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Results for “Umbrella Sampling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Efficient Computation of Free Energy Surfaces of Diels–Alder Reactions in Explicit Solvent at Ab Initio QM/MM Level

For Diels–Alder (DA) reactions in solution, an accurate and converged free energy (FE) surface at ab initio (ai) quantum mechanical/molecular mechanical (QM/MM) level is imperative for the understanding of reaction mechanism. However, this computation is still far too expensive. In a previous work, we proposed a new method termed MBAR+wTP, with which the computation of the ai FE profile can be accelerated by several orders of magnitude via a three-step procedure: (I) an umbrella sampling (US) using a semi-empirical (SE) QM/MM Hamiltonian is performed; (II) the FE profile is generated using the Multistate Bennett Acceptance Ratio (MBAR) analysis; and (III) a weighted Thermodynamic Perturbation (wTP) from the SE Hamiltonian to the ai Hamiltonian is performed to obtain the ai QM/MM FE profile using weight factors from the MBAR analysis. In this work, this method is extended to the calculations of two-dimensional FE surfaces of two Diels–Alder reactions of cyclopentadiene with either acrylonitrile or 1-4-naphthoquinone at ai QM/MM level. The accurate activation free energies at the ai QM/MM level, which are much closer to the experimental measurements than those calculated by other methods, indicate that this MBAR+wTP method can be applied in the studies of complex reactions in condensed phase with much-enhanced efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Molecular Mechanisms Underlying Surfactant-Based Plastics De-Inking

Surfactant-mediated binder removal is critical for de-inking pretreatment in plastics recycling, yet the molecular mechanisms governing surfactant performance remain poorly understood. We used all-atom (AA) and coarse-grained (CG) molecular dynamics (MD) simulations alongside alkaline surfactant washing experiments to investigate interactions between a series of surfactants and a polyether urethane (PEU) binder in solution and on a polyethylene (PE) surface. Experiments reveal a range of de-inking efficiencies, ranging from <25 to >95% depending upon surfactant headgroup charge and tail length. AA simulations reveal that charged surfactants reach stable levels of surfactant coverage, while nonionic surfactants aggregate on the binder. CG umbrella sampling calculations quantify the thermodynamics of binder desorption in water. In ∼0.25 M surfactant solutions, up to a 52% reduction in the free energy barrier is computed, with trends in good agreement (R 2 = 0.92, Pearson’s r = –0.96, Spearman’s ρ = –0.83) with experimental de-inking efficiencies. We find that charged surfactants are more effective than nonionic surfactants for de-inking and propose three regimes of surfactant de-inking processes: good de-inking occurs in surfactants that promote PEU desorption with a low radius of gyration (R g ); moderate de-inking occurs when surfactants stabilize PEU but increase R g ; poor de-inking occurs in surfactants that aggregate on the binder and promote extensive anchoring to the surface. Overall, these molecular-level insights have the potential to guide the design of surfactant formulations for plastics recycling applications.

ink removal↗
DOE OSTI2014

Statistically optimal analysis of state-discretized trajectory data from multiple thermodynamic states

We propose a discrete transition-based reweighting analysis method (dTRAM) for analyzing configuration-space-discretized simulation trajectories produced at different thermodynamic states (temperatures, Hamiltonians, etc.) dTRAM provides maximum-likelihood estimates of stationary quantities (probabilities, free energies, expectation values) at any thermodynamic state. In contrast to the weighted histogram analysis method (WHAM), dTRAM does not require data to be sampled from global equilibrium, and can thus produce superior estimates for enhanced sampling data such as parallel/simulated tempering, replica exchange, umbrella sampling, or metadynamics. In addition, dTRAM provides optimal estimates of Markov state models (MSMs) from the discretized state-space trajectories at all thermodynamic states. Under suitable conditions, these MSMs can be used to calculate kinetic quantities (e.g., rates, timescales). In the limit of a single thermodynamic state, dTRAM estimates a maximum likelihood reversible MSM, while in the limit of uncorrelated sampling data, dTRAM is identical to WHAM. dTRAM is thus a generalization to both estimators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Transition State Theory Methods To Measure Diffusion in Flexible Nanoporous Materials: Application to a Porous Organic Cage Crystal

