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393 results for “Molecular dynamics simulations”
Dataset of "Molecular Dynamics Simulations Unveil the Aggregation Patterns and Salting out of Polyarginines at Zwitterionic POPC Bilayers in Solutions of Various Ionic Strengths"
<p>Molecular dynamics simulations are performed for a series of model cell-penetrating peptides (in particular nona-arginines) in aqueous solutions, in contact with model phosphocholine (POPC) membranes in conditions of different ionic strengths. The unusual aggregation properties of peptides at model lipid bilayers are analyzed and different sizes and lifetimes of aggregates are presented.<br>This dataset contains molecular dynamics simulation data with trajectories, input files, and topology files for all studied systems. They contain low peptide concentration in water, low NaCl concentration, high NaCl concentration, low CaCl2 concentration, and high CaCl2 concentration.<br>In addition to low peptide concentration, high peptide concentration in water, low NaCl concentration, high NaCl concentration, low CaCl2 concentration, and high CaCl2 concentration are also studied.</p>
Inactive to active transition of human Thymidine Kinase 1 revealed by Molecular Dynamics simulations
<p>The trajectories and input files for the manuscript <em>Inactive to active transition of human Thymidine</em></p> <p><em>Kinase 1 revealed by Molecular Dynamics simulations</em> (<a href="https://doi.org/10.1021/acs.jcim.1c01157">https://doi.org/10.1021/acs.jcim.1c01157</a>) </p> <p>ABSTRACT</p> <p>Despite its importance for the nucleoside (and nucleoside prodrug) metabolism, the structure<br> of the active conformation of human Thymidine Kinase 1 (hTK1) remains elusive. We perform<br> microsecond molecular dynamics simulations of the inactive enzyme form bound to a<br> bisubstrate inhibitor that was shown experimentally to activate another TK1-like kinase,<br> Thermotoga maritima TK (TmTK). Our results are in excellent agreement with the<br> experimental findings for the TmTK closed-to-open state transition. We show that the inhibitor<br> induces an increase of the enzyme radius of gyration due to the expansion on one of the dimer<br> interfaces; the structural changes observed, including the active site pocket volume increase,<br> decrease in monomer-monomer buried surface area and of the number of hydrogen bonds (as<br> compared to the inactive enzyme control simulation), show that the catalytically competent<br> (open) conformation of hTK1 can be assumed in the presence of an activating ligand.</p>
Atomistic trajectories from ab-initio molecular dynamics simulations of wetted TiO2 nanoparticle
<p>This repository contains atomistic trajectories from ab-initio molecular dynamics simulations of water and TiO2 nanoparticle described in the paper:</p> <p>E. G. Brandt, L. Agosta and A.P.Lyubartsev, " Reactive wetting properties of TiO2 nanoparticles predicted by ab initio molecular dynamics simulations", Nanoscale, 8, 13385-13398 (2016) DOI: 10.1039/c6nr02791a</p> <p>The trajectories are saved in the .xtc format, and initial structures with specification of atom types are given in the .pdb format.</p> <p>The name of each file contains brief information about the simulated system:</p> <p>TiO2 : composition of the nanoparticle<br> n24 : number of TiO2 units in the nanoparticle<br> anatase/brookite/rutile : type of crystall structure<br> - a number 0 - 30 : number of water molecules in the simulation<br> 2fs - the time step</p> <p>For more details, see the referred paper</p>
Dataset For Molecular Dynamics Simulations of Thin Film Rupture
