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99 results for “lipid membrane”
Simulation files for POPC lipid membrane with Slipids-VIS force field for Gromacs MD simulation engine
<p>The tar.gz archive contains simulation input files that were used in the publication Transmembrane potential modeling: Comparison between methods of constant electric field and ion imbalance.</p> <p>http://pubs.acs.org/doi/abs/10.1021/acs.jctc.5b01202</p> <p>The files are meant to be used with <strong>Gromacs</strong> simulation package (gromacs.org).</p> <p>A modified Slipids force field, <strong>Slipids-VIS</strong>, is introduced. It uses Virtual Interaction sites in order to speed up simulation. The technique is described in the aforementioned work. The archive contains working topology for <strong>POPC</strong> lipid molecules and 6fs timestep without any significant loss of accuracy.</p>
Can calmodulin bind to lipids of the cytosolic leaflet of plasma membranes?
<p>Can calmodulin bind to lipids of the cytosolic leaflet of plasma membranes?:</p> <p><br>This data set contains all the experimental raw data, analysis and source files for the final figures reported in the manuscript: "Can calmodulin bind to lipids of the cytosolic leaflet of plasma membranes?". It is divided into five (1-5) zipped folders, named as the technique used to obtain the data. Each of them, where applicable, consists of three different subfolders (raw data, analysed data, final graph). Read below for more details. </p> <p>1) ConfocalMicroscopy</p> <p> 1a) Raw_Data: the raw images are reported as .dat and .tif formats, divided into folders (according to date first yymmdd, and within the same day according to composition). Each folder contains a .txt file reporting the experimental details </p> <p> 1b) GUVs_Statistics<br> - GUVs_Statistics.txt explains how we generated the bar plot shown in Fig. 1E</p> <p> 1c) Final_Graph<br> - Figure_1B_1D.png is the figure representing figure 1B and 1D<br> - Figure1E_%ofGUVswithCaMAdsorbptions.csv is the source file x-y of the bar plot shown in figure 1E (% of GUVs which showed adsorption of CaM over the total amount of measured GUVs) <br> - Where_To_Find_Representative_Images.txt states the folders where the raw images chosen for figure 1 can be found </p> <p>2) FCS<br> <br> 2a) Raw_Data: <br> - 1_points: .ptu files <br> - 2_points: .ht3 files <br> - Raw_Data_Description.docx which compositions and conditions correspond to which point in the two data sets<br> <br> 2b) Final_Graphs:<br> - Figure_2A.xlsx contains the x-y source file for figure 2A</p> <p> 2c) Analysis: <br> - FCS_Fits.xlsx outcome of the global fitting procedure described in the .docx below (each group of points represents a certain composition and calcium concentration, read the Raw_Data_Description.docx in the FCS > Raw_Data)<br> - Notes_for_FCS_Analysis.docx contains a brief description of the analysis of the autocorrelation curves</p> <p>3) GPLaurdan<br> <br> 3a) Raw Data: all the spectra are stored in folders named by date (yymmdd_lipidcomposition_Laurdan) and are in both .FS and .txt formats </p> <p> 3b) GP calculations: contains all the .xlsx files calculating the GP values from the raw emission and excitation spectra</p> <p> 3c) Final_Graphs<br> - Data_Processing_For_Fig_2D.csv contains the data processing from the GP values calculated from the spectra to the DeltaGP (GP with- GP without CaM) reported in fig. 2D<br> - Figure_2C_2D.xlsx contains the x-y source file for the figure 2C and 2D</p> <p>4) LiveCellsImaging </p> <p> 3a) Intensity_Protrusions_vs_Cell_Body: <br> - contains all the .xlsx files calculating the intensity of the various images. File renamed by date (yymmdd) <br> - All data in all excel sheets gathered in another Excel file to create a final graph </p> <p> 3b) Final_Graphs<br> - Figure_S2B.xlsx contains the x-y source file for the figure S2B</p> <p>5) LiveCellImaging_Raw_Data: it contains some of the images, which are given in .tif. They are divided by date (yymmdd) and each contains subfolders renamed by sample name, concentration of ionomycin. Within the subfolders, the images are divided into folders distinguishing the data acquired before and after the ionomycin treatment and the incubation time.</p> <p> </p> <p>6) 211124_BioCev_Imaging_1 folder has the .jpg files of the time laps, these are shown in fig 1A and S2.