Transition state theory (TST) methods are useful for predicting adsorbate diffusivities in nanoporous materials at timescales inaccessible to molecular dynamics (MD). Most TST applications treat the nanoporous framework as rigid, which is inaccurate in highly flexible materials or where adsorbate dimensions are comparable to the size of pore aperatures. In this study, we demonstrate two computationally efficient TST methods for simulating adsorbate diffusion in nanoporous materials where framework flexibility has a significant influence on diffusion. These methods are applied to light gas diffusion in porous organic cage crystal 3 (CC3), a highly flexible molecular crystal that has shown promise in gas separation applications. Diffusion in CC3 is modeled as a series of uncorrelated adsorbate hops between cage molecules and the voids between adjacent cages. The first method we applied to compute adsorbate hopping rates in CC3 is implicit ligand sampling (ILS). In ILS TST, hopping rates are calculated in an ensemble of rigid framework snapshots captured from a fully flexible MD trajectory of the empty CC3 structure. The second TST method we applied is umbrella sampling (US), where hopping rates are computed from a series of biased MD simulations. Our ILS and US TST calculations are shown to agree well with direct MD simulation of adsorbate diffusion in CC3. We anticipate that the efficient TST methods detailed here will be broadly applicable other classes of flexible nanoporous materials such as metal–organic frameworks.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Comparing solvophobic and multivalent induced collapse in polyelectrolyte brushes

Here, coarse-grained molecular dynamics enhanced by free-energy sampling methods is used to examine the roles of solvophobicity and multivalent salts on polyelectrolyte brush collapse. Specifically, we demonstrate that while ostensibly similar, solvophobic collapsed brushes and multivalent-ion collapsed brushes exhibit distinct mechanistic and structural features. Notably, multivalent-induced heterogeneous brush collapse is observed under good solvent polymer backbone conditions, demonstrating that the mechanism of multivalent collapse is not contingent upon a solvophobic backbone. Umbrella sampling of the potential of mean-force (PMF) between two individual brush strands confirms this analysis, revealing starkly different PMFs under solvophobic and multivalent conditions, suggesting the role of multivalent “bridging” as the discriminating feature in trivalent collapse. Structurally, multivalent ions show a propensity for nucleating order within collapsed brushes, whereas poor-solvent collapsed brushes are more disordered; this difference is traced to the existence of a metastable PMF minimum for poor solvent conditions, and a global PMF minimum for trivalent systems, under experimentally relevant conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multitask Machine Learning of Collective Variables for Enhanced Sampling of Rare Events

Computing accurate reaction rates is a central challenge in computational chemistry and biology because of the high cost of free energy estimation with unbiased molecular dynamics. In this work, a data-driven machine learning algorithm is devised to learn collective variables with a multitask neural network, where a common upstream part reduces the high dimensionality of atomic configurations to a low dimensional latent space and separate downstream parts map the latent space to predictions of basin class labels and potential energies. Here, the resulting latent space is shown to be an effective low-dimensional representation, capturing the reaction progress and guiding effective umbrella sampling to obtain accurate free energy landscapes. This approach is successfully applied to model systems including a 5D Müller Brown model, a 5D three-well model, the alanine dipeptide in vacuum, and an Au(110) surface reconstruction unit reaction. It enables automated dimensionality reduction for energy controlled reactions in complex systems, offers a unified and data-efficient framework that can be trained with limited data, and outperforms single-task learning approaches, including autoencoders.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Studying vapor-liquid transition using a generalized ensemble

Homogeneous vapor-liquid nucleation is studied using the generalized Replica Exchange Method (gREM). The generalized ensemble allows the study of unstable states that cannot directly be studied in the canonical ensemble. Along with replica exchange, this allows for efficient sampling of the multiple states in a single simulation. Statistical Temperature Weighted Histogram Analysis Method is used for postprocessing to get a continuous free energy curve from bulk vapor to bulk liquid. gREM allows the study of planar, cylindrical, and spherical interfaces in a single simulation. The excess Gibbs free energy for the formation of a spherical liquid droplet in vapor for a Lennard-Jones system is calculated from the free energy curve and compared against the umbrella sampling results. The nucleation free energy barrier obtained from gREM is then used to calculate the nucleation rate without relying on any classification scheme for separating the vapor and liquid.

