scholarly journals A hierarchical Bayesian framework for force field selection in molecular dynamics simulations

2016 ◽  
Vol 374 (2060) ◽  
pp. 20150032 ◽  
Author(s):  
S. Wu ◽  
P. Angelikopoulos ◽  
C. Papadimitriou ◽  
R. Moser ◽  
P. Koumoutsakos
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Force Field ◽  
Computational Cost ◽  
Md Simulations ◽  
Bayesian Framework ◽  
Underlying Structure ◽  
Hierarchical Bayesian ◽  
Wide Range ◽  
Selection Of

We present a hierarchical Bayesian framework for the selection of force fields in molecular dynamics (MD) simulations. The framework associates the variability of the optimal parameters of the MD potentials under different environmental conditions with the corresponding variability in experimental data. The high computational cost associated with the hierarchical Bayesian framework is reduced by orders of magnitude through a parallelized Transitional Markov Chain Monte Carlo method combined with the Laplace Asymptotic Approximation. The suitability of the hierarchical approach is demonstrated by performing MD simulations with prescribed parameters to obtain data for transport coefficients under different conditions, which are then used to infer and evaluate the parameters of the MD model. We demonstrate the selection of MD models based on experimental data and verify that the hierarchical model can accurately quantify the uncertainty across experiments; improve the posterior probability density function estimation of the parameters, thus, improve predictions on future experiments; identify the most plausible force field to describe the underlying structure of a given dataset. The framework and associated software are applicable to a wide range of nanoscale simulations associated with experimental data with a hierarchical structure.

scholarly journals Ligand-induced structural changes analysis of ribose-binding protein as studied by molecular dynamics simulations

2021 ◽  
pp. 1-12
Author(s):  
Haiyan Li ◽  
Zanxia Cao ◽  
Guodong Hu ◽  
Liling Zhao ◽  
Chunling Wang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Structural Changes ◽  
Binding Protein ◽  
Network Models ◽  
Md Simulations ◽  
Protein Domain ◽  
Opening Angle ◽  
Conformation Changes ◽  
Wide Range ◽  
Ribose Binding Protein

BACKGROUND: The ribose-binding protein (RBP) from Escherichia coli is one of the representative structures of periplasmic binding proteins. Binding of ribose at the cleft between two domains causes a conformational change corresponding to a closure of two domains around the ligand. The RBP has been crystallized in the open and closed conformations. OBJECTIVE: With the complex trajectory as a control, our goal was to study the conformation changes induced by the detachment of the ligand, and the results have been revealed from two computational tools, MD simulations and elastic network models. METHODS: Molecular dynamics (MD) simulations were performed to study the conformation changes of RBP starting from the open-apo, closed-holo and closed-apo conformations. RESULTS: The evolution of the domain opening angle θ clearly indicates large structural changes. The simulations indicate that the closed states in the absence of ribose are inclined to transition to the open states and that ribose-free RBP exists in a wide range of conformations. The first three dominant principal motions derived from the closed-apo trajectories, consisting of rotating, bending and twisting motions, account for the major rearrangement of the domains from the closed to the open conformation. CONCLUSIONS: The motions showed a strong one-to-one correspondence with the slowest modes from our previous study of RBP with the anisotropic network model (ANM). The results obtained for RBP contribute to the generalization of robustness for protein domain motion studies using either the ANM or PCA for trajectories obtained from MD.

scholarly journals Molecular dynamics simulations and CD spectroscopy reveal hydration-induced unfolding of the intrinsically disordered LEA proteins COR15A and COR15B from Arabidopsis thaliana

2016 ◽  
Vol 18 (37) ◽  
pp. 25806-25816 ◽  
Author(s):  
Carlos Navarro-Retamal ◽  
Anne Bremer ◽  
Jans Alzate-Morales ◽  
Julio Caballero ◽  
Dirk K. Hincha ◽  
...  
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Arabidopsis Thaliana ◽  
Molecular Dynamics Simulations ◽  
Md Simulations ◽  
Cd Spectroscopy ◽  
Lea Proteins ◽  
Intrinsically Disordered ◽  
Dynamics Simulations ◽  
Crowded Environment

Unfolding of intrinsically unstructured full-length LEA proteins in a differentially crowded environment can be modeled by 30 ns MD simulations in accordance with experimental data.

