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393 results for “Molecular dynamics simulations”
Atomistic Picture of Opening-Closing Dynamics of DNA Holliday Junction Obtained by Molecular Simulations: Simulations Topology, Coordinate, Parameters, Input and Output files
<p>The simulation data for the article: Atomistic Picture of Opening-Closing Dynamics of DNA Holliday Junction Obtained by Molecular Simulations.</p> <p>ck_metad.tar.gz: Includes the topology files, coordinates files and gromacs parameter input file (.mdp) used for WT-MetaD-HREX simulations with different c(K+), which are newly added runs for resubmission. The corresponding script files and Plumed files are in GitHub.</p> <p>eq_mini.tar.gz: Includes the parameter files required for the equilibration and minimization protocol.</p> <p>standard_md.tar.gz: Includes the topology files and coordinate files for all systems built in the article. Also include the hbfix parameters file required on the MD run, and the MD script file.</p> <p>metad.tar.gz: Includes the topology files, coordinates files and gromacs parameter input file (.mdp) used for WT-MetaD-HREX simulations. The corresponding script files and Plumed files are in GitHub.</p> <p>metad*fe*.tar.gz: Plumed HILLS files and metad.bias data used for drawing the free energy landscapes.</p> <p>ions.tar.gz: Data used for Figure.3 in the manuscript</p> <p>si_data.tar.gz: All data used for SI figures.</p>
Data set for graphene/GO polymer molecular dynamics simulation
<p>Lammps input files and log files for molecular dynamics simulations of graphene and graphene-oxide nano ribbons for paper "Molecular dynamics reveals the origin of the enhancement of polymer properties by graphene". Log files include stress-strain behaviour during uniaxial strain. </p> <p> </p>
Charge Transport in Water-NaCl Electrolytes with Molecular Dynamics Simulations
<p>LAMMPS input-file, and log-files used in "Charge Transport in Water-NaCl Electrolytes with Molecular Dynamics Simulations"</p> <p> </p> <p>DOI: 10.1021/acs.jpcb.2c08047</p>
Surface tension coefficient of acqueous glycerol from Molecular Dynamics simulations
<p>The dataset contains the configuration files and the results of molecular simulations of aqueous glycerol liquid slabs. The aim of the simulations is to determine the surface tension of the interface between aqueous glycerol and its vapour. Simulations are performed with Gromacs 2021. The water model is SPC/E, while the force field for Glycerol is extrapolated from OPLS-AA according to the work by Jahn et al. (<a href="https://doi.org/10.1021/jp5059098">doi.org/10.1021/jp5059098</a>). Surface tension is computed using Gromacs analysis tool by running</p> <pre><code>gmx energy -f ener.edr</code></pre> <p>and selecting the #Surf*SurfTen term, which returns the surface tension (bar*nm) times the number of surfaces (2, due to the system's periodicity). The surface tension is computed from the difference between interface-perpendicular and interface-parallel components of the pressure tensor (see Gromacs documentation or Frenkel and Smit <em>Understanding Molecular Simulations </em>second edition p.472).</p> <p>The nomenclature of the zip files indicates the mass fraction of glycerol, ranging from 0% (Glycerol000) to 100% (Glycerol100).</p>
Molecular Dynamics simulations of acqueous glycerol spreading on a silica-like surface
<p>This dataset contains the results of Molecular Dynamics simulations of quasi-2D water-glycerol liquid droplets, spreading on silica-like surfaces. The goal of the simulations is to quantify the contact line friction coefficient by regressing over the dynamic contact angle and the contact line speed.</p> <p>The pattern "Glycerol***" refers to the mass fraction of glycerol ("000": pure water, "100": pure glycerol). Each folder contains configuration files and compressed output molecular trajectories. The contact angle and the contact line speed are computed from density maps binned on-the-fly using a customized Gromacs version (<a href="https://github.com/pjohansson/gromacs-flow-field">https://github.com/pjohansson/gromacs-flow-field</a>); frames are placed in a tarball ("spread-*p-r1.tar.gz").</p> <p>The zipped folder 'scripts.zip' contains a self-contained library of functions to read density maps and a Jupyter notebook with an example of density reading and plotting.</p> <p>Simulations are performed with Gromacs. We refer to the code documentation for further information (<a href="https://manual.gromacs.org/">https://manual.gromacs.org/</a>).</p>
The files for "RlmI-c-di-GMP" molecular dynamics simulation
<p>The crystal structure files (protein RlmI), MD simulation files (input files, parameter files, topology files etc) and structures of c-Di-GMP.</p>
Introduction to HPC: molecular dynamics simulations with GROMACS: input files
<p>Introduction to HPC: molecular dynamics simulations with GROMACS: input files</p>
Identification of novel NLRP3 Inhibitors a comprehensive approach using 2D-QSAR, molecular docking, molecular dynamics simulation and drug-likeness evaluation
<p>This dataset encapsulates the comprehensive outputs derived from molecular docking and molecular dynamics (MD) simulation studies conducted to investigate the binding affinities, interactions, and dynamic behaviors of selected ligands with NLRP3.</p>
Using Molecular Dynamics Simulations to Interrogate T Cell Receptor Non-Equilibrium Kinetics
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Interaction between cytochrome c and DNA: conformation, peroxidase activity and molecular dynamics simulation
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Data from: Molecular dynamics simulation of the interaction between palmitic acid and high pressure CO2
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Supporting data: Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?