<p>Data files for production runs for the key results reported in "Life and Death of a Thin Liquid Film", (2024) by Muhammad Rizwanur Rahman, Li Shen, James P. Ewen, D. M. Heyes, Daniele Dini, and E. R. Smith. The directory named "spontaneous-rupture-equilibrated-state-for-production-runs" contains data files of different initial film thicknesses, and the directory named "synthetic-rupture-equilibrated-state-for-production-runs" contains data files for films with similar initial thickness, but with different patterns of synthetic damages caused to the film. These files should be used as the restart file for production phase under NVE ensemble. </p> <p>Codes to run these files, and process the data are described in github: https://github.com/MuhammadRRahman/Thin-Film-Rupture-NEMD.git.</p>
All-atom 500-nano seconds 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 500 nano-seconds (ns) production run was performed for the simulation.</p>
Representative Structures from Molecular Dynamics Simulations of the Inward Facing and Outward Facing States of LaINDY
<p>This upload is a supplementary data set for the following publication: <a href="https://doi.org/10.7554/eLife.61350">D. B. Sauer, N. Trebesch, J. J. Marden, N. Cocco, J. Song, A. Koide, S. Koide, E. Tajkhorshid, and D.-N. Wang. "Structural basis for the reaction cycle of DASS dicarboxylate transporters." <em>eLife</em>. <strong>9</strong>, e61350. DOI: 10.7554/eLife.61350</a>. Please see the main publication for the methods, analysis, and discussion associated with this data set.</p>
Two 100 ns NVT molecular dynamics simulations of dsDNA and dsRNA "GGGG" 18-mers (GCGGGGGGGGGGGGGGGC)
<p>Supporting information for "Molecular origin of distinct hydration dynamics in double helical DNA and RNA sequences" by E. Frezza, D. Laage and E. Duboué-Dijon, <span><em>J. Phys. Chem. Lett.</em></span> <span>2024</span><span>, 15</span><span>, </span><span>4351–4358</span><br>Two 100 ns-long NVT molecular dynamics simulation: one of dsDNA "GGGG" 18-mer (GCGGGGGGGGGGGGGGGC) and one of the analogous dsRNA. The nucleic acid is explicitly solvated in water and neutralized with 0.15M KCl. Simulations were performed using the Gromacs 5 software. DNA is described with the Amber 99SB-ILDN force field with the BSC0 modifications, RNA is described with the Amber 99SB-ILDN force field with the BSC0 and χOL3 modifications, the SPC/E force field is used for water, and the Joung Cheatham paraeters for ions. The shared coordinates are saved every 500fs, twice less frequently than the original trajectories used for the publication, to reduce the size of the shared dataset below the allowed size limit.</p>
Data related to the article "Impedance of nanocapacitors from molecular simulations to understand the dynamics of confined electrolytes"
<p>Contains input files and data used to generate the figures of the article:</p> <p>Impedance of nanocapacitors from molecular simulations to understand the dynamics of confined electrolytes<br>(Giovanni Pireddu, Connie J. Fairchild, Samuel P. Niblett, Stephen J. Cox and Benjamin Rotenberg)</p> <p>ChemRxiv: https://doi.org/10.26434/chemrxiv-2023-2ccrw</p> <p>Published version: to be inserted upon publication</p> <p>The folder EXAMPLE_INPUT_FILES contains typical [MetalWalls](https://doi.org/10.21105/joss.02373) ([repository](https://gitlab.com/ampere2/metalwalls)) and [LAMMPS]([repository](https://github.com/lammps/lammps)) input files used to perform the molecular simulations.</p> <p>The folder DATA_FIGURES contains the processed data used to plot all the figures of the paper (see below).</p> <p><br>Notes: <br>1) In the file names, the notation 'M01', 'M05', 'M10' and 'M15' refers to the salt concentration in each system (0.1, 0.5, 1.0 and 1.5, respectively). 'W' refers to pure water (0 M) systems.