Ballal, Deepti (ORCID:0000000315694749)↗
DOE OSTI2018

Emergent Properties of Antiagglomerant Films Control Methane Transport: Implications for Hydrate Management

The relationship between collective properties and performance of antiagglomerants (AAs) used in hydrate management is handled using molecular dynamics simulations and enhanced sampling techniques. A thin film of AAs adsorbed at the interface between one flat sII methane hydrate substrate and a fluid hydrocarbon mixture containing methane and $n$-dodecane is studied. The AA considered is a surface-active compound with a complex hydrophilic head that contains both amide and tertiary ammonium cation groups and hydrophobic tails. At a sufficiently high AA density, the interplay between the surfactant layer and the liquid hydrocarbon excludes methane from the interfacial region. In this scenario, we combine metadynamics and umbrella sampling frameworks to study accurately the free-energy landscape and the equilibrium rates associated with the transport of one methane molecule across the AA film. We observe that the local configurational changes of the liquid hydrocarbon packed within the AA film are associated with high free-energy barriers for methane transport. The time scales estimated for the transport of methane across the AA film can be, in some cases, comparable to those reported in the literature for the growth of hydrates, suggesting that one possible mechanism by which AAs delay the formation of hydrate plugs could be providing a barrier to methane transport. Considering the interplay between the structural design and collective properties of AAs might be of relevance to improve their performance in flow assurance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

An interoperable implementation of collective‐variable based enhanced sampling methods in extended phase space within the OpenMM package

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. Here, in this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Molecular simulation of lignin-related aromatic compound permeation through gram-negative bacterial outer membranes

Lignin, an abundant aromatic heteropolymer in secondary plant cell walls, is the single largest source of renewable aromatics in the biosphere. Leveraging this resource for renewable bioproducts through targeted microbial action depends on lignin fragment uptake by microbial hosts and subsequent enzymatic action to obtain the desired product. Recent computational work has emphasized that bacterial inner membranes are permeable to many aromatic compounds expected from lignin depolymerization processes. In this study, we expand on these findings through simulations for 42 lignin-related compounds across a gram-negative bacterial outer membrane model. Unbiased simulation trajectories indicate that spontaneous crossing for the full outer membrane is relatively rare at molecular simulation timescales, primarily due to preferential membrane partitioning and slow diffusion within the lipopolysaccharide layer within the outer membrane. Membrane partitioning and permeability coefficients were determined through replica exchange umbrella sampling simulations to overcome sampling limitations. We find that the glycosylated lipopolysaccharides found in the outer membrane increase the permeation barrier to many lignin-related compounds, particularly the most hydrophobic compounds. However, the effect is relatively modest; at industrially relevant concentrations, uncharged lignin-related compounds will readily diffuse across the outer membrane without the need for specific porins. Together, our results provide insight into the permeability of the bacterial outer membrane for assessing lignin fragment uptake and the future production of renewable bioproducts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Computational methods for intramolecular electron transfer in a ferrous-ferric iron complex

