thiol/disulfide exchanges with the remaining disulfide bridges, in a process in which mechanical force may increase the proximity of specific reactant cysteines, further trapping C4 in a state of low integrin-binding propensity. We identify a multitude of redox states in all 6 VWF-C domains, suggesting disulfide bond reduction and swapping to be a general theme. ConclusionsOur data suggests a mechanism in which disulfide bonds dynamically swap cysteine partners and control the interaction of VWF with integrin and potentially other partners, thereby critically influencing its hemostatic function.

Gmak: A Parameter-Space Mapping Strategy for Force-Field Calibration.

In the context of classical molecular simulations, the accuracy of a force field is highly influenced by the values of the relevant simulation parameters. In this work, a parameter-space mapping (PSM) workflow is proposed to aid in the calibration of force-field parameters, based mainly on the following features: (i) regular-grid discretization of the search space; (ii) partial sampling of the search-space grid; (iii) training of surrogate models to predict the estimates of the target properties for nonsampled parameter sets; (iv) post hoc interpretation of the results in terms of multiobjective optimization concepts; (v) attenuation of statistical errors achieved via empiric extension of the duration of the simulations; (vi) iterative search-space translation according to a user-defined scalar objective function that measures the accuracy of the force field (e.g., the weighted root-mean-square deviation of the target properties relative to the reference data). This combination of features results in a hybrid of a single- and a multiobjective optimization strategy, allowing for the approximate determination of both a local minimum of the chosen objective function and its neighboring Pareto efficient points. The PSM workflow is implemented in the extensible Python program gmak, which is made available in the Git repository at http://github.com/mssm-labmmol/gmak. Using this implementation, the PSM workflow was tested in a proof-of-concept fashion in the recalibration of the Lennard-Jones parameters of the 3-point Optimal Point Charge (OPC3) water model for compatibility with the GROMOS treatment of nonbonded interactions. The recalibrated model reproduces typical pure-liquid properties with an accuracy similar to the original OPC3 model and represents a significant improvement relative to the Simple Point Charge (SPC) model, which is the official recommendation for simulations using GROMOS force fields.

Investigation of the Second Harmonic Generation at the Water-Vacuum Interface by Using Multi-Scale Modeling Methods.

Invited for this month's cover picture are Dr. Tárcius N. Ramos and Prof. Benoît Champagne at the University of Namur (Belgium). The cover picture shows the interfacial selectivity of second harmonic generation at the water-vacuum interface, which is targeted in this work. In more details, the molecular first hyperpolarizability responses have been calculated by combining classical molecular dynamics and quantum chemistry simulations, and our model was able to distinguish between the bulk and the interfacial contributions. Read the full text of their Research Article at 10.1002/open.202200045.

Collaborative Assessment of Molecular Geometries and Energies from the Open Force Field.

Force fields form the basis for classical molecular simulations, and their accuracy is crucial for the quality of, for instance, protein-ligand binding simulations in drug discovery. The huge diversity of small-molecule chemistry makes it a challenge to build and parameterize a suitable force field. The Open Force Field Initiative is a combined industry and academic consortium developing a state-of-the-art small-molecule force field. In this report, industry members of the consortium worked together to objectively evaluate the performance of the force fields (referred to here as OpenFF) produced by the initiative on a combined public and proprietary dataset of 19,653 relevant molecules selected from their internal research and compound collections. This evaluation was important because it was completely blind; at most partners, none of the molecules or data were used in force field development or testing prior to this work. We compare the Open Force Field "Sage" version 2.0.0 and "Parsley" version 1.3.0 with GAFF-2.11-AM1BCC, OPLS4, and SMIRNOFF99Frosst. We analyzed force-field-optimized geometries and conformer energies compared to reference quantum mechanical data. We show that OPLS4 performs best, and the latest Open Force Field release shows a clear improvement compared to its predecessors. The performance of established force fields such as GAFF-2.11 was generally worse. While OpenFF researchers were involved in building the benchmarking infrastructure used in this work, benchmarking was done entirely in-house within industrial organizations and the resulting assessment is reported here. This work assesses the force field performance using separate benchmarking steps, external datasets, and involving external research groups. This effort may also be unique in terms of the number of different industrial partners involved, with 10 different companies participating in the benchmark efforts.