</p> <p>7) 211124_BioCev_Imaging_2 and 8) 211124_BioCev_Imaging_3 contain the images of HeLa cells expressing EGFP-CaM after treatment with ionomycin 200 nM (A1) and 1 uM (A2), respectively. </p> <p><br>9) SPR</p> <p> 9a) Raw Data: <br> - SPR_Raw_Data.xlsx x/y exported sensorgrams <br> - the .jpg files of the software are also reported and named by lipid composition</p> <p> 9b) Final_Graph: <br> - Fig.2B.xlsx contains the x-y source file for the figure 2B</p> <p> 9c) Analysis<br> - SPR_Analysis.xlsx: excel file containing step-by-step (sheet by sheet) how we processed the raw data to obtain the final figure (details explained in the .docx below)<br> - Analysis of SPR data_notes.docx: read me for detailed explanation</p>
A partnership between the lipid scramblase XK and the lipid transfer protein VPS13A at the plasma membrane
<p>This upload contains files documented in a preprint and a publication.</p> <p>Preprint: https://doi.org/10.1101/2022.03.30.486314</p> <p>Publication: <a href="https://doi.org/10.1073/pnas.2205425119">https://doi.org/10.1073/pnas.2205425119</a></p> <p>The files uploaded here are:</p> <p>- Alphafold predictions for VPS13A N-term (a.a. 1-2100) and C-term (a.a. 1021-3174). The .pse file is the pymol structure alignment of the two predicted VPS13A portions, join at aminoacid position D14 with the different representations presented throughout the paper stored as pymol "scenes". </p> <p>- AlphaFold-Multimer prediction for the interaction between XK and the C-term region of VPS13A is also included.</p> <p>- An excel file containing the tabular data for the graphs in Figures 1G, S2E and 4D.</p>
dataset for paper "Activation energy for pore opening in lipid membranes under an electric field"
<p>Dataset for the paper "Electropermeabilization of hydroperoxidized lipid membranes".</p> <p>Data was generated from Orbit Mini miniaturized bilayer workstation (Nanion Technologies, Munich, Germany), with an inserted microelectrode cavity array (MECA 4) recording chip (Ionera Technologies, Freiburg, Germany).</p> <p>The data files have format .abf, a standard format for electrophysiological data. <br> It can be read by applications such as for instance</p> <p>- Clampex and ClampFit, from the patch-clamp software suite pCLAMP, <br> - Elements Data Analyzer, associated with the elements data reader software from Elements-IC, </p> <p><br> or imported into Python through the package pyABF 2.3.5.</p> <p>import pyabf // abf=pyabf.ABF(path+"/"+f+"/"+abffile) // data = np.vstack((abf.sweepX, abf.data)) </p> <p>Data is organized in five folders named according to target hydroperoxidation degrees:<br> POPC<br> POPC-OOH 25%<br> POPC-OOH 50%<br> POPC-OOH 75%<br> POPC-OOH 100%</p> <p>Inside each of the five above files data is organized by date, and informed with the actual measured hydroperoxidation degree for a given sample. </p>
Data for publication "Lipid oxidation controls peptide self-assembly near membranes through a surface attraction mechanism"
<p>The data provided refer to our published article:</p> <p>T. John,* S. Piantavigna, T. J. A. Dealey, B. Abel, H. J. Risselada, L. L. Martin*, Lipid oxidation controls peptide self-assembly near<br>membranes through a surface attraction mechanism, Chem. Sci. 14 (2023), 3730-3741. <a href="https://doi.org/10.1039/d3sc00159h">https://doi.org/10.1039/d3sc00159h</a>.</p>
Simulation data and code used for the publication in Magn. Reson. "Time-domain proton-detected local-field NMR for molecular structure determination in complex lipid membranes"
<p>Simulation data used in the publication Magn. Reson. "Time-domain proton-detected local-field NMR for molecular structure determination in complex lipid membranes". The simulation data set, and the code developed to generate such data, are included. Details in the published paper </p>
Lipid membrane simulations with flat-bottom and double-bilayer setups, part 2/2