Bayesian active learning of interatomic force field for molecular dynamics simulation of Pt/Ag(111)

2021 ◽  
Author(s):  
Kai Xu ◽  
Lei Yan ◽  
Bingran You
Keyword(s):  
Molecular Dynamics ◽  
Active Learning ◽  
Force Field ◽  
Density Functional ◽  
Process Model ◽  
Large Scale ◽  
Computational Cost ◽  
Dynamics Simulation ◽  
Potential Energy Landscape ◽  
Three Body

Force field is a central requirement in molecular dynamics (MD) simulation for accurate description of the potential energy landscape and the time evolution of individual atomic motions. Most energy models are limited by a fundamental tradeoff between accuracy and speed. Although ab initio MD based on density functional theory (DFT) has high accuracy, its high computational cost prevents its use for large-scale and long-timescale simulations. Here, we use Bayesian active learning to construct a Gaussian process model of interatomic forces to describe Pt deposited on Ag(111). An accurate model is obtained within one day of wall time after selecting only 126 atomic environments based on two- and three-body interactions, providing mean absolute errors of 52 and 142 meV/Å for Ag and Pt, respectively. Our work highlights automated and minimalistic training of machine-learning force fields with high fidelity to DFT, which would enable large-scale and long-timescale simulations of alloy surfaces at first-principles accuracy.

Highly Efficient and Accurate Gas-Alkane Binary Mixture Interfacial Tension Equations for a Broad Range of Temperatures, Pressures, and Compositions

SPE Journal ◽  
2021 ◽  
pp. 1-19
Author(s):  
Yingnan Wang ◽  
Nadia Shardt ◽  
Janet A. W. Elliott ◽  
Zhehui Jin
Keyword(s):  
Experimental Data ◽  
Binary Mixture ◽  
Interfacial Tension ◽  
Binary Mixtures ◽  
Oil Recovery ◽  
Computational Cost ◽  
Petroleum Engineering ◽  
Pure Species ◽  
Highly Efficient ◽  
Wide Range

Summary Gas-alkane interfacial tension (IFT) is an important parameter in the enhanced oil recovery (EOR) process. Thus, it is imperative to obtain an accurate gas-alkane mixture IFT for both chemical and petroleum engineering applications. Various empirical correlations have been developed in the past several decades. Although these models are often easy to implement, their accuracy is inconsistent over a wide range of temperatures, pressures, and compositions. Although statistical mechanics-based models and molecular simulations can accurately predict gas-alkane IFT, they usually come with an extensive computational cost. The Shardt-Elliott (SE) model is a highly accurate IFT model that for subcritical fluids is analytic in terms of temperature T and composition x. In applications, it is desirable to obtain IFT in terms of temperature T and pressure P, which requires time-consuming flash calculations, and for mixtures that contain a gas component greater than its pure species critical point, additional critical composition calculations are required. In this work, the SE model is combined with a machine learning (ML) approach to obtain highly efficient and highly accurate gas-alkane binary mixture IFT equations directly in terms of temperature, pressure, and alkane molar weights. The SE model is used to build an IFT database (more than 36,000 points) for ML training to obtain IFT equations. The ML-based IFT equations are evaluated in comparison with the available experimental data (888 points) and with the SE model, as well as with the less accurate parachor model. Overall, the ML-based IFT equations show excellent agreement with experimental data for gas-alkane binary mixtures over a wide range of T and P, and they outperform the widely used parachor model. The developed highly efficient and highly accurate IFT functions can serve as a basis for modeling gas-alkane binary mixtures for a broad range of T, P, and x.

scholarly journals Molecular Dynamics Modellization and Simulation of Water Diffusion through Plant Cutin

1999 ◽  
Vol 54 (11) ◽  
pp. 896-902 ◽  
Author(s):  
Antonio Matas ◽  
Antonio Heredia
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Structural Information ◽  
Md Simulations ◽  
Water Molecules ◽  
Plant Cuticle ◽  
X Ray Diffraction ◽  
Cross Link ◽  
X Ray ◽  
Good Agreement

Abstract A theoretical molecular modelling study has been conducted for cutin, the biopolyester that forms the main structural component of the plant cuticle. Molecular dynamics (MD) simulations, extended over several ten picoseconds, suggests that cutin is a moderately flexible netting with motional constraints mainly located at the cross-link sites of functional ester groups. This study also gives structural information essentially in accordance with previously reported experimental data, obtained from X -ray diffraction and nuclear magnetic resonance experiments. MD calculations were also performed to simulate the diffusion of water mole­cules through the cutin biopolymer. The theoretical analysis gives evidence that water perme­ation proceedes by a “hopping mechanism”. Coefficients for the diffusion of the water molecules in cutin were obtained from their mean-square displacements yielding values in good agreement with experimental data.

