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393 results for “Molecular dynamics simulations”
Molecular dynamics simulation data 1: Structure of the connexin-43 gap junction channel in a putative closed state
<p>Molecular dynamics data for the manuscript Qi C.*, Acosta-Gutierrez S.*, Lavriha P., Othman A., Lopez-Pigozzi D., Bayraktar E., Schuster D., Picotti P., Zamboni N., Bortolozzi M., Gervasio F.L., Korkhov V.M. Structure of the connexin-43 gap junction channel in a putative closed state. eLife (2023) <a href="https://doi.org/10.7554/eLife.87616.2">https://doi.org/10.7554/eLife.87616.2</a></p> <p>The dataset includes:</p> <p>1. The starting coordinates, topology, MD inputs</p> <p>2. Production run gromacs trajectories for the Cx43 gap junction channel</p>
Molecular dynamics simulation based analysis of celecoxib-polymer interactions
<p>This dataset contains scripts and coordinate files for running and analysing molecular dynamics simulations to investigate celecoxib-polymer interactions in aqueous solution. Trajectory files (stripped of water and ions) are included.</p> <p>The associated study is described in:</p> <p>" Comparative analysis of drug-salt-polymer interactions by experiment and molecular simulation improves biopharmaceutical performance", Sumit Mukesh, Goutam Mukherjee, Ridhima Singh, Nathan Steenbuck, Carolina Demidova, Prachi Joshi, Abhay T. Sangamwar, Rebecca C. Wade, submitted.</p>
Molecular dynamics simulations PksD AH
<p>This data set includes topology files, trajectories and force field parameters for non-standard residues for the molecular dynamics simulations discussed in the accompanying manuscript "<strong>Basis for controlled acyl chain hydrolysis in <em>trans</em>-AT polyketide synthases</strong>"</p>
Dataset from "Deciphering the Catalytic Mechanism of Virginiamycin B Lyase with Multiscale Methods and Molecular Dynamics Simulations"
<p>Dataset from "Deciphering the Catalytic Mechanism of Virginiamycin B Lyase with Multiscale Methods and Molecular Dynamics Simulations", containing the most relevant simulation output trajectories ran with GROMACS 2021:</p> <p>1) apo simulations, including wildtype, Y28F, and H228A;<br> 2) holo simulations, including the two tested protonation states for the antibiotic;<br> 3) mutant simulations, including Y18F, H228A, E268Q, and E284Q.</p> <p>All folders contain the topology file (.top), restraint files (.itp), the initial coordinates file (.gro), and the coordinates after the first minimization (em1.gro). The output trajectories of all replicas (per system) have been concatenated in a single compressed file (.xtc).</p>
All Atom Molecular Dynamics Simulations of Lopinavir 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 lopinavir 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 simulations.</p>
Molecular dynamics simulation data of designed cyclic peptide (ligand-only)
<p>Trajectories of <strong>ligand-only </strong>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>
Molecular dynamics simulation data of regulatory ACT domain dimer of human phenylalanine hydroxylase (PAH)
<p>Raw data of molecular dynamics simulations of regulatory ACT domain dimer.</p> <p><strong>binding.zip</strong>: simulation starting from 21 dimer conformations with 19 Phe ligand </p> <p><strong>bound.zip</strong>: simulation starting from dimer with bound Phe ligand</p> <p><strong>dimer.zip</strong>: simulation starting from 21 dimer conformations simulation</p> <p>Simulation setup files are also included in each folder.</p> <p>Details can be found in this paper:</p> <p><strong>Yunhui Ge</strong>, 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 regulatory ACT domain monomer of human phenylalanine hydroxylase (PAH)
<p>Raw data of molecular dynamics simulations of regulatory ACT domain monomer.</p> <p><strong>binding.zip</strong>: simulation starting from 21 monomer conformations with 19 Phe ligand </p> <p><strong>bound.zip</strong>: simulation starting from monomer with bound Phe ligand</p> <p><strong>monomer_only.zip</strong>: simulation starting from 21 monomer conformations simulation</p> <p>Simulation setup files are also included in each folder. Adaptive sampling data are also included in <strong>monomer </strong>and <strong>binding</strong> simulations.</p> <p>Details can be found in this paper:</p> <p><strong>Yunhui Ge</strong>, 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 β-hairpins