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Molecular dynamics simulations of the tripartite interface (Syt1_C2B—SNARE—Cpx Complex)
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Role of black carbon in the formation of primary organic aerosols: Insights from molecular dynamics simulations: Supplementary Materials
<p>This zip file contains supplements for the article entitled "Role of black carbon in the formation of primary organic aerosols: Insights from molecular dynamics simulations" authored by Zhou et al. including three different sets of data as follows:</p> <p>data: Data files that contain optimized atomistic configurations of organic molecules adsorbed on nanoparticles are provided. These .xyz files contain the atomic coordinates of the adsorbed organic molecules. The first line in each file contains the total number of atoms, the second line comprises three integers corresponding to the number of molecules, number of atoms in each molecule and number of atoms in the nanoparticle, and each subsequent line contains the atomic species and the three Cartesian coordinates (in Angstrom) for an atom. Please see the PDF in the directory for instructions.</p> <p>code: Sets of Lammps simulation input scripts.</p> <p>video: Supplements demonstrating the formation process of molecular clusters of these simulations.</p>
All Atom Molecular Dynamics Simulations of Ritonavir at the Binding Pocket of SARS-CoV2 Main Protease
<p>Data includes all of the trajectories (2000) of classical all-atom molecular dynamics (MD) simulations of ritonavir at the binding pocket of SARS-CoV2 main protease target. In order to decrease the size of the file only protein and ligand trajectories were provided. Simulation has been performed with Desmond. Protein–ligand complexes were obtained by Glide/SP docking program. Complex was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff<br> radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 500 ns production run was performed for the simulation.</p> <p> </p>
All Atom Molecular Dynamics Simulations of inhibitor N3 at the binding pocket of SARS-CoV2 Main Protease (PDB ID: 6LU7)
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of inhibitor N3 at the binding pocket of SARS-CoV2 main protease target (PDB ID: 6LU7). In order to decrease the size of the file only protein and ligand trajectories were provided. Simulation has been performed with Desmond. Protein–ligand complexes were obtained from RCSB PDB (PDB ID: 6LU7). Complex was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff<br> radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 100 ns production run was performed for the simulations.</p>
Molecular dynamics simulation data of regulatory ACT domain dimer of human phenylalanine hydroxylase (PAH) (with unbound ligand)
<p>Raw data of molecular dynamics simulations of regulatory ACT domain dimer with unbound ligands. Simulation starts from the crystal pose (PDB: 5FII) and is motivated by this paper:</p> <p>Yunhui Ge, Elias Borne, Shannon Stewart, Michael R. Hansen, Emilia C. Arturo, Eileen K. Jaffe and Vincent A. Voelz. <a href="http://www.jbc.org/content/293/51/19532"><em>Simulation of the regulatory ACT domain of human PAH unveil the mechanism of phenylalanine binding.</em></a> J. Biol. Chem., 2018, 293(51), pp 19532-19543</p>
Molecular dynamics simulation data of designed cyclic peptide (ligand-binding)
<p>Trajectories of ligand binding simulation and simulation set-up files of designed cyclic peptide as MDM2 binders. <br> The original paper of these designed cyclic peptide: Danelius, E., Pettersson, M., Bred, M., Min, J., Waddell, M. B., Guy, R. K., et al. (2016). Flexibility is important for inhibition of the MDM2/p53 protein–protein interaction by cyclic β-hairpins. <em>Org. Biomol. Chem.</em>, <em>14</em>(44), 10386–10393. http://doi.org/10.1039/C6OB01510G</p>
Input files and scripts for Hamiltonian replica-exchange molecular dynamics simulations of intrinsically disordered proteins using a software GROMACS patched with PLUMED
<p>Here we share the necessary files and scripts to run Hamiltonian replica-exchange molecular dynamics simulations of intrinsically disordered protein studied in the preprint uploaded to bioRxiv (doi: https://doi.org/10.1101/2020.06.16.155374). It requires software GROMACS patched with PLUMED.</p>
Predicting Hydrophobicity by Learning Spatiotemporal Features of Interfacial Water Structure: Combining Molecular Dynamics Simulations with Convolutional Neural Networks
<p>Files for reproducing results from Kelkar et al. (JPCB 2020) - Predicting Hydrophobicity by Learning Spatiotemporal Features of Interfacial Water Structure: Combining Molecular Dynamics Simulations with Convolutional Neural Networks</p> <p> </p> <p>This folder contains simulations starter files and also plug-and-play datasets to test ML algorithms on molecular dynamics (MD) simulation data.</p> <p> </p> <p>All analysis scripts can also be found on GitLab on this link: https://gitlab.com/atharva-kelkar/kelkar_et_al_jpcb_2020</p>
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