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691 results for “Molecular dynamics”
Molecular Dynamics Simulation of MC-congeners in complex with PPP1 - Replicate 1
<p>This data sets contains Molecular Dynamics (MD) Simulation files and analysis. Microcystin (MC) congeners were simulated in solvent (water) and in complex with protein phosphatase 1 (PPP1). MD Simulation was repeated for three times. This data is replicate 1 and related data sets are available.</p> <p>Please cite the original publication when using all or part of the data:</p> <p>S. Jaeger-Honz, J. Nitschke, S. Altaner, K. Klein, D. R. Dietrich, F. Schreiber:<a href="https://doi.org/10.1016/j.cbi.2021.109766"> Investigation of microcystin conformation and binding towards PPP1 by molecular dynamics simulation</a>. <em>Chemico-Biological Interactions</em>, 2021</p>
Molecular Dynamics of SARS-CoV-2 Delta Variant Receptor Binding Domain in Complex with ACE2 Receptor
<p>Molecular dynamics simulation for 10 ns at 37 C degrees of SARS-CoV-2 delta variant. Performed with NAMD and visualized/analyzed in ChimeraX software using Frontera supercomputer from Texas Advanced Computing Center. By Victor Padilla-Sanchez, PhD.</p> <p>https://www.youtube.com/watch?v=8N_MjWwxbMQ</p>
Supplementary Data for "Molecular dynamics simulations provide structural insight into binding of cyclic dinucleotides to human STING protein"
<p>Supplementary Data for "Molecular dynamics simulations provide structural insight into binding of cyclic dinucleotides to human STING protein", Journal of Biomolecular Structure and Dynamics, 2021, 10.1080/07391102.2021.1942213</p> <p>A random selection of 10 representative structures from each MSM state of STING/CDN complexes is provided in .pdb file format. The selected MSM representatives are aligned and available as PyMOL session files.</p>
Nanoporous carbon structures of different densities generated through GAP molecular dynamics
<p>These nanoporous (NP) carbon atomic structures, in extendend XYZ format, have been generated using a melt-graphitization-quench molecular dynamics (MD) protocol using a Gaussian interatomic potential (GAP) for amorphous carbon [1]. Simulation details and characterization of structural and mechanical properties will follow shortly in a scientific paper.</p> <p><strong>References</strong></p> <p>[1] M.A. Caro. GAP interatomic potential for amorphous carbon (2.0) [Data set]. Zenodo, 10.5281/zenodo.5243184 (2021).</p>
Structural determinants of ligands recognition by the human mitochondrial basic amino acids transporter SLC25A29. Insights from molecular dynamics simulations of the c-state.
<p>Initial coordinates, molecular dynamics trajectories and representative snapshots resulting from the study "Structural determinants of ligands recognition by the human mitochondrial basic amino acids transporter SLC25A29. Insights from molecular dynamics simulations of the c-state." by Pasquadibisceglie and Polticelli.</p> <p>The MD folders contain the parameter/topology (parm7) and initial coordinates (rst7) for the molecular dynamics simulations. Moreover, a NetCDF trajectory "prod.nc" of the production phase is also included.<br> In detail:<br> - MD0 -> SLC25A29 in absence of ligands;<br> - MD1, MD3, MD4 -> SLC25A29-ARG complex;<br> - MD1-LYS, MD3-LYS, MD4-LYS -> SLC25A29-LYS complex.</p> <p>The folder PDB_figures contains the PDB files used to produce the figures presented in the manuscript.</p>
Spliced isoforms of the cardiac Nav1.5 channel modify channel activation by distinct structural mechanisms: Molecular dynamics coordinate and trajectory files
<p>Molecular dynamics files associated with the publication: Spliced isoforms of the cardiac Nav1.5 channel modify channel activation by distinct structural mechanisms</p>
Molecular Dynamics Simulation on the Effect of Transition Metal Binding to the N-Terminal Fragment of Amyloid-β
<p>Molecular dynamics trajectories in PDB format for 3x Cu-Aβ, 3x Zn-Aβ and 9x Fe-Aβ<strong> </strong>simulations.</p>
Investigation of the behavior of dioxadet molecules in water by molecular dynamics
