scholarly journals Constructing 3-Dimensional Atomic-Resolution Models of Nonsulfated Glycosaminoglycans with Arbitrary Lengths Using Conformations from Molecular Dynamics

2020 ◽  
Vol 21 (20) ◽  
pp. 7699 ◽  
Author(s):  
Elizabeth K. Whitmore ◽  
Devon Martin ◽  
Olgun Guvench
Keyword(s):  
Molecular Dynamics ◽  
Md Simulation ◽  
Md Simulations ◽  
Atomic Resolution ◽  
Dihedral Angles ◽  
Backbone Flexibility ◽  
Arbitrary Length ◽  
3 Dimensional ◽  
Conformational Ensembles ◽  
Carbohydrate Components

Glycosaminoglycans (GAGs) are the linear carbohydrate components of proteoglycans (PGs) and are key mediators in the bioactivity of PGs in animal tissue. GAGs are heterogeneous, conformationally complex, and polydisperse, containing up to 200 monosaccharide units. These complexities make studying GAG conformation a challenge for existing experimental and computational methods. We previously described an algorithm we developed that applies conformational parameters (i.e., all bond lengths, bond angles, and dihedral angles) from molecular dynamics (MD) simulations of nonsulfated chondroitin GAG 20-mers to construct 3-D atomic-resolution models of nonsulfated chondroitin GAGs of arbitrary length. In the current study, we applied our algorithm to other GAGs, including hyaluronan and nonsulfated forms of dermatan, keratan, and heparan and expanded our database of MD-generated GAG conformations. Here, we show that individual glycosidic linkages and monosaccharide rings in 10- and 20-mers of hyaluronan and nonsulfated dermatan, keratan, and heparan behave randomly and independently in MD simulation and, therefore, using a database of MD-generated 20-mer conformations, that our algorithm can construct conformational ensembles of 10- and 20-mers of various GAG types that accurately represent the backbone flexibility seen in MD simulations. Furthermore, our algorithm efficiently constructs conformational ensembles of GAG 200-mers that we would reasonably expect from MD simulations.

scholarly journals Efficient Construction of Atomic-Resolution Models of Non-Sulfated Chondroitin Glycosaminoglycan Using Molecular Dynamics Data

Biomolecules ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 537 ◽  
Author(s):  
Elizabeth K. Whitmore ◽  
Gabriel Vesenka ◽  
Hanna Sihler ◽  
Olgun Guvench
Keyword(s):  
Molecular Dynamics ◽  
Computational Cost ◽  
Md Simulations ◽  
Atomic Resolution ◽  
Backbone Flexibility ◽  
Arbitrary Length ◽  
Internal Validation ◽  
Carbohydrate Polymers ◽  
Distance Distributions ◽  
End Distance

Glycosaminoglycans (GAGs) are linear, structurally diverse, conformationally complex carbohydrate polymers that may contain up to 200 monosaccharides. These characteristics present a challenge for studying GAG conformational thermodynamics at atomic resolution using existing experimental methods. Molecular dynamics (MD) simulations can overcome this challenge but are only feasible for short GAG polymers. To address this problem, we developed an algorithm that applies all conformational parameters contributing to GAG backbone flexibility (i.e., bond lengths, bond angles, and dihedral angles) from unbiased all-atom explicit-solvent MD simulations of short GAG polymers to rapidly construct models of GAGs of arbitrary length. The algorithm was used to generate non-sulfated chondroitin 10- and 20-mer ensembles which were compared to MD-generated ensembles for internal validation. End-to-end distance distributions in constructed and MD-generated ensembles have minimal differences, suggesting that our algorithm produces conformational ensembles that mimic the backbone flexibility seen in simulation. Non-sulfated chondroitin 100- and 200-mer ensembles were constructed within a day, demonstrating the efficiency of the algorithm and reduction in time and computational cost compared to simulation.

scholarly journals Fully Atomistic Molecular Dynamics Computation of Physico-Mechanical Properties of PB, PS, and SBS

Nanomaterials ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 1088 ◽  
Author(s):  
Yang Kang ◽  
Dunhong Zhou ◽  
Qiang Wu ◽  
Fuyan Duan ◽  
Rufang Yao ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Strain Rate ◽  
Strain Hardening ◽  
Md Simulation ◽  
Md Simulations ◽  
Strain Rates ◽  
Young’S Moduli ◽  
Plastic Modulus ◽  
Styrene Butadiene ◽  
Butadiene Styrene

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.