Mechanical Properties of α-Helices Estimated Using Molecular Dynamics and Finite Element Simulations

2008 ◽  
Author(s):  
Peyman Honarmandi ◽  
Philip Bransford ◽  
Roger D. Kamm
Keyword(s):  
Mechanical Properties ◽  
Molecular Dynamics ◽  
Finite Element ◽  
Solid Mechanics ◽  
Normal Mode Analysis ◽  
Computational Cost ◽  
Md Simulations ◽  
Elastic Stiffness ◽  
Mode Analysis ◽  
Molecular Volume

Mechanical properties of biomolecules and their response to mechanical forces may be studied using Molecular Dynamics (MD) simulations. However, high computational cost is a primary drawback of MD simulations. This paper presents a computational framework based on the integration of the Finite Element Method (FEM) with MD simulations to calculate the mechanical properties of polyalanine α-helix proteins. In this method, proteins are treated as continuum elastic solids with molecular volume defined exclusively by their atomic surface. Therefore, all solid mechanics theories would be applicable for the presumed elastic media. All-atom normal mode analysis is used to calculate protein’s elastic stiffness as input to the FEM. In addition, constant force molecular dynamics (CFMD) simulations can be used to predict other effective mechanical properties, such as the Poisson’s Ratio. Force versus strain data help elucidate the mechanical behavior of α-helices upon application of constant load. The proposed method may be useful in identifying the mechanical properties of any protein or protein assembly with known atomic structure.

scholarly journals Simulating Absorption Spectra of Flavonoids in Aqueous Solution: A Polarizable QM/MM Study

Molecules ◽  
2020 ◽  
Vol 25 (24) ◽  
pp. 5853
Author(s):  
Sulejman Skoko ◽  
Matteo Ambrosetti ◽  
Tommaso Giovannini ◽  
Chiara Cappelli
Keyword(s):  
Molecular Dynamics ◽  
Aqueous Solution ◽  
Hydrogen Bonding ◽  
Force Field ◽  
Absorption Spectra ◽  
Computational Study ◽  
Md Simulations ◽  
Quantum Mechanical ◽  
Hydrogen Bonding Interactions

We present a detailed computational study of the UV/Vis spectra of four relevant flavonoids in aqueous solution, namely luteolin, kaempferol, quercetin, and myricetin. The absorption spectra are simulated by exploiting a fully polarizable quantum mechanical (QM)/molecular mechanics (MM) model, based on the fluctuating charge (FQ) force field. Such a model is coupled with configurational sampling obtained by performing classical molecular dynamics (MD) simulations. The calculated QM/FQ spectra are compared with the experiments. We show that an accurate reproduction of the UV/Vis spectra of the selected flavonoids can be obtained by appropriately taking into account the role of configurational sampling, polarization, and hydrogen bonding interactions.

SoftBV – a software tool for screening the materials genome of inorganic fast ion conductors

2019 ◽  
Vol 75 (1) ◽  
pp. 18-33 ◽  
Author(s):  
Haomin Chen ◽  
Lee Loong Wong ◽  
Stefan Adams
Keyword(s):  
Force Field ◽  
High Throughput ◽  
High Throughput Screening ◽  
Density Functional ◽  
Inorganic Compounds ◽  
Computational Cost ◽  
Lewis Base ◽  
Computational Screening ◽  
Wide Range ◽  
Dft Simulations