<p>A set of files for all-atom molecular dynamic simulations of a dioxadet molecule in water for four parametrizations obtained with a number of tools: ATBuilder, Amber tools, and Swiss Parameters.</p>
Supporting data for "Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics"
<p>Supporting data for "<a href="https://www.nature.com/articles/s41467-023-36666-y">Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics</a>" by M. Bocus, R. Goeminne, A. Lamaire, M. Cools-Ceuppens, T. Verstraelen and V. Van Speybroeck, <em>Nature Communications</em>, <strong>2023</strong>, 14, 1008.</p> <p>This dataset contains examples of input files, submission and analysis scripts to train and use a machine learning potential based on the Schnet architecture for the proton hopping reaction in the H-CHA zeolite. The complete DFT training set, obtained by unbiasing the forces printed by CP2K (with PLUMED coupling), is stored as extended xyz files in the folders DFT/A-B/training_data.xyz where A=1-3 and A<B<5. More details on the folder architecture can be found in the README.md file.</p>
Molecular dynamics simulation of the permeation of 5ALA across the lipid bilayers of the stratum corneum
<p>Input and output files for US-REST3 MD simulations of the permeation of 5ALA across a lipid bilayer representative of the lipid bilayers of the stratum corneum. Each folder corresponds to US-REST3 and conventional US calculations performer at different distances between the permeant and the centre of mass of the lipid bilayer.</p>
Molecular dynamics simulation of the permeation of Me-5ALA across the lipid bilayers of the stratum corneum
<p>Input and output files for US-REST3 MD simulations of the permeation of Me-5ALA across a lipid bilayer representative of the lipid bilayers of the stratum corneum. Each folder corresponds to US-REST3 and conventional US calculations performer at different distances between the permeant and the centre of mass of the lipid bilayer.</p>
Molecular dynamics simulations in: High-resolution structures with bound Mn2+ and Cd2+ map the metal import pathway in an Nramp transporter
<p>Transporters of the Nramp (Natural resistance-associated macrophage protein) family import divalent transition metal ions into cells of most organisms. By supporting metal homeostasis, Nramps prevent disorders related to metal insufficiency or overload. Previous studies revealed that Nramps take on a LeuT fold and identified the metal-binding site. We present high- resolution structures of <em>Deinococcus radiodurans</em> Nramp in three stable conformations of the transport cycle revealing that global conformational changes are supported by distinct coordination geometries of its physiological substrate, Mn2+, across conformations and conserved networks of polar residues lining the inner and outer gates. A Cd2+-bound structure highlights differences in coordination geometry for Mn2+ and Cd2+. Measurements of metal binding using isothermal titration calorimetry indicate that the thermodynamic landscape for binding and transporting physiological metals like Mn2+ is different and more robust to perturbation than for transporting the toxic Cd2+ metal.</p>
On equilibrating non-periodic molecular dynamics samples for coupled particle-continuum simulations of amorphous polymers: dataset
<p><strong>Abstract:</strong><br> (from [1])<br> In the context of fracture simulations of polymers, the molecular mechanisms in the vicinity of the<br> crack tip are of particular interest. Nevertheless, to keep the computational cost to a minimum, a<br> coarser resolution must be used in the remaining regions of the numerical sample. For the specific<br> case of amorphous polymers, the Capriccio method bridges the gap between the length and time scales<br> involved at the different levels of resolution by concurrently coupling molecular dynamics (MD) with<br> the finite element method (FEM). Within the scope of the Capriccio approach, the coupling to the<br> molecular MD region introduces non-periodic, so-called stochastic boundary conditions (SBC). In<br> similarity to typical simulations under periodic boundary conditions (PBC), the SBC MD simulations<br> must reach an equilibrium