The limitations of common theoretical and molecular computational approaches for predicting electron transfer quantities were assessed, using an archetypal bridged ferrous-ferric electron transfer system in aqueous solution. The basis set effect on the magnitude of the electronic coupling matrix element computed using the quasi-diabatic method was carefully examined, and it was found that the error related to a poor basis set could exceed the thermal energy at room temperature. A range of approaches to determining the external (solvent) reorganization energy were also investigated. Significant improvements from the Marcus continuum model can be obtained by including dipolar Born-Kirkwood-Onsager correction. In this regard we also found that Klamt’s Conductor-Like Screening Model (COSMO) yields estimations of the external reorganization energy similar to those obtained with explicit solvent molecular dynamics simulations, if the fast-frequency modes are neglected, which makes it an attractive alternative to laborious umbrella sampling simulations. As expected, dielectric saturation observed in the first solvation shell decreases the curvature of the potential energy surface, but it nonetheless remains a quadratic function of the reaction coordinate. The linearity of solvent response to the charge redistribution was assessed by analyzing the energy gap autocorrelation function as well as the solvent density and dipole moment fluctuations. Molecular dynamics was also used to evaluate the sign and magnitude of the solvent reorganization entropy, to determine its effect on the predicted electron transfer rate. Finally, we present a simple way of estimating the vibration frequency along the reaction coordinate, which also enables prediction of the mass dependent isotopic signature of electron-transfer reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Differential Membrane Binding Mechanics of Synaptotagmin Isoforms Observed in Atomic Detail

Synaptotagmin (Syt) is a membrane-associated protein involved in vesicle fusion through the SNARE complex that is found throughout the human body in 17 different isoforms. These isoforms have two membrane-binding C2 domains, which sense Ca 2+ and thereby promote anionic membrane binding and lead to vesicle fusion. Through molecular dynamics simulations using the HMMM acclerated bilayer model, we have investigated how small protein sequence changes in the Ca 2+ binding loops of the C2 domains may give rise to the experimentally determined difference in binding kinetics between Syt-1 and Syt-7 isoforms. Syt-7 C2 domains are found to form more close contacts with anionic phospholipid head groups, particularly in Loop 1, where an additional positive charge in Syt-7 draws the loop closer to the membrane and causes the anchoring residue F167 to insert deeper into the bilayer than the corresponding methionine in Syt-1 (M173). By carrying out additional replica exchange umbrella sampling calculations, we demonstrate that these additional contacts increase the energetic cost of unbinding the Syt-7 C2 domains from the bilayer, causing them to unbind more slowly than their counterparts in Syt-1.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Atomistic Characterization of Gramicidin Channel Formation

We investigated gramicidin A (gA) subunit dimerization in lipid bilayers using microsecond-long replica-exchange umbrella sampling simulations, millisecond-long unbiased molecular dynamics simulations, and machine learning. Our simulations led to a dimer structure that is indistinguishable from the experimentally determined gA channel structures, with the two gA subunits joined by six hydrogen bonds (6HB). The simulations also uncovered two additional dimer structures, with different gA–gA stacking orientations that were stabilized by four or two hydrogen bonds (4HB or 2HB). When examining the temporal evolution of the dimerization, we found that two bilayer-inserted gA subunits can form the 6HB dimer directly, with no discernible intermediate states, as well as through paths that involve the 2HB and 4HB dimers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Thermodynamic Analysis of Silk Fibroin–Graphite Hybrid Materials and Their Morphology

Silk fibroin (SF) is a β-sheet-rich protein that is responsible for the remarkable tensile strength of silk. In addition to its mechanical properties, SF is biocompatible and biodegradable, making it an attractive candidate for use in biotic/abiotic hybrid materials. A pairing of particular interest is the use of SF with graphene-based nanomaterials (GBNs). The properties of this interface drive the formation of well-ordered nanostructures and can improve the electronic properties of the resulting hybrid. It was previously demonstrated that SF can form lamellar nanostructures in the presence of graphite; however, the equilibrium morphology and associated driving interactions are not fully understood. Here, in this study, we characterize these interactions between SF and SF lamellar with graphite using molecular dynamics (MD) simulations and umbrella sampling (US). We find that SF lamellar nanostructures have strong orientational and spatial preferences on graphite that are driven by the hydrophobic effect, destabilizing solvent–protein interactions and stabilizing protein–protein and protein–graphite interactions. Finally, we show how careful consideration of these underlying interactions can be applied to rationally modify the nanostructure morphology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Molecular Modeling and Molecular Dynamics Simulation of a Packed and Intact Bacterial Microcompartment