A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: probing the binding pathway of dasatinib to Src-kinase

2020 ◽  
Vol 36 (18) ◽  
pp. 4714-4720
Author(s):  
Farzin Sohraby ◽  
Mostafa Javaheri Moghadam ◽  
Masoud Aliyar ◽  
Hassan Aryapour
Keyword(s):  
Molecular Dynamics ◽  
Ligand Binding ◽  
Md Simulation ◽  
Src Kinase ◽  
Deep Understanding ◽  
Md Simulations ◽  
Binding Mode ◽  
Supplementary Information ◽  
Computational Resources ◽  
Binding Mechanisms

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.

Surface Tension Evaluation Via Thermodynamic Analysis of Statistical Data From Molecular Dynamics Simulations

Volume 4 ◽  
2004 ◽  
Author(s):  
Aaron P. Wemhoff ◽  
Van P. Carey
Keyword(s):  
Molecular Dynamics ◽  
Surface Tension ◽  
Density Profile ◽  
Md Simulation ◽  
Md Simulations ◽  
Bulk Liquid ◽  
Interfacial Region ◽  
Lennard Jones Potential ◽  
Jones Potential ◽  
Lennard Jones

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.

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

2021 ◽  
Author(s):  
Jonathan Vandersluis
Keyword(s):  
Molecular Dynamics ◽  
Finite Element ◽  
Md Simulation ◽  
Computational Simulation ◽  
Md Simulations ◽  
Single Step ◽  
Depth Interval ◽  
Simulation Tool ◽  
Custom Made ◽  
Computational Resources

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.

scholarly journals Neural relational inference to learn allosteric long-range interactions in proteins from molecular dynamics simulations

2021 ◽  
Author(s):  
Jingxuan Zhu ◽  
Juexin Wang ◽  
Weiwei Han ◽  
Dong Xu
Keyword(s):  
Molecular Dynamics ◽  
Long Range ◽  
Md Simulation ◽  
Biological Process ◽  
Dynamic Networks ◽  
Md Simulations ◽  
Amino Acid Mutation ◽  
Long Range Interactions ◽  
Decoder Architecture ◽  
Dynamics Simulations

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.

STUDY OF AFFINITIES BETWEEN SINGLE-WALLED NANOTUBE AND EPOXY RESIN USING MOLECULAR DYNAMICS SIMULATION

2006 ◽  
Vol 05 (01) ◽  
pp. 131-144 ◽  
Author(s):  
JIHUA GOU ◽  
BIN FAN ◽  
GANGBING SONG ◽  
AURANGZEB KHAN
Keyword(s):  
Molecular Dynamics ◽  
Epoxy Resin ◽  
Md Simulation ◽  
Average Distance ◽  
Md Simulations ◽  
Dynamics Simulation ◽  
Repulsive Interaction ◽  
Curing Agent ◽  
Single Walled Nanotubes ◽  
Simulation Results

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.

scholarly journals A New Algorithm for Contact Angle Estimation in Molecular Dynamics Simulations

2015 ◽  
Author(s):  
Sumith Yd ◽  
Shalabh C. Maroo
Keyword(s):  
Molecular Dynamics ◽  
Contact Angle ◽  
Md Simulation ◽  
Spline Interpolation ◽  
Vertical Axis ◽  
Md Simulations ◽  
Computationally Efficient ◽  
B Spline ◽  
Wetting Properties ◽  
Dynamics Simulations

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.

scholarly journals Molecular Dynamics Investigation of Phenolic Oxidative Coupling Protein Hyp-1 Derived from Hypericum perforatum

Crystals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 43
Author(s):  
Joanna Smietanska ◽  
Tomasz Kozik ◽  
Radoslaw Strzalka ◽  
Ireneusz Buganski ◽  
Janusz Wolny
Keyword(s):  
Molecular Dynamics ◽  
Md Simulation ◽  
Hypericum Perforatum ◽  
Structural Model ◽  
Md Simulations ◽  
Atomic Displacement ◽  
Experimental Models ◽  
Coupling Protein ◽  
Atomic Displacement Parameters ◽  
Chain Conformations

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.

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

2021 ◽  
Author(s):  
Jonathan Vandersluis
Keyword(s):  
Molecular Dynamics ◽  
Finite Element ◽  
Md Simulation ◽  
Computational Simulation ◽  
Md Simulations ◽  
Single Step ◽  
Depth Interval ◽  
Simulation Tool ◽  
Custom Made ◽  
Computational Resources

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.

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