state before mechanical loads are exerted on the coupled systems. In this<br> contribution, we hence extensively study the equilibration properties of non-periodic MD samples<br> using the Capriccio method. We demonstrate that the relaxation behavior of an MD-FE coupled<br> MD domain utilizing non-periodic boundary conditions is rather insensitive to the specific coupling<br> parameters of the method chosen to implement the boundary conditions. The behavior of an exemplary<br> system equilibrated with the parameter set considered as optimal is further studied under uniaxial<br> tension and we observe some peculiarities in view of creep and relaxation phenomena. This raises<br> important questions to be addressed in the further development of the Capriccio method.<br> <br> <strong>Contact:</strong><br> Felix Weber<br> Institute of Applied Mechanics<br> Friedrich-Alexander-Universität Erlangen-Nürnberg<br> Egerlandstr. 5<br> 91058 Erlangen<br> Germany<br> <br> <strong>Context:</strong><br> This dataset contains the results presented in [1] and related data.</p> <p><strong>Content:</strong><br> Throughout this data set, Lammps [2] real units are used. The following folders contain the results obtained under periodic boundary conditions:<br> - biax_PBC: biaxial loading <br> - equil_PBC: equilibration<br> - ut_PBC: uniaxial tension<br> Each simulation directory contains:<br> - input.prm: input parameters of the specific simulation (read by the input file)<br> - job.out: simulation log file<br> - meta.info: meta data of the specific simulation run<br> - Lammps input file (*.in) of the specific simulation<br> - Lammps data file (*.data, molecular style) of the investigated sample<br> - LAMMPS_out: resulting Lammps data and restart (*.rst) files and simulation results (Lammps thermo_out) in <br> tabulated form, an overview of the columns is given in the respective folders</p> <p>The following folders contain the results obtained under stochastic boundary conditions using the Capriccio method [3]:<br> - best: equilibration with the parameter set considered to be most suitable for the MD-FE coupled equilibration<br> - biax: biaxial loading<br> - bridging: equilibration with different adaptivity levels of the bridging domain<br> - descr_obs: equilibration with a Lagrangian frame for the description of the observation region<br> - dpd: equilibration with different thicknesses of the dissipative particle dynamics (DPD) region<br> - friccoeff: equilibration with different friction coefficients applied in the dissipative particle dynamics region<br> - fur: equilibration with different numbers of fur beads <br> - gausspoints: equilibration with different numbers of quadrature points per direction <br> - min: equilibration applying an initial, static energy minimization<br> - nodes: equilibration with a higher number of finite element nodes<br> - shifted: equilibration with particle systems obtained at different positions and points in time within the periodic master system<br> - smdcub: equilibration with different remaining stiffness ratios for the cubic modified weighting factor<br> - smdlin: equilibration with different remaining stiffness ratios for the linear modified weighting factor<br> - timestepsize: equilibration with different molecular dynamics time step sizes<br> - ut: uniaxial tension<br> - ut_friccoeff: uniaxial tension with different friction coefficients applied in the dissipative particle dynamics region<br> - weighting: equilibration with different energy weighting functions<br> - youngsmod: equilibration with different Young's moduli<br> Each simulation directory contains:<br> - input_files: Abaqus [4] input file (*.inp) and Lammps data file (*.data, molecular style) of the investigated sample<br> - MD_data: Results evaluated in the molecular dynamics region. MD_data contains the following subfolders: <br> anchorforces (dumped force components on the anchor points (AP) in kcal/mol, files anchorforce_[load step]_[MD-FE iteration].AF), <br> data (resulting Lammps data files *.[load step].