<p>Raw simulations data (protein only) and simulation set-up files of designed β-hairpins. More details can be found in this paper: </p> <p>Yunhui Ge, Brandon Kier, Niels H. Andersen and Vincent A. Voelz. <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.7b00132"><em>Computational and experimental evaluation of designed beta-cap hairpins using molecular simulations and kinetic network models.</em></a> J. Chem. Inf. Model., 2017, 57 (7), pp 1609–1620</p>
Replica exchange molecular dynamics simulation data of designed β-hairpins (implicit solvent, AMBER ff96)
<p>Raw REMD simulation data (protein only) of designed β-hairpins. AMBER ff96 and implicit solvent model is used. More details can be found in this paper: </p> <p>Yunhui Ge, Brandon Kier, Niels H. Andersen and Vincent A. Voelz. <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.7b00132"><em>Computational and experimental evaluation of designed beta-cap hairpins using molecular simulations and kinetic network models.</em></a> J. Chem. Inf. Model., 2017, 57 (7), pp 1609–1620</p>
Replica exchange molecular dynamics simulation data of designed β-hairpins (implicit solvent, AMBER ff99SB-ildn)
<p>Raw REMD simulation data (protein only) of designed β-hairpins. AMBER ff99SB-ildn and implicit solvent model is used. More details can be found in this paper: </p> <p>Yunhui Ge, Brandon Kier, Niels H. Andersen and Vincent A. Voelz. <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.7b00132"><em>Computational and experimental evaluation of designed beta-cap hairpins using molecular simulations and kinetic network models.</em></a> J. Chem. Inf. Model., 2017, 57 (7), pp 1609–1620</p>
All-atom Molecular Dynamics Simulations of SARS-CoV-2 Spike Receptor-binding Domain bound with ACE2
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of of SARS-CoV2 Spike Protein/ACE2 complex (PDB ID: 6M0J). In order to decrease the size of the file only protein rajectories were provided. Simulation has been performed with Desmond. Protein 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 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 simulation.</p>
Simulation trajectories for the article "Molecular conformation and bilayer pores in a nonionic surfactant lamellar phase studies with 13C-1H solid-state NMR and molecular dynamics simulations"
<p>Simulation trajectories for the article "Molecular conformation and bilayer pores in a nonionic surfactant lamellar phase studies with 1H-13C solid-state NMR and molecular dynamics simulations" Langmuir 2014, 30 (2), pp 461–469 http://dx.doi.org/10.1021/la404684r</p> <p>System: 80 wt% C12E5, T=298K</p> <p>Other files available: http://dx.doi.org/10.6084/m9.figshare.861071</p>
Gaussian-accelerated Molecular Dynamics simulations of CCR8-CCL1-Gprotein complex in a POPC lipid bilayer
<p>Gaussian-accelerated Molecular Dynamics simulations of the CCR8-CCL1-Gprotein complex in a POPC lipid bilayer. Simulation system was prepared with OpenMM v7.7 and simulations were performed using the GaMD-OpenMM package (https://github.com/MiaoLab20/gamd-openmm) with a modification to include the MDTraj h5 file formate reporter as the output file format. These simulations were then converted to pdb topologies and dcd trajectories using MDTraj. </p><p>Files include:</p><p>CCL1_CCR8_noSer23_oriented_repaired1_system.pdb : system topology</p><p>CCL1_CCR8_config.xml : config for running GaMD-OpenMM</p><p>CCL1_CCR8_N_1ns_imaged_structure.pdb : initial topology/structure</p><p>CCL1_CCR8_N_1ns_imaged_trajectory.dcd : trajectory file</p><p> </p><p>Simulations can be loaded in python using MDTraj:</p><p>import mdtraj</p><p>trj = mdtraj.load(<dcd file>, top=<pdb file>)</p>
Molecular dynamics simulation of human ρ1 GABAA receptor with neurosteriod pregnenolone sulfate
<p>Molecular dynamics simulation trajectory, parameter files for the systems of human ρ1 GABAA receptor with neurosteriod pregnenolone sulfate. Pregnenolone sulfate was tested with two different poses, either sulfate group "up" or "down".</p> <p> </p>
How Binding Site Flexibility Promotes RNA Scanning in TbRGG2 RRM: A Molecular Dynamics Simulation Study
<p>The data necessary to independently reproduce the MD simulations and the first part of the simulation trajectories reported in the paper "<strong>How Binding Site Flexibility Promotes RNA Scanning in TbRGG2 RRM: A Molecular Dynamics Simulation Study</strong>", by Lemmens et al.</p> <p>Due to Zenodo data deposition limits, every 10th frame of the MD simulation trajectories is included. Due to Zenodo deposition limits, MD trajectory files for this paper are also available at 10.5281/zenodo.14260246.</p>
An estimate for thermal diffusivity in highly irradiated tungsten using Molecular Dynamics simulation