Bacterial microcompartments (BMCs) are protein-bound organelles found in some bacteria which encapsulate enzymes for enhanced catalytic activity. These compartments spatially sequester enzymes within semipermeable shell proteins and are packed full of enzyme cargoes and metabolites as they fulfill their function. Coupling together recent SAXS and proteomics work, it is possible to develop molecular models for these microcompartments and interrogate enzyme and metabolite dynamics within. Our primary goal of this study is to quantify the permeability of metabolite glyceraldehyde-3-phosphate (G3P) and dihydroxyacetone phosphate (DHAP) across the BMC shell through classical molecular dynamics simulation. The Haliangium ochraceum model of BMC shell (PDB: 6MZX) was used to model an intact BMC of approximately 10 million atoms. Working at this scale presented its own challenges in managing large data sets, with multiple challenges and hardware advances discussed that facilitated this work. Over approximately 750 ns of aggregate simulation, we see multiple permeation events for these metabolites that were added at high concentration through the pores present within BMC shell tiles. When compared to independent permeability estimates for the same metabolites determined through replica exchange umbrella sampling simulations, the permeabilities varied by approximately 3 orders of magnitude. Regardless, the permeability coefficients for both G3P and DHAP are highly similar and very high, such that only very small concentration gradients can be maintained across the BMC shell between the cytosol and BMC interior. The large simulation systems also facilitated comparisons for molecular diffusivity in the crowded environment within the BMC shell. By our estimates, the viscosity within a packed BMC shell is at least 10-fold higher than it would be in neat solution and is the real driver for varying permeability estimates we obtained through simulation. These findings will be used as design inputs for future bioengineering efforts to make products from BMCs, highlighting how permeable BMC shells can be.

Diffusion↗
DOE OSTI2017

Predicting a Drug’s Membrane Permeability: A Computational Model Validated With in Vitro Permeability Assay Data

Membrane permeability is a key property to consider during the drug design process, and particularly vital when dealing with small molecules that have intracellular targets as their efficacy highly depends on their ability to cross the membrane. In this work, we describe the use of umbrella sampling Molecular Dynamics (MD) computational modeling to comprehensively assess the passive permeability profile of a range of compounds through a lipid bilayer. The model was initially calibrated through in vitro validation studies employing a Parallel Artificial Membrane Permeability Assay (PAMPA). The model was subsequently evaluated for its quantitative prediction of permeability profiles for a series of custom synthesized and closely related compounds. The results exhibited substantially improved agreement with the PAMPA data, relative to alternative existing methods. Our work introduces a computational model that underwent progressive molding and fine-tuning as a result of its synergistic collaboration with numerous in vitro PAMPA permeability assays. The presented computational model introduces itself as a useful, predictive tool for permeability prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Restrained Proton Indicator in Combined Quantum-Mechanics/Molecular-Mechanics Dynamics Simulations of Proton Transfer through a Carbon Nanotube

Recently, a collective variable “proton indicator” was purposed for tracking an excess proton solvated in bulk water in molecular dynamics simulations. In this work, we demonstrate the feasibility of utilizing the position of this proton indicator as a reaction coordinate to model an excess proton migrating through a hydrophobic carbon nanotube in combined quantum-mechanics/molecular-mechanics simulations. Our results indicate that applying a harmonic restraint to the proton indicator in the bulk solvent near the nanotube pore entrance leads to the recruitment of water molecules into the pore. This is consistent with an earlier study that employed a multistate empirical valence bond potential and a different representation (center of excess charge) of the proton. We attribute this water recruitment to the delocalized nature of the solvated proton, which prefers to be in high-dielectric bulk solvent. While water recruitment into the pore is considered an artifact in the present simulations (because of the artificially imposed restraint on the proton), if the proton were naturally restrained, it could assist in building water wires prior to proton transfer through the pore. The potential of mean force for a proton translocation through the water-filled pore was computed by umbrella sampling, where the bias potentials were applied to the proton indicator. The free energy curve and barrier heights agree reasonably with those in the literature. Finally, the results suggest that the proton indicator can be used as a reaction coordinate in simulations of proton transport in confined environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