[MD-FE iteration].data), Density (dumped mass density in the observation region in kg/m^3), <br> Energy (dumped total (kinetic + potential), angle, bond, and pair energies in kcal/(mol*Angstrom)), Strain (integral strains in the<br> observation region in x-, y-, and z-direction calculated by means of the Matlab [5] script calc_OBSstrain.m),<br> Stress (stresses in the observation region in MPa), and Temperature (temperature in the observation region in K)<br> - job.out: simulation log file<br> - meta.info: meta data of the specific Lammps simulation<br> Information on the subfolders is given in the respective folders.</p> <p><strong>References:</strong><br> [1] F. Weber, M. Ries, C. Bauer, C. R. Wick, S. Pfaller, "On equilibrating non-periodic molecular dynamics samples for coupled<br> particle-continuum simulations of amorphous polymers", Forces in Mechanics, 2023, 10, 100159.<br> [2] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, <br> S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, S. J. Plimpton, "LAMMPS - a flexible simulation tool <br> for particle-based materials modeling at the atomic, meso, and continuum scales", Computer Physics Communications, 2022, 271, 108171.<br> [3] S. Pfaller, M. Rahimi, G. Possart, P. Steinmann, F. Müller-Plathe, M. C. Böhm, "An Arlequin-based method to couple molecular dynamics <br> and finite element simulations of amorphous polymers and nanocomposites", Computer Methods in Applied Mechanics and Engineering, <br> 2013, 260, 109-129. <br> [4] Dassault Systèmes, "Abaqus documentation", URL: https://abaqus-docs.mit.edu/2017/English/SIMACAEEXCRefMap/simaexc-c-docproc.htm.<br> [5] The MathWorks, Inc, "MATLAB. The Language of Technical Computing", URL: https://de.mathworks.com/help/matlab/.</p> <p><strong>Funding:</strong><br> This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -<br> 377472739/GRK 2423/1-2019. The authors are very grateful for this support. Sebastian Pfaller is furthermore<br> funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 396414850 (Individual<br> Research Grant ’Identifikation von Interphaseneigenschaften in Nanokompositen’).</p>
ConforMine Molecular Dynamics Data: Conformational Variability, Secondary Structure Propensities and Molecular Dynamics Simulations
<pre>This dataset contains all the data used to calculate Conformational Variability (ConVa) and Conformational Propensities as well as to train ConforMine. Each directory one level below this document contains another readme for further explanation on the contained data. The following information can be found in this dataset: </pre> <ul> <li>ConforMine_MD_training_sequences.fasta: FASTA file with the amino acid sequences of all used proteins.</li> <li>simulations (directory): Contains all the raw data derived from the MD simulations.</li> <li>ConforMine_training_MD_dihedrals (directory): Contains .xvg files with the dihedral angles of each amino acid at each step of the MD simulation.</li> <li>ConforMine_training_data_conformational_variability (directory): Contains the Conformational Variability values for all amino acids. Each file contains all ConVa values for a whole protein. The data is provided in .csv and .npy format.</li> <li>ConforMine_training_data_conformational_propensities (directory): Contains the Conformational Propensities values for all amino acids. Each file contains all propensities for a whole protein. The data is provided in .csv and .npy format.</li> </ul>
Supporting data for: Condensed-phase molecular representation to link structure and thermodynamics in molecular dynamics
<p>This repository contains supporting data and code for the paper titled "Condensed-phase molecular representation to link structure and thermodynamics in molecular dynamics" by Bernadette Mohr, Diego van der Mast, and Tristan Bereau.</p>
Input data for Reversible Unwrapping Algorithm for Constant-Pressure Molecular Dynamics Simulations
