scholarly journals Nanoindentation simulations for large atomic systems : an analysis of molecular dynamics and bridged finite element - molecular dynamics methodologies

Author(s):  
Jonathan Vandersluis

This thesis develops a molecular dynamics (MD) custom made computational tool to perform nanoindentation simulations on copper nanomaterials, a Face Centred Cubic (FCC) metal. The Embedding Atom Method (EAM) is used to model the interatomic forces with the substrate. Further, a bridged finite element - molecular dynamics (FE-MD) simulation tool is also adapted to perform nanoindentation experimentation. Using this bridged FE-MD simulation tool, nanoindentations are performed much more effectively than the MD simulations while saving substantial computational simulation time. While the MD simulation experienced difficulties capturing the behaviour of the system during indentation especially at faster indentation speeds, the bridged FE-MD method is capable of reaching a state of equilibrium within a single step for each indentation depth interval analyzed throughout the nanoindentation. Although the hardness values for these simulations cannot be obtained without larger scale simulations using more powerful computational resources, the simulations provide insight into the behaviour of the copper nanomaterial during nanoindentation. As a result, it is clear that the bridged FE-MD nanoindentation tool is much more effective for executing nanoindentation simulations than the traditional MD methodologies.

2021 ◽  
Author(s):  
Jonathan Vandersluis

This thesis develops a molecular dynamics (MD) custom made computational tool to perform nanoindentation simulations on copper nanomaterials, a Face Centred Cubic (FCC) metal. The Embedding Atom Method (EAM) is used to model the interatomic forces with the substrate. Further, a bridged finite element - molecular dynamics (FE-MD) simulation tool is also adapted to perform nanoindentation experimentation. Using this bridged FE-MD simulation tool, nanoindentations are performed much more effectively than the MD simulations while saving substantial computational simulation time. While the MD simulation experienced difficulties capturing the behaviour of the system during indentation especially at faster indentation speeds, the bridged FE-MD method is capable of reaching a state of equilibrium within a single step for each indentation depth interval analyzed throughout the nanoindentation. Although the hardness values for these simulations cannot be obtained without larger scale simulations using more powerful computational resources, the simulations provide insight into the behaviour of the copper nanomaterial during nanoindentation. As a result, it is clear that the bridged FE-MD nanoindentation tool is much more effective for executing nanoindentation simulations than the traditional MD methodologies.


2020 ◽  
Vol 36 (18) ◽  
pp. 4714-4720
Author(s):  
Farzin Sohraby ◽  
Mostafa Javaheri Moghadam ◽  
Masoud Aliyar ◽  
Hassan Aryapour

Abstract Summary Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased MD simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased MD simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) MD simulations, in this case a protein–ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nanosecond time scales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction. Availability and implementation The links of the tutorial and technical documents are accessible in the article. Supplementary information Supplementary data are available at Bioinformatics online.


Nanomaterials ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 1088 ◽  
Author(s):  
Yang Kang ◽  
Dunhong Zhou ◽  
Qiang Wu ◽  
Fuyan Duan ◽  
Rufang Yao ◽  
...  

The physical properties—including density, glass transition temperature (Tg), and tensile properties—of polybutadiene (PB), polystyrene (PS) and poly (styrene-butadiene-styrene: SBS) block copolymer were predicted by using atomistic molecular dynamics (MD) simulation. At 100 K, for PB and SBS under uniaxial tension with strain rate ε ˙ = 1010 s−1 and 109 s−1, their stress–strain curves had four features, i.e., elastic, yield, softening, and strain hardening. At 300 K, the tensile curves of the three polymers with strain rates between 108 s−1 and 1010 s−1 exhibited strain hardening following elastic regime. The values of Young’s moduli of the copolymers were independent of strain rate. The plastic modulus of PS was independent of strain rate, but the Young’s moduli of PB and SBS depended on strain rate under the same conditions. After extrapolating the Young’s moduli of PB and SBS at strain rates of 0.01–1 s−1 by the linearized Eyring-like model, the predicted results by MD simulations were in accordance well with experimental results, which demonstrate that MD results are feasible for design of new materials.


Author(s):  
Peyman Honarmandi ◽  
Philip Bransford ◽  
Roger D. Kamm

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.


Volume 4 ◽  
2004 ◽  
Author(s):  
Aaron P. Wemhoff ◽  
Van P. Carey

Surface tension determination of liquid-vapor interfaces of polyatomic fluids using traditional methods has shown to be difficult due to the requirement of evaluating complex intermolecular potentials. However, analytical techniques have recently been developed that determine surface tension solely by means of the characteristics of the interfacial region between the bulk liquid and vapor regions. A post-simulation application of the excess free energy density integration (EFEDI) method was used for analysis of the resultant density profile of molecular dynamics (MD) simulations of argon using a simple Lennard-Jones potential and diatomic nitrogen using a two-center Lennard-Jones potential. MD simulations were also run for an approximation of nitrogen using the simple Lennard-Jones potential. In each MD simulation, a liquid film was initialized between vapor regions and NVE-type simulations were run to equilibrium. The simulation domain was divided into bins across the interfacial region for fluid density collection, and the resultant interfacial region density profile was used for surface tension evaluation. Application of the EFEDI method to these MD simulation results exhibited good approximations to surface tension as a function of temperature for both a simple and complex potential.