<br>2) In the file names, the notation 'd1', 'd2', 'd3', 'd4', refers to different interelectrode distances (d1= 2.56 nm; d2= 5.07 nm; d3= 9.80 nm; d4= 19.84 nm) <br>3) The files containing the polarization cross-correlation are marked with 'AxB' indicating the cross-correlation between the contributions A and B. Specifically A and B can be: <br> - T = total<br> - I = ion<br> - W = water</p> <p><br>Figure 1:<br>- Panel B<br> - 'Fig1_CapConcentration': Differential capacitance scaled by electrode area as a function of NaCl concentration<br>- Panel C<br> - 'Fig1_QACF_*': Electrode charge autocorrelation function<br>- Panel D<br> - 'Fig1_Norm_QACF_*': Normalized electrode charge autocorrelation function<br> - 'Fig1_NormChar_*': Normalized non-equilibrium charge response</p> <p>Figure 2:<br>- Panel A: <br> - 'Fig2_ReZ_*': Real part of impedance<br>- Panel B:<br> - 'Fig2_nImZ_*': Negative imaginary part of impedance<br>- Panel C:<br> - 'Fig2_ReZint_*': Real part of interfacial impedance<br> - 'Fig2_Resistivities.dat': Resistivity as a function of NaCl concentration (bulk, confined, Nernst-Einstein)<br>- Panel D:<br> - 'Fig2_nImZint_*': Negative imaginary part of interfacial impedance<br> - 'Fig2_ECM*': Capacitor contributions to the imaginary part of interfacial impedance (finite concentrations)<br> - 'Fig2_ECW1.dat': Capacitor contributions to the imaginary part of interfacial impedance (pure water). Full cell capacitance taken into account<br> - 'Fig2_ECW2.dat': Capacitor contributions to the imaginary part of interfacial impedance (pure water). Interfacial capacitance taken into account </p> <p>Figure 3:<br>- Panel A:<br> - 'Fig3_ReCond_Peyman_M10.dat': Real part of conductivity (data from: A Peyman, C Gabriel, E Grant, Complex permittivity of sodium chloride solutions at microwave frequencies. Bioelectromagnetics 28, 264–274 (2007))<br> - 'Fig3_ReCond_Querry_M10.dat': Real part of conductivity (data from: MR Querry, RC Waring, WE Holland, GM Hale, W Nijm, Optical Constants in the Infrared for Aqueous Solutions of NaClt. J. Opt. Soc. Am. 62 (1972)) <br> - 'Fig3_ReCond_Vinh_M10.dat': Real part of conductivity (data from: NQ Vinh, et al., High-precision gigahertz-to-terahertz spectroscopy of aqueous salt solutions as a probe of the femtosecond-to-picosecond dynamics of liquid water. The J.<br>Chem. Phys. 142, 164502 (2015).)<br> - 'Fig3_ReCond_M10.dat': Real part of conductivity from MD simulations<br>- Panel B:<br> - 'Fig3_ReCond_M*/W.dat': Real part of conductivity from MD simulations<br> - 'Fig3_ReCond_Peyman_M*': Real part of conductivity (data from: A Peyman, C Gabriel, E Grant, Complex permittivity of sodium chloride solutions at microwave frequencies. Bioelectromagnetics 28, 264–274 (2007))<br>- Panel C:<br> - 'Fig3_Cond0.dat': Static conductivity as a function of concentration (MD data)<br> - 'Fig3_Cond0_Buchner.dat': Static conductivity as a function of concentration (data from: R Buchner, GT Hefter, PM May, Dielectric relaxation of aqueous nacl solutions. The J. Phys. Chem. A 103, 1–9 (1999))<br> - 'Fig3_Cond0_Peyman.dat': Static conductivity as a function of concentration (data from: A Peyman, C Gabriel, E Grant, Complex permittivity of sodium chloride solutions at microwave frequencies. Bioelectromagnetics 28, 264–274 (2007))</p> <p>Figure 4:<br>- Panel A: <br> - 'Fig4_ReZ_d*': Real part of impedance (MD simulations)<br> - 'Fig4_ReZEC_d*': Real part of impedance (equivalent circuit model)<br>- Panel B:<br> - 'Fig4_nImZ_d*': Negative imaginary part of impedance (MD simulations)<br> - 'Fig4_nImZEC_d*': Negative imaginary part of impedance (equivalent circuit model)</p> <p>Figure 5:<br>- 'Fig5_TauQ.dat': timescales from the total charge autocorrelation functions<br>- 'Fig5_iontot.dat': timescales from the TxI autocorrelation function<br>- 'Fig5_RC.dat': timescales from the RC estimates<br>- 'Fig5_RbulkC.dat': timescales from the RbulkC estimates<br>- 'Fig5_Taudiff.dat': timescales from the difference between electrolyte and pure water QACFs<br>- 'Fig5_taud.dat': tau_d analytical timescales<br>- 'Fig5_tauDebye.dat': tau_Debye analytical timescales<br>- 'Fig5_taumix.dat': tau_mix