Prenucleation at the Liquid/Substrate Interface: An Overview

Prenucleation refers to the phenomenon of substrate-induced atomic ordering in the liquid adjacent to the liquid/substrate interface at temperatures above the nucleation temperature. We investigated the effects of the physical and chemical properties of the substrate on prenucleation, using the classical molecular dynamics (MD) and ab initio MD simulations. We found that the physical origin of prenucleation is structural templating, which is affected significantly by the lattice misfit between the solid and the substrate, chemical interaction between the solid and the substrate, and the substrate surface roughness at the atomic level. Prenucleation ultimately determines the nucleation potency of a substrate and provides a precursor for heterogeneous nucleation at the nucleation temperature. In this paper, we provide an overview of the recent advances in the understanding of prenucleation made by the LiME Research Hub. After a brief review of the historical research on atomic ordering at the liquid/substrate interface in the literature, we present an overview of the recent advances in understanding prenucleation, covering the concept of prenucleation, the effect of temperature, lattice misfit and substrate chemistry, and substrate surface roughness at the atomic level. Our discussions will be focused on the effect of prenucleation on heterogeneous nucleation and its consequences on grain refinement.

Atomistic Mismatch Defines Energy-Structure Relationships during Oriented Attachment of Nanoparticles.

Oriented attachment is an important crystal growth pathway in nature and has been extensively exploited to develop hierarchically structured crystalline materials. Atomistic mismatch in the crystal structure of two particles in the solvent-separated state creates forces that drive particle motions enabling solvent expulsion and coalescence, but the relative magnitudes of the energy barriers for approach, rotation, and translation are not well-known. Here we use classical molecular simulations to calculate the potential of mean force for these three different motions for basal surface encounters of gibbsite nanoplatelets separated by one water layer. In all cases, the highest energy barrier is associated with removing this last water layer to enable jump to contact, even when coaligned. Mutual rotation is more probable than sliding motion, which are both much more probable than jump to contact. This work provides the first comparison on an equal footing of the energy-structure relationships for multiple alignment paths between solvent-separated particles in bulk aqueous solution.

Novel Spiro-pyrrolizidine-Oxindole and Spiropyrrolidine-Oxindoles: Green synthesis under Classical, Ultrasonic, and microwave conditions and Molecular docking simulation for antitumor and type 2 diabetes

Novel spiropyrrolizine / pyrrolidineoxindole moieties were synthesized chemo-, and regio-selectively in high yields from knoevenagel reaction of bis[arylmethylidene]piperidin-4-ones, isatin and L-proline or sarcosine under classical, ultrasonic, and microwave conditions. Seven derivatives of the synthesized dispiro-pyrrolizidine-oxindole and spiropyrrolidine were screened for their antitumor activity against two cell lines MCF-7 (breast cancer) and HEPG2 (liver cancer). The results of biological activity indicated that the tested derivatives showed potent activity against breast cancer cell MCF-7. Molecular docking simulation screening studies of the synthesized products with each of the receptors of (3hb5) for breast cancer and (4k9g) for liver cancer and their interaction with 1H5U of glycogen phosphorylase B, type 2 diabetes drug were examined. The docking study of dispiro-pyrrolizidine-oxindole and spiropyrrolidine showed promising results with several derivatives.

VOC Mixture Sensing with a MOF Film Sensor Array: Detection and Discrimination of Xylene Isomers and Their Ternary Blends.

Detection and recognition of volatile organic compounds (VOCs) are crucial in many applications. While pure VOCs can be detected by various sensors, the discrimination of VOCs in mixtures, especially of similar molecules, is hindered by cross-sensitivities. Isomer identification in mixtures is even harder. Metal-organic frameworks (MOFs) with their well-defined, nanoporous, and versatile structures have the potential to improve the VOC sensing performance by tailoring the adsorption affinities. Here, we detect and identify ternary xylene isomer mixtures by using an array of six gravimetric, quartz crystal microbalance (QCM)-based sensors coated with selected MOF films with different isomer affinities. We use classical molecular simulations to provide insights into the sensing mechanism. In addition to the attractive interaction between the analytes and the MOF film, the isomer discrimination is caused by the rigid crystalline framework sterically controlling the access of the isomers to different adsorption sites in the MOFs. The sensor array has a very low limit of detection of 1 ppm for each pure isomer and allows the isomer discrimination in mixtures. At 100 ppm, 16 different ternary o-p-m-xylene mixtures were identified with high classification accuracy (96.5%). This work shows the unprecedented performance of MOF-sensor arrays, also referred to as MOF-electronic nose (MOF-e-nose), for sensing VOC mixtures. Based on the study, guidelines for detecting and discriminating complex mixtures of volatile molecules are also provided.