2019 ◽  
Author(s):  
Aleksandra Badaczewska-Dawid ◽  
Andrzej Kolinski ◽  
Sebastian Kmiecik

SummaryConformational flexibility of protein structures can play an important role in protein function. The flexibility is often studied using computational methods, since experimental characterization can be difficult. Depending on protein system size; computational tools may require large computational resources or significant simplifications in the modeled systems to speed-up calculations. In this work, we present the protocols for efficient simulations of flexibility of folded protein structures that use coarse-grained simulation tools of different resolutions: medium, represented by CABS-flex, and low, represented by SUPRASS. We test the protocols using a set of 140 globular proteins and compare the results with structure fluctuations observed in MD simulations, ENM modeling and NMR ensembles. As demonstrated, CABS-flex predictions show high correlation to experimental and MD simulation data, while SURPASS is less accurate but promising in terms of future developments.


2021 ◽  
Author(s):  
Jingxuan Zhu ◽  
Juexin Wang ◽  
Weiwei Han ◽  
Dong Xu

Abstract Protein allostery is a biological process facilitated by spatially long-range intra-protein communication, whereby ligand binding or amino acid mutation at a distant site affects the active site remotely. Molecular dynamics (MD) simulation provides a powerful computational approach to probe the allosteric effect. However, current MD simulations cannot reach the time scales of whole allosteric processes. The advent of deep learning made it possible to evaluate both spatially short and long-range communications for understanding allostery. For this purpose, we applied a neural relational inference (NRI) model based on a graph neural network (GNN), which adopts an encoder-decoder architecture to simultaneously infer latent interactions to probe protein allosteric processes as dynamic networks of interacting residues. From the MD trajectories, this model successfully learned the long-range interactions and pathways that can mediate the allosteric communications between the two distant sites in the Pin1, SOD1, and MEK1 systems.


2006 ◽  
Vol 05 (01) ◽  
pp. 131-144 ◽  
Author(s):  
JIHUA GOU ◽  
BIN FAN ◽  
GANGBING SONG ◽  
AURANGZEB KHAN

In the processing of carbon nanotube/polymer composites, the interactions between the nanotube and polymer matrix will occur at the molecular level. Understanding their interactions before curing is crucial for nanocomposites processing. In this study, molecular dynamics (MD) simulations were employed to reveal molecular interactions between (10, 10) single-walled nanotube and two kinds of epoxy resin systems. The two kinds of resin systems were EPON 862/EPI-CURE W curing agent (DETDA) and DGEBA (diglycidylether of bisphenol A)diethylenetriamine (DETA) curing agent. The MD simulation results show that the EPON 862, DETDA and DGEBA molecules had strong attractive interactions with single-walled nanotubes and their molecules changed their conformation to align their aromatic rings parallel to the nanotube surface due to π-stacking effect, whereas the DETA molecule had a repulsive interaction with the single-walled nanotubes. The interaction energies of the molecular systems were also calculated. Furthermore, an affinity index (AI) of the average distance between the atoms of the resin molecule and nanotube surface was defined to quantify the affinities between the nanotubes and resin molecules. The MD simulation results show that the EPON 862/EPI-CURE W curing agent system has good affinities with single-walled nanotubes.


Author(s):  
Sumith Yd ◽  
Shalabh C. Maroo

It is important to study contact angle of a liquid on a solid surface to understand its wetting properties, capillarity and surface interaction energy. While performing transient molecular dynamics (MD) simulations it requires calculating the time evolution of contact angle. This is a tedious effort to do manually or with image processing algorithms. In this work we propose a new algorithm to estimate contact angle from MD simulations directly and in a computationally efficient way. This algorithm segregates the droplet molecules from the vapor molecules using Mahalanobis distance (MND) technique. Then the density is smeared onto a 2D grid using 4th order B-spline interpolation function. The vapor liquid interface data is estimated from the grid using density filtering. With the interface data a circle is fitted using Landau method. The equation of this circle is solved for obtaining the contact angle. This procedure is repeated by rotating the droplet about the vertical axis. We have applied this algorithm to a number of studies (different potentials and thermostat methods) which involves the MD simulation of water.


Crystals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 43
Author(s):  
Joanna Smietanska ◽  
Tomasz Kozik ◽  
Radoslaw Strzalka ◽  
Ireneusz Buganski ◽  
Janusz Wolny

Molecular dynamics (MD) simulations provide a physics-based approach to understanding protein structure and dynamics. Here, we used this intriguing tool to validate the experimental structural model of Hyp-1, a pathogenesis-related class 10 (PR-10) protein from the medicinal herb Hypericum perforatum, with potential application in various pharmaceutical therapies. A nanosecond MD simulation using the all-atom optimized potentials for liquid simulations (OPLS–AA) force field was performed to reveal that experimental atomic displacement parameters (ADPs) underestimate their values calculated from the simulation. The average structure factors obtained from the simulation confirmed to some extent the relatively high compliance of experimental and simulated Hyp-1 models. We found, however, many outliers between the experimental and simulated side-chain conformations within the Hyp-1 model, which prompted us to propose more reasonable energetically preferred rotameric forms. Therefore, we confirmed that MD simulation may be applicable for the verification of refined, experimental models and the explanation of their structural intricacies.


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