analytical timescales</p> <p>Figure 6:<br>- Panel A:<br> - 'Fig6_Static_*: Static correlation between polarization contributions as a function of salt concentration<br>- Panel B:<br> - 'Fig6_Dynamic_EQ_*_M01' Dynamical correlations between polarization contributions (equilibrium MD results)<br> - 'Fig6_Dynamic_NEQ_*_M01' Dynamical correlations between polarization contributions (non-equilibrium MD results)<br>- Panel C:<br> - 'Fig6_Dynamic_EQ_*_M10' Dynamical correlations between polarization contributions (equilibrium MD results)<br> - 'Fig6_Dynamic_NEQ_*_M10' Dynamical correlations between polarization contributions (non-equilibrium MD results)</p> <p> </p> <p> </p>
Molecular Dynamic Simulation on the Role of CL5D in Accelerate the Product Dissociation of SIRT6
<p>The source data used to generate figures in the main text is stored in the ‘Source Data.xlsx’ file, and 'Source Data Description.docx' is a brief description of the source data table.<br>'SIRT6.prmtop' and 'SIRT6.inpcrd' are initial structure of SIRT6 system,'SIRT6-CL5D.prmtop' and 'SIRT6-CL5D.inpcrd' are initial structure of SIRT6-CL5D system.<br>'SIRT6_equ.pdb', 'SIRT6-CL5D'_equ.pdb are snapshots of the equilibrium structure of the SIRT6 system and the SIRT6-CL5D system, respectively.<br>'ramd.conf' is an example configuration file that uses RAMD simulations to obtain the AR6 dissociation path in the SIRT6 system, with the acceleration of 0.0625 kcal/Å/g and a cutoff distance of 0.005 Å.<br>'win1.conf' and 'win1.in' are example configuration files for the first window of the umbrella sampling, which calculates the dissociation energy barrier of AR6 in the SIRT6 system,'win1.in' is the parameter file for umbrella sampling, with A 2.5 kcal/mol/Ų spring constant, and window center is 9 Å.</p> <p> </p>
Dry trajectories of SARS-CoV-2 RBD from accelerated molecular dynamics simulation
<p>These are supplementary files to the preprint/paper "SARS-CoV-2 spike protein unlikely to bind to integrins via the Arg-Gly-Asp (RGD) motif of the Receptor Binding Domain: evidence from structural analysis and microscale accelerated molecular dynamics" (http://dx.doi.org/10.1101/2021.05.24.445335).</p> <p>The attached code in Jupyter notebook can be run after installing the virtual environment using the `environment.yml `</p> <p>The file `data.zip` needs to be extracted to the same path where the notebook is run from</p>
Molecular Dynamics simulations suggest possible activation and deactivation pathways in hERG channel
<ol> <li>equil_gating_4_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 4 equilibration trajectory</li> <li>equil_gating_6_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 6 equilibration trajectory</li> <li>equil_gating_8_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 8 equilibration trajectory</li> <li>equil_gating_4.dcd: 100 ns NPT trajectory of the hERG closed state with gating charge 4</li> <li>equil_gating_6.dcd: 100 ns NPT trajectory of the hERG closed state with gating charge 6</li> <li>equil_gating_8.dcd: 100 ns NPT trajectory of the hERG closed state with gating charge 8</li> <li>equil_open_assembly_xleap.prmtop: file topology of the hERG open state equilibration trajectory</li> <li>equil_open.dcd: 100 ns NPT trajectory of the hERG open state</li> <li>herg_closed_gating_4.pdb: PDB file of hERG closed state with gating charge 4 after Steered MD simulations</li> <li>herg_closed_gating_6.pdb: PDB file of hERG closed state with gating charge 6 after Steered MD simulations</li> <li>herg_closed_gating_8.pdb: PDB file of hERG closed state with gating charge 8 after Steered MD simulations</li> <li>TMD_O-C_closed_gating_8_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 8 TMD trajectory</li> <li>TMD_O-C_closed_gating_6_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 6 TMD trajectory</li> <li>TMD_O-C_closed_gating_4_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 4 TMD trajectory</li> <li>TMD_O-C_closed_gating_8.dcd: TMD trajectory of the hERG closed state with gating charge 8</li> <li>TMD_O-C_closed_gating_6.dcd: TMD trajectory of the hERG closed state with gating charge 6</li> <li>TMD_O-C_closed_gating_4.dcd: TMD trajectory of the hERG closed state with gating charge 4</li> </ol> <p>MD trajectories (equilibration and Targeted MD trajectories) in dcd format can be visualized using visualization tools such as VMD or PyMol after uploading the topology file.