<p>As described in the main text, here is the input data used for simulation, as well as analysis directories. The archive was generated in my project folder with "tar --exclude=*trr --exclude=pbctools --exclude=qtwrap --exclude=old* --exclude=*npz --exclude=*pdf --exclude=*png --exclude=*ppm --exclude=*dcd* --exclude=*xtc --exclude=*slurm* --exclude=core* --exclude=*sh --exclude=*xvg --exclude=*out --exclude=*git* --exclude=*edr --exclude=*log --dereference -zcvf kulke-$(date +"%F").tar.gz data figures scripts Simulations". Big data and trajectory files were excluded to keep the archive size small. The archive includes all necessary files to reproduce the simulations, analysis and figures for the publication.</p>
Data for manuscript "Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting"
<p>The tar file contains the input files for RADICAL augmented MDFF implementation (R-MDFF) for two protein systems, Adenylate Kinase (ADK) and Carbon Monoxide Dehydrogenase (CODH). These examples demonstrate the implementation of R-MDFF using RADICAL-Cybertools to flexibly fit biomolecules in cryo-EM density maps with on-the-fly decision making.</p> <p>All molecular simulations were performed using CUDA enabled NAMD 2.14 installed on OLCF Summit HPC resource. The CHARMM36 force field parameters were used for the proteins. Synthetic density maps were prepared at 1.8, 3 and 5 Å for ADK and 1.8 and 3 Å for CODH using VMD 1.9.3 software installed on OLCF Summit HPC resource. During the analysis stage, the cross correlation coefficients between density maps and atomic model were computed using VMD 1.9.3 on Summit HPC as part of the R-MDFF workflow.</p> <p>The source code is publicly available on GitHub: <a href="https://github.com/radical-collaboration/MDFF-EnTK">https://github.com/radical-collaboration/MDFF-EnTK </a></p> <p>The preprint of this research is submitted on bioRxiv, doi: <a href="https://doi.org/10.1101/2021.12.07.471672">https://doi.org/10.1101/2021.12.07.471672 </a></p> <p>To obtain maximum compression of the data, the tar command used to generate this tarball was:</p> <pre><code class="language-bash">GZIP=-9 tar --exclude='last.pdb' --exclude='*last_from_prev_iter.pdb' --exclude='*old' --exclude='*log' --exclude='*coor' --exclude='*vel' --exclude='*xsc' --exclude='*dcd' --exclude='lastframepdbs_fix' --exclude='*out' --exclude='*sl' --exclude='*rs' --exclude='*prof' --exclude='*err' --exclude='*dx' --exclude='*grid.pdb' --exclude='*txt' -cvzf rmdffv2.tar.gz rmdff-zenodo/</code></pre> <p> </p>
Effect of Single-Residue Mutations on CTCF Binding to DNA: Insights from Molecular Dynamics Simulations
<p>Supplementary dataset for manuscript "Effect of Single-Residue Mutations on CTCF Binding to DNA: Insights from Molecular Dynamics Simulations". </p>
Movie of the molecular dynamics simulation of a crucial step in the activation of the STING protein
<p>STING (stimulator of interferon genes) is a homodimer protein involved in regulation of the innate immune system and plays a role in antitumor immunity by inducing the production of cytokines. Activation of STING stems from binding of endogenous cyclic dinucleotides (CDNs), which induce a conformational change to initiate signaling. The MP4 movie shows a molecular dynamics simulation of a crucial step of the activation process.</p>
Movie of the molecular dynamics simulation of the opening and closing of the Cullin-RING protein complex
<p>Heterobifunctional degraders, which consist of two separate protein binding moieties (the warhead and the E3-ligand) joined by a linker, are a class of molecules that "induce proximity" between a target protein of interest (POI) and a E3 ubiquitin ligase. This induced proximity can lead to ubiquitination of the POI and its subsequent proteosomal degradation through a complex machinery of proteins. TPD present a novel approach to drug protein targets, since a single degrader molecule can induce catalytic degradation of the POI and potentially offer an avenue to eliminate targets traditionally labeled as undruggable by classical therapeutic strategies. Here we probe the conformational landscape of the full CRL macromolecular assembly and present a MP4 trajectory movie showing the molecular dynamics simulation of the large-scale conformational change during the opening and closing of the Cullin-RING protein complex.</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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.