<p>To cite: Biriukov, D. and Javanainen, M. Efficient Simulations of Solvent Asymmetry Across Lipid Membranes Using Flat-Bottom Restraints. J. Chem. Theory Comput. 2023, 19 (18), 6332–6341. DOI: <a href="https://doi.org/10.1021/acs.jctc.3c00614">10.1021/acs.jctc.3c00614</a></p> <p>Gromacs molecular dynamics simulations to compare membrane and solvent properties from lipid membrane simulations with flat-bottom and double-bilayer setups. CHARMM36 force field was used except for simulations with peptides, where a prosECCo model was used [Nencini et al., Biophys. J. 121, 157a (2022)]</p> <p>This dataset contains only double-bilayer simulations. The flat-bottom simulations together with all topologies and mdp files can be found in part 1 : DOI: <a href="https://zenodo.org/record/7973838">10.5281/zenodo.7973838</a></p> <p>Abbreviations in the names of simulation files:</p> <ul> <li>"fb" - simulations with a flat-bottom setup</li> <li>"2m" - simulations with two lipid membranes, i.e., a double-bilayer setup</li> <li>"popc" - membrane is modeled as a POPC lipid bilayer</li> <li>"mix" - a realistic membrane with various lipids is modeled, resembling the composition from [Lorent et al., Nat. Methods 16, 644–652 (2020)]</li> <li>"nak" - only sodium and potassium cations, together with chloride anions, are present in the system</li> <li>"ext" - as "nak", but also calcium and magnesium cations are added</li> <li>"r9" - as "nak" but also R9 (nona-arginine) peptides are added on both sides of the membrane</li> <li>"r9k" - as "nak" but also R9 (nona-arginine) peptides are added on the extracellular side of the membrane</li> <li>"one" - ions are present only on one side of a lipid membrane</li> <li>"freecl" - flat-bottom simulations but without restraints on chloride anions</li> <li>"s" - simulations were performed using the scaled-charge prosECCo75 force field based on CHARMM [Nencini et al., Biophys. J. 121, 157a (2022)]</li> <li>"restr" - restraint .gro file with ionic/peptide <em>z</em> coordinates set to zero</li> </ul>
Lipid membrane simulations with flat-bottom and double-bilayer setups, part 1/2
<p>To cite: Biriukov, D. and Javanainen, M. Efficient Simulations of Solvent Asymmetry Across Lipid Membranes Using Flat-Bottom Restraints. J. Chem. Theory Comput. 2023, 19 (18), 6332–6341. DOI: <a href="https://doi.org/10.1021/acs.jctc.3c00614">10.1021/acs.jctc.3c00614</a></p> <p>Gromacs molecular dynamics simulations to compare membrane and solvent properties from lipid membrane simulations with flat-bottom and double-bilayer setups. CHARMM36 force field was used except for simulations with peptides, where a prosECCo model was used [Nencini et al., Biophys. J. 121, 157a (2022)]</p> <p>This dataset contains all the topologies and flat-bottom simulation files. The double-bilayer simulation files can be found in part 2: DOI: <a href="https://zenodo.org/record/7974633">10.5281/zenodo.7974633</a></p> <p>Abbreviations in the names of simulation files:</p> <ul> <li>"fb" - simulations with a flat-bottom setup</li> <li>"2m" - simulations with two lipid membranes, i.e., a double-bilayer setup</li> <li>"popc" - membrane is modeled as a POPC lipid bilayer</li> <li>"mix" - a realistic membrane with various lipids is modeled, resembling the composition from [Lorent et al., Nat. Methods 16, 644–652 (2020)]</li> <li>"nak" - only sodium and potassium cations, together with chloride anions, are present in the system</li> <li>"ext" - as "nak", but also calcium and magnesium cations are added</li> <li>"r9" - as "nak" but also R9 (nona-arginine) peptides are added on both sides of the membrane</li> <li>"r9k" - as "nak" but also R9 (nona-arginine) peptides are added on the extracellular side of the membrane</li> <li>"one" - ions are present only on one side of a lipid membrane</li> <li>"freecl" - flat-bottom simulations but without restraints on chloride anions</li> <li>"s" - simulations were performed using the scaled-charge prosECCo75 force field based on CHARMM [Nencini et al., Biophys. J. 121, 157a (2022)]</li> <li>"restr" - restraint .gro file with ionic/peptide <em>z</em> coordinates set to zero</li> </ul> <p> </p>
Membrane interaction and mechanism of LC3 lipidation machinery in autophagy raw GUV data
<p>Raw GUV data of fluorescent protein imaged on a Nikon A1 confocal microscope with a 63 × Plan 359 Apochromat 1.4 NA objective. Three biological replicates were performed for each experimental 360 condition. Identical laser power and gain settings were used during the course of all conditions.</p>
Data from: Free energy analysis of peptide-induced pore formation in lipid membranes by bridging atomistic and coarse-grained simulations
Open the record for dataset details and reuse information.
