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140 results for “molecular dynamics data”
Kreysing_et_al_2024_molecular_dynamics_simulation_data
<p>The molecular dynamics simulation data set accompanying Kreysing et al, 2024, containing (i) representative coordinates and measurements described therein, (ii) selected simulation trajectories, and (iii) LAMMPS input files.</p>
Data for 'Ranking Single Fluorescent Protein Based Calcium Biosensor Performance by Molecular Dynamics Simulations'
<h2>Melike Berksoz, Canan Atilgan* </h2> <h3>Faculty of Engineering and Natural Sciences, Sabanci University </h3> <p><strong>*Correspondance:</strong> Canan Atilgan, Faculty of Natural Sciences and Engineering, Sabancı University, Tuzla 34956 Istanbul, Türkiye, E-mail: canan@sabanciuniv.edu</p> <p>Genetically Encoded Fluorescent Biosensors (GEFBs) have become indispensable tools for visualizing biological processes <em>in</em> <em>vivo.</em> A typical GEFB is composed of a sensory domain (SD) which undergoes a conformational change upon ligand binding and a genetically fused fluorescent protein (FP). Ligand binding in the SD allosterically modulates the chromophore environment and changes its spectral properties. Single fluorescent (FP)-based biosensors, a subclass of GEFBs, offer a simple experimental setup; they are easy to produce in living cells, structurally stable and simple due to their single-wavelength operation. However, they pose a significant challenge for structure optimization, especially concerning the length and residue content of linkers between the FP and SD which effect how well the chromophore responds to conformational change in the SD. In this work, we use classical all-atom molecular dynamics simulations to analyze the dynamic properties of a series of calmodulin-based calcium biosensors, all with different FP-SD interaction interfaces and varying degrees of calcium binding dependent fluorescence change. Our results indicate that biosensor performance can be predicted based on distribution of water molecules around the chromophore and shifts in hydrogen bond occupancies between the ligand-bound and ligand-free sensor structures.</p> <p>Hydrogen bond occupancies were calculated with merging_bonds.py script. Double counted hydrogen bonds where a residue acts both as acceptor and donor are merged into a single entry with merge_files.py. To run sasa.tcl, you need VMD software. Trajectories were created with NAMD2 with a dcdfrequency of 5000 timesteps (every 10 ps) and strided in a 1:100 ratio (every 1 ns=1 frame in dcd). </p>
Research Data for "Molecular Dynamics Study of Structure and Reactions at the Hydroxylated Mg(0001)/Bulk Water Interface"
<p>This folder contains data used in the paper "Molecular Dynamics Study of Structure and Reactions at the Hydroxylated Mg(0001)/Bulk Water Interface" (Title subject to change). Some details on the structure are as follows:</p> <p>The folder "figures" contains data to create various figures in the main paper. Each file contains a json object, where keys "0", "1", etc. refer to the 1st/2nd subplot for a figure. The values are then another json object with the data used to create the relevant plot; the most useful of which is the "data" key which contains the plot data.</p> <p>The folder "md_traj" contains the molecular dynamics trajectory. The file "traj.exyz" is a standard format which can be opened with various software. "traj.json" contains the same information in an in-house format used by the author. The "thermo_data.json" contains various thermodynamics properties over the simulation, such as temperatures and kinetic energies. Units are femtoseconds, Angstrom, electron-volts and Kelvin.</p> <p>The folder "react_traj" contains trajectories in the same formats as "md_traj", but each are limited to time-windows where reactions occurred (so each trajectory will only be hundreds of femtoseconds long at most). The subfolder "full_traj" contains the trajectories with all atoms present, whilst "trimmed_traj" contains trajectories with most atoms removed (the atoms included are those nearest the reaction).We include these "trimmed_traj" files as it is difficult to find the reacting molecules when visualising all atoms in the simulation.</p> <p>The folder "opt_geoms" contains geometries for various structures used in the paper (in *.exyz format). These also contain *.json files; these contain information on how the calculations were carried out in a format used by the author (they are small files primarily included for the benefit of the author).</p> <p> </p> <p> </p>
CG molecular dynamics simulations. Supporting data for "Improving Martini 3 for Disordered and Multidomain Proteins".