<p>The changing thermal conductivity of an irradiated material is among the principal design considerations for any nuclear reactor, but at present few models are capable of predicting these changes starting from an arbitrary atomistic model. Here we present a simple model for computing the thermal diffusivity of tungsten, based on the conductivity of the perfect crystal and resistivity per Frenkel pair, and dividing a simulation into perfect and athermal regions statistically. This is applied to highly irradiated microstructures simulated with Molecular Dynamics. A comparison to experiment shows that simulations closely track observed thermal diffusivity over a range of doses from the dilute limit of a few Frenkel pairs to the high dose saturation limit at 3 displacements per atom (dpa).<br> </p>
All-atom Molecular Dynamics Simulations of Meiosis 1-associated protein (M1AP) to Investagate the Impact of Known Missense Mutations Associated with Male Infertility through Non-obstructive Azoospermia
<p>Protein structure of meiosis 1-associated protein (M1AP) was modelled by using GalaxyWeb (from Seok Lab). We used this model to investigate the impact of variants (i.e., S50P, R266Q, P389L, G317R, and L430P) in M1AP which were recently associated with non-obstructive azoospermia (NOA). NOA is a male infertility-related condition causing absence of sperm in the seminal fluid due to meiosis failure. We aimed to elucidate the pathogenicity mechanisms of these five missense NOA-related mutations on M1AP by performing molecular modeling and molecular dynamics (MD) simulations. This dataset includes the results of 1000 ns MD simulations (two repeats, each 500 ns) for each of the mutant and wild-type systems.</p> <p>Systems were prepared in Visual Molecular Dynamics (VMD 1.9.3) by placing them in a TIP3P water box with approximately 20 Å thickness from the protein surface and neutralizing the system charge with 0.15 M KCl. Of note, only protein parts were kept for the submission to reduce the size of files. Nanoscale Molecular Dynamics (NAMD 2.13-CUDA) was used to perform MD simulations with CHARMM36m force field. For pressure and temperature controls, Nosé-Hoover Langevin barostat and Langevin thermostat were used. ShakeH algorithm of NAMD was applied for water molecule constraints. 12 Å cut-off distance was used for van der Waals interactions. Switching function starts at 10 Å and reaches zero at 14 Å. Integration time-step was 2 fs. To compute the long-range Coulomb interactions, the particle-mash Ewald method was used. NPT ensemble was applied for whole simulations. Two step minimization & equilibration procedure was performed: (1) 5,000-step minimization and 1 ns equilibrium with constraints on the protein; (2) 5,000-step minimization and 1 ns equilibrium without the constraints on the protein. All related configuration files for wild-type system were also included to the dataset. Production simulations were run twice along 500 ns by using different random seeds to assign the velocities from Boltzmann distribution (total simulation time for each system was 1000 ns, which are given as 500 ns repeat 1, and 500 ns repeat 2). The production simulations were supplied in the dataset. "out" and "log" files were used for energy analysis.</p> <p>For all analysis scripts, see https://github.com/ugerlevik/M1AP_analysis.</p>
Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations
<p>MD simulations used in the studies of the publication "<strong>Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations</strong>"</p>
Data of curvature model for the study of nanoparticle size effects on amyloid fibril stability and molecular dynamics simulations data
<p>The data provided refer to our published article:</p> <p>T. John, J. Adler, C. Elsner, J. Petzold, M. Krueger, L.L. Martin, D. Huster, H.J. Risselada, B. Abel, Mechanistic insights into the size-dependent effects of nanoparticles on inhibiting and accelerating amyloid fibril formation, J. Colloid Interface Sci. 622 (2022), 804–818. <a href="https://doi.org/10.1016/j.jcis.2022.04.134">https://doi.org/10.1016/j.jcis.2022.04.134</a></p> <p>This article is accompanied by a 'Data in Brief' article that explains in more detail the use of the curvature model and our molecular dynamics (MD) simulations:</p> <p>T. John, L.L. Martin, H.J. Risselada, B. Abel, Curvature model for nanoparticle size effects on peptide fibril stability and molecular dynamics simulation data, Data Brief 45 (2022), 108598. <a href="https://doi.org/10.1016/j.dib.2022.108598">https://doi.org/10.1016/j.dib.2022.108598</a></p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.