Pure POPC membrane simulations using Amber Lipid 14 Force Field
<p>Pure POPC membrane simulations using the Amber Lipid 14 force field.</p> <pre>@article{dickson2014lipid14, title={Lipid14: the amber lipid force field}, author={Dickson, Callum J and Madej, Benjamin D and Skjevik, {\AA}ge A and Betz, Robin M and Teigen, Knut and Gould, Ian R and Walker, Ross C}, journal={Journal of chemical theory and computation}, volume={10}, number={2}, pages={865--879}, year={2014}, publisher={ACS Publications} }</pre> <p>The trajectories are centered such that the center of mass of the lipid tails are at the origin. <strong>Please check the imaging again to make sure that there are no problems. </strong></p> <p><strong>The trajectories do not contain water molecules.</strong> </p> <p>Simulation Details:</p> <p>Lipids : 72 POPC lipids, 36 per leaflet</p> <p>Water: 9560 TIP3P water molecules (<strong>water coordinates are not saved</strong>)</p> <p>Temperature: 303 K</p> <p>Pressure: 1 bar</p> <p>Thermostat: Langevin</p> <p>Barostat: Berendsen</p> <p>Pressure coupling: Semi-isotropic</p> <p>Trajectory Length: 100 ns (after 100 ns pre-equilibration)</p> <p>Saving frequency: 100 ps</p> <p>Further details are available at the 04_Run.in file</p> <p>All trajectories started from the same structure but equilibriated for 100 ns independently (using 03_Hold.in)</p>
The Physics of Stratum Corneum Lipid Membranes
<p>Topologies, force-fields and final configurations for the SC lipid systems for which results have been included in the paper "The physics of stratum corneum lipid membranes", by Chinmay Das and Peter D. Olmsted, to be published in Philosophical Transactions A, 2016. (Preprint available at http://arxiv.org/abs/1510.08939 )</p> <p> </p>
POPC lipid membrane, 303K, Charmm36 force field, simulation files and 200 ns trajectory for openMM simulation engine v7
<p>POPC lipid membrane, 303K, Charmm36 force field, simulation files and 200 ns trajectory for for openMM simulation engine v7</p> <p>The starting structure was obtained from CHARMM-GUI Membrane Builder v1.7 (http://www.charmm-gui.org/) online tool. [1]</p> <p>All runs were performed with openMM simulation engine v7 and CHARMM36 additive force field parameters obtained from CHARMM-GUI input files [1]. Conditions: T=303, 128 POPC molecules, 5120 tip3p waters, 200ns trajectory (preceded with equilibration).</p> <p>Note that the provided trajectories are in Gromacs XTC format, whereas NAMD DCD format was generated by openMM. This required trajectory conversion using Gromacs package (v5.1.2) with binary topology file from https://doi.org/10.5281/zenodo.153944 </p> <p>These data were originally obtained for the nmrlipids.blospot.fi project.</p> <p>Find more details at nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi</p> <p>[1] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field, J. Lee et al.<strong>,</strong> JCTC,<strong> </strong>DOI: 10.1021/acs.jctc.5b00935</p>
POPC lipid membrane, 303K, Charmm36 force field, simulation files and 200 ns trajectory for Gromacs MD simulation engine v5.1.2
<p>POPC lipid membrane, 303K, Charmm36 force field, simulation files and 200 ns trajectory for Gromacs MD simulation engine v5.1.2</p> <p>The starting structure was obtained from CHARMM-GUI Membrane Builder v1.7 (http://www.charmm-gui.org/) online tool. [1]</p> <p>All runs were performed with Gromacs 5.1.2 software package and CHARMM36 additive force field parameters obtained from CHARMM-GUI input files [1]. Conditions: T=303, 128 POPC molecules, 5120 tip3p waters, 200ns trajectory (preceded with equilibration)</p> <p>These data were originally obtained for the nmrlipids.blospot.fi project.</p> <p>Find more details at nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi</p> <p>[1] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field, J. Lee et al.<strong>,</strong> JCTC,<strong> </strong>DOI: 10.1021/acs.jctc.5b00935</p>
POPC/Cholesterol (50:50) lipid membrane, 303K, Charmm36 force field from charmm-gui, simulation files and 200 ns trajectory for Gromacs MD simulation engine v5.1.2
<p>The starting structure was obtained from CHARMM-GUI Membrane Builder v1.7 (http://www.charmm-gui.org/) online tool. [1]</p> <p>All runs were performed with Gromacs 5.1.2 software package and CHARMM36 additive force field parameters obtained from CHARMM-GUI input files [1]. Conditions: T=303, 80 POPC and 80 Cholesterol molecules, 7200 tip3p waters, 200ns trajectory (preceded with equilibration)</p> <p>These data were originally obtained for the nmrlipids.blospot.fi project.</p> <p>Find