<pre>Coarse-grained molecular dynamics simulations with Martini 3 with varying rescaling of protein-water interactions. Supporting data for "Improving Martini 3 for Disordered and Multidomain Proteins".</pre>
Molecular dynamics simulation trajectory data for "Permeability and ammonia selectivity in aquaporin TIP2;1: linking structure to function"
<p>Trajectories and input files corresponding to entries in Supplementary Table S1.</p>
Molecular dynamics simulation data of the manuscript "KnowVolution of an efficient polyamidase through molecular dynamics simulations of incrementally docked oligomeric substrates"
<p>This repository provides the simulation data as well as the input and parameters files to reproduce our findings.</p> <p><strong>Acknowledgments</strong></p> <p>The authors gratefully acknowledge the computing time provided by RWTH Aachen University. Computations were performed with computing resources granted by RWTH Aachen University under project rwth1584.</p>
DFT data from article "Oxide Ion Mobility in V- and P-doped Bi2O3-Based Solid Electrolytes: Combining Quasielastic Neutron Scattering with Ab Initio Molecular Dynamics"
<p>DFT data from article: "Oxide Ion Mobility in V- and P-doped Bi2O3-Based Solid Electrolytes: Combining Quasielastic Neutron Scattering with Ab Initio Molecular Dynamics" (<span><a href="https://pubs.acs.org/doi/full/10.1021/acs.chemmater.2c03103">https://pubs.acs.org/doi/full/10.1021/acs.chemmater.2c03103</a>). Published by 'creators' listed above. </span></p>
Molecular Dynamics simulation data of Cyt c at pH 7 at the water|TFT interface
<p>Programmed cell death via apoptosis is a natural defence against excessive cell division, crucial for foetal development to maintenance of homeostasis and elimination of precancerous and senescent cells. Here we demonstrate an electrified liquid bio-interface that replicates the molecular machinery of the inner mitochondrial membrane at the onset of apoptosis. By mimicking in vivo cytochrome c (Cyt c) interactions with cell membranes, our platform allows us to modulate the conformational plasticity of the protein by simply varying the electrochemical environment at an aqueous|organic interface. Remarkably, we observe interfacial electron transfer between an organic electron donor decamethylferrocene and O2, electrocatalysed by Cyt c. This interfacial reaction requires partial Cyt c unfolding, mimicking Cyt c in vivo peroxidase activity. As proof-of-concept, we use our electrified liquid bio-interface to identify drug molecules, such as bifonazole, that can potentially downregulate Cyt c and protect against uncontrolled neuronal cell death in neurodegenerative disorders.</p>
Data set of the article "Comparative analysis of the unbinding pathways of antiviral drug Indinavir from HIV and HTLV1 proteases by supervised molecular dynamics simulation"
<p>Data set of the article "Comparative analysis of the unbinding pathways of antiviral drug Indinavir from HIV and HTLV1 proteases by supervised molecular dynamics simulation"</p>
Jensen_etal_2022_molecular_dynamics_simulation_data
<p>Full molecular dynamics simulation data set accompanying Jensen et al, 2022, containing (i) representative coordinates and measurements described therein, (ii) simulation trajectories, and (iii) GROMACS input files.</p>
Yu_et_al_2023_molecular_dynamics_simulation_data
<p>The molecular dynamics simulation data set accompanying Yu et al, 2023, containing (i) representative coordinates and measurements described therein, (ii) selected simulation trajectories, and (iii) LAMMPS input files.</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>
Zr–O Ab Initio Training Data Created by Molecular Dynamics, Contour Exploration, and Dimer Searches
<p> These density functional theory calculations span a diverse set of structures in the Zr–O system which was used as machine-learned interatomic potential (MLIP) training data. This data set was used to benchmark different structural evolution methods (molecular dynamics, contour exploration, and dimer searches) for the quality and accuracy of MLIPs trained on them. The data is provided in the .traj format from ASE. Along with data set used in our publication, we provide a large set of extra unused data and a small Python script example for parsing the data set. The set contains 120,068 structures which contain a total of 3,154,158 atoms.</p> <p>For more details, please see our paper:<br> Michael J Waters and James M Rondinelli, <em>J. Phys.: Condens. Matter</em> <strong>34</strong> 385901(2022) (<a href="https://dx.doi.org/10.1088/1361-648X/ac7f73">https://dx.doi.org/10.1088/1361-648X/ac7f73</a>)</p>
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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Data from: A molecular phylogeny of forktail damselflies (genus Ischnura) reveals a dynamic macroevolutionary history of female colour polymorphisms
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Data from: Molecular ecology of the Neotropical otter (Lontra longicaudis): non-invasive sampling yields insights into local population dynamics
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Data from: Molecular docking and dynamics studies to identify novel active compounds targeting potential breast cancer receptor proteins from an indigenous herb Euphorbia thymifolia Linn
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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>
Complementary data to "Molecular dynamics trajectories for 630 drug-membrane potentials of mean force"
<p>Missing data from "Molecular dynamics trajectories for 630 drug-membrane potentials of mean force"</p> <p>Hoffmann, Christian; Centi, Alessia; Menichetti, Roberto; Bereau, Tristan (2020): Molecular dynamics trajectories for 630 drug-membrane potentials of mean force. figshare. Collection.</p> <p>https://doi.org/10.6084/m9.figshare.c.4641551.v1</p> <p>Includes:</p> <ul> <li>'bsResult.xvg' of DIM_P2-P3 in DLPC</li> </ul>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.