The identification of materials for advanced energy-storage systems is still mostly based on experimental trial and error. Increasingly, computational tools are sought to accelerate materials discovery by computational predictions. Here are introduced a set of computationally inexpensive software tools that exploit the bond-valence-based empirical force field previously developed by the authors to enable high-throughput computational screening of experimental or simulated crystal-structure models of battery materials predicting a variety of properties of technological relevance, including a structure plausibility check, surface energies, an inventory of equilibrium and interstitial sites, the topology of ion-migration paths in between those sites, the respective migration barriers and the site-specific attempt frequencies. All of these can be predicted from CIF files of structure models at a minute fraction of the computational cost of density functional theory (DFT) simulations, and with the added advantage that all the relevant pathway segments are analysed instead of arbitrarily predetermined paths. The capabilities and limitations of the approach are evaluated for a wide range of ion-conducting solids. An integrated simple kinetic Monte Carlo simulation provides rough (but less reliable) predictions of the absolute conductivity at a given temperature. The automated adaptation of the force field to the composition and charge distribution in the simulated material allows for a high transferability of the force field within a wide range of Lewis acid–Lewis base-type ionic inorganic compounds as necessary for high-throughput screening. While the transferability and precision will not reach the same levels as in DFT simulations, the fact that the computational cost is several orders of magnitude lower allows the application of the approach not only to pre-screen databases of simple structure prototypes but also to structure models of complex disordered or amorphous phases, and provides a path to expand the analysis to charge transfer across interfaces that would be difficult to cover by ab initio methods.

A Study of Nanoparticle-Enhanced Heat Transfer

2010 ◽  
Author(s):  
Lawrence M. Jones ◽  
Timothy Sirk ◽  
Eugene Brown
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Molecular Dynamics ◽  
Heat Flux ◽  
Nuclear Power ◽  
Power Plants ◽  
Md Simulations ◽  
Theoretical Description ◽  
Different Temperatures ◽  
Dynamics Simulations

The study of the heat transfer characteristics of nanofluids, i.e. fluids that are suspensions of nanometer size particles, has gained significant attention in the search for new coolants that can effectively service a variety of needs ranging from the increasing heat transfer demands of ever smaller microelectronic devices to mitigating the effects of loss of coolant accidents in nuclear power plants. Experimental data has shown large increases in thermal conductivity and associated increases in the level of critical heat flux in nuclear reactors; however, in some cases the range of the applicability of the experimental results is uncertain and there is a lack of a theory by which this can be resolved. Complicating the theoretical description of heat transfer in nanofluids is the fact that fluids in the vicinity of the nanoparticles are a complex combination of phase transition, interfacial, and transport phenomena. This paper describes a study in which molecular dynamics simulations were used to enhance the understanding of the effect of nanoparticles on heat transfer. The molecular dynamics (MD) simulations presented here model a Lennard-Jones fluid in a channel where the walls are maintained at different temperatures. The heat flux is calculated for a variety of nanoparticle sizes and concentrations. The results are compared to experimental data in order to provide information that will more confidently bound the data and provide information that will guide the development of more comprehensive theories. We also anticipate that this work could contribute to the design of biosensors where suspended molecules are transported through micro- and nano-channels in the presence of heat transfer.

Molecular Dynamics and Multiscale Simulations of Nanoindentation and Nanoscratch

2010 ◽  
Author(s):  
Peng-zhe Zhu ◽  
Hui Wang ◽  
Yuan-zhong Hu
Keyword(s):  
Molecular Dynamics ◽  
Computational Cost ◽  
Three Dimensional ◽  
Multiscale Model ◽  
Md Simulations ◽  
System Size ◽  
Multiscale Simulations ◽  
First Case ◽  
Chip Volume ◽  
Indenter Shape

Three-dimensional molecular dynamics (MD) simulations have been performed to investigate behaviors of nanoindentation and nano-scratch. The first case concerns the effects of material defect on the nanoindentation of nickel thin film. The defect is modeled by a spherical void embedded in the substrate and located under the surface of indentation. The simulation results reveal that compared to the case without defect, the presence of the void softens the material and allows for larger indentation depth at a given load. MD simulations are then performed for nano-scratch of single crystal copper, with emphasis on the effect of indenter shape (sharp and blunt) on the substrate deformation. The results show that the blunt indenter causes larger deformation region and much more dislocations at both the indentation and scratch stages. It is also found that during the scratching stage the blunt indenter results in larger chip volume in front of the indenter and gives rise to more friction than the sharp indenter. The scope of the simulations has been extended by introducing a multiscale model which couples MD simulations with Finite Element Method (FEM), and multiscale simulations are performed for two-dimensional nanoindentation of copper. The model has been validated by well-consistent load-depth curves obtained from both multiscale and full MD simulations, and by good continuity of deformation observed in the handshake region. The simulations also reveal that indenter radius and indentation velocity significantly affect the nanoindentation behavior. By use of multiscale method, the system size to be explored can be greatly expanded without increasing much computational cost.

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