</p> <p>The directory data_supplementary-note-4.tar.bz2 contains the files related to the Supplementary Notes 4: "A practical example of pathway calculation".</p>
A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories
<p>Containes input data for MD simulations of 3 HSP90- small compound complexes from the paper</p> <p>A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories" from Daria B. Kokh, Bernd Doser , Stefan Richter , Fabian Ormersbach , Xingyi Cheng, Rebecca C. Wade, publishe in J. Chem. Phys. <strong>153</strong>, 125102 (2020); <a href="https://doi.org/10.1063/5.0019088">https://doi.org/10.1063/5.0019088</a></p> <ul> <li>ref.pdb - structure of the complex in PDB format</li> <li>ref.prmtop - topology file in AMBER</li> <li>ref-equal-NTP.pdb - structure after NTP equilibration </li> <li>ref-equal-NTP.rst7 - coordinates after NTP equilibration</li> <li>ref-equal-NTP.crd - coordinates after NTP equilibration </li> <li>gromacs.gro - coordinates in Gromacs format (after NTP equalibration)</li> <li>gromacs.top - Gromacs topology </li> </ul> <p> </p>
Molecular Dynamics simulations of spreading droplets
<p>This dataset contains the results of non-equilibrium Molecular Dynamic simulations of 2-dimensional SPC/E water nanodroplets spontaneously spreading over silica-like walls, performed using Gromacs. The main purpose of these simulations is to study the motion of three-phases contact lines over high-friction surfaces and to test contact line friction models.</p> <p>Further details can be found in 'documentation.pdf'.</p>
data set to bioRxiv preprint 'Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation
<p>This is supporting data and software code for the following preprint in bioRxiv</p> <p><strong>Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation</strong></p> <p>https://www.biorxiv.org/content/10.1101/2022.04.18.488629v1</p>
Molecular Dynamics simulations of shear droplets
<p>This dataset contains the results of non-equilibrium Molecular Dynamic simulations of 2-dimensional SPC/E water nanodroplets confined between silica-like walls and under shear flow conditions, performed using Gromacs. The main purposes of these simulations are: a) to study the motion of three-phases contact lines over high-friction surfaces, b) to study the critical transition leading to droplet breakage and c) to test the modelling and prediction capabilities of continuous fluid dynamics simulation methods. The investigation of the points above is illustrated in an article, which has been digitally published on the Journal of Fluid Mechanics (doi:10.1017/jfm.2022.219, see references); please refer to the paper for a detailed description of the molecular simulations and of the tested CFD methods. The publication of this dataset not only grants the reproducibility of the results discussed in the article, but also serves as collection of benchmarks for the fellow researchers willing to test improved and/or alternative models to describe the motion of contact lines.</p>
All-atom molecular dynamics simulations of Synechocystis halorhodopsin (SyHR)
<p>The trajectories of all-atom MD simulations of:<br> 1) Cl<sup>-</sup>-bound SyHR in the ground (GR) state (SyHR_monomer_GR_POPC_CHARMM36_200ns)<br> 2) Cl<sup>-</sup>-bound SyHR in the K state (SyHR_monomer_K_POPC_CHARMM36_200ns)<br> in the monomeric form in a POPC bilayer.<br> 3) SO<sub>4</sub><sup>2-</sup>-bound SyHR in the GR state (SyHR_trimer_GR_POPC_CHARMM36_500ns)<br> in the trimeric form in a POPC bilayer.</p> <p>Simulations have been performed using the CHARMM36 force field, running with the GROMACS 2022 package.</p>
Intermolecular interactions in G protein-coupled receptor allosteric sites at the membrane interface from molecular dynamics simulations and quantum chemical calculations
<p>Allosteric modulators are called to be promising candidates in G protein-coupled receptor (GPCR) drug development by displaying target selectivity and fewer side effects. Among the allosteric sites known to date, extrahelical cavities represent an uncharacteristic binding location that raises many questions about the ligand interactions and stability; the binding site structure, and how all of these are affected by lipid molecules. In this work, we analyze the dynamics and interactions in the PAR2, C5aR1, and GCGR receptors unbound and bound to allosteric modulators at the receptor-lipid interface using molecular dynamics simulations in three lipid compositions. In addition, we performed quantum chemical calculations to further explore electrostatic interactions and the strength of atom pairwise contacts in the stabilization of the ligand-receptor complexes. We show that besides classical hydrogen bonds weak polar interactions such as O-HC, O-Br, and S-HC contacts and aromatic interactions contribute to the binding of allosteric modulators at the extrahelical sites in the middle of the membrane. The allosteric cavities are open and detectable in various membrane compositions but not always predicted as druggable. The availability of polar atoms for interactions in such cavities can be assessed by water molecules from the simulations. Although ligand-lipid interactions are weak, the lipid tails play a role in sizing and shaping the large part of the allosteric cavity. </p> <p>You will find the following files:</p> <ul> <li>Input files of the equilibration and production protocols of MD simulations (MD_simulations_inputs.zip)</li> <li>Input files and coordinate files of F-SAPT and NCIPLOT calculations (quantum_chemical_coordiates_inputs.zip)</li> </ul>
Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% DOPS with Na+ counterions using ff99 Ions
<p><strong>System: </strong>Symmetric bilayer of anionic DOPS (1,2-Dioleoyl-<em>sn</em>-glycero-3-phosphoserine 100 mol-%) lipids with sodium (Na<sup>+</sup>) counter ions.</p> <p><strong>Number of DOPS:</strong> 128.<br> <strong>Number of Na<sup>+</sup>-ions:</strong> 128.<br> <strong>Number of waters:</strong> 4480.</p> <p><strong>Lipid model:</strong> Amber Lipid 17 [IR Gould, AA Skjevik, CJ Dickson, BD Madej, RC Walker: "Lipid17: A Comprehensive AMBER Force Field for the Simulation of Zwitterionic and Anionic Lipids" in prep. (2018)].</p> <p><strong>Ion models: </strong> Amber ff99 [J Åqvist <em>J. Phys. Chem.</em> <strong>94</strong> 8021 (1990)].</p> <p><strong>Water model:</strong> TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein <em>J. Chem. Phys.</em> <strong>79</strong> 926 (1983)].</p> <p><strong>Simulation engine:</strong> Amber16 [DA Case et al. <em>AMBER 2017</em> UCSF (2017)].</p> <p><strong>Number of independent repeats per setup: </strong>2.<br> <strong>Trajectory lengths per repeat:</strong> 400 ns + 100 ns.<br> <strong>Previously equilibrated for:</strong> 100 ns.<br> <strong>Sampling rate:</strong> every 10 ps.</p> <p><strong>Time integration step:</strong> 2 fs.</p> <p><strong>Thermodynamic ensemble:</strong> NpT. <br> <strong>Temperature coupling:</strong> 'Langevin' at T = 303 K.<br> <strong>Pressure coupling: '</strong>Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984); <em>J. Chem. Phys.</em> <strong>103</strong> 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension.</p> <p><strong>Electrostatics: </strong>PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993);<em> J. Chem. Theory Comput.</em> <strong>9</strong> 3878 (2013)].<br> <strong>Van der Waals:</strong> Turned off between 1.0 nm and 1.5 nm.</p> <p><strong>Constraints: </strong>Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [<em>J. Comput. Phys.</em> <strong>23</strong> 327 (1977)], in water using SETTLE [<em>J. Comput. Chem. </em><strong>13</strong> 952 (1992)].</p> <p><strong>Used in publications: </strong>OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).</p>
Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% POPS with Na+ counterions using Joung-Cheatham Ions
<p><strong>System:</strong> Symmetric bilayer of anionic POPS (palmitoyl-oleoyl-phosphatidylserine 100 mol-%) lipids with sodium (Na<sup>+</sup>) counter ions.</p> <p><strong>Number of POPS:</strong> 128.<br> <strong>Number of Na<sup>+</sup>-ions:</strong> 128.<br> <strong>Number of waters:</strong> 4480.</p> <p><strong>Lipid model:</strong> Amber Lipid 17 [IR Gould, AA Skjevik, CJ Dickson, BD Madej, RC Walker: "Lipid17: A Comprehensive AMBER Force Field for the Simulation of Zwitterionic and Anionic Lipids" in prep. (2018)].</p> <p><strong>Ion model:</strong> Joung–Cheatham [IS Joung, TE Cheatham III <em>J. Phys. Chem. B</em> <strong>112</strong> 9020 (2008)].</p> <p><strong>Water model:</strong> TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein <em>J. Chem. Phys.</em> <strong>79</strong> 926 (1983)].</p> <p><strong>Simulation engine:</strong> Amber16 [DA Case et al. <em>AMBER 2017</em> UCSF (2017)].</p> <p><strong>Number of independent repeats per setup:</strong> 2.<br> <strong>Trajectory lengths per repeat:</strong> 400 ns + 100 ns.<br> <strong>Previously equilibrated for:</strong> 100 ns.<br> <strong>Sampling rate:</strong> every 10 ps.</p> <p><strong>Time integration step:</strong> 2 fs.</p> <p><strong>Thermodynamic ensemble:</strong> NpT. <br> <strong>Temperature coupling:</strong> 'Langevin' at T = 298 K.<br> <strong>Pressure coupling:</strong> 'Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984); <em>J. Chem. Phys</em>. <strong>103</strong> 10252 (1995)] with <em>xy</em> and <em>z</em> coupled separately at p = 1.0 bar with no surface tension.</p> <p><strong>Electrostatics:</strong> PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993); <em>J. Chem. Theory Comput. </em><strong>9</strong> 3878 (2013)].<br> <strong>Van der Waals:</strong> Turned off between 1.0 nm and 1.5 nm.</p> <p><strong>Constraints:</strong> Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [<em>J. Comput. Phys.</em> <strong>23</strong> 327 (1977)], in water using SETTLE [<em>J. Comput. Chem.</em> <strong>13</strong> 952 (1992)].</p> <p><strong>Used in publications:</strong> OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).</p>
Molecular dynamics simulation of SpoIVFB:Pro-SigmaK complex (replicate 1)
<p>Replicate simulation 1/4</p> <p>Found here are all files needed to reproduce or visualize the results of molecular dynamics simulation of the SpoIVFB intramembrane protease bound to the transcription factor Pro-sigmaK. The protein complex was embedded in a POPE_POPG_DAG_CL bilayer using CHARMM-GUI and simulated using OpenMM. The README file is a C-shell script that will run equilibration and 250ns of unrestrained simulation. </p> <p>Individual output (.out) and trajectory (.dcd) files are provided for each checkpoint of the simulation. A combined trajectory containing 250 ns of unrestrained simulation is also provided (combined_250ns_traj.dcd). Together with the step5_input.psf file, this combined dcd file can be used with common software such as VMD to visualize the molecular dynamics trajectory.</p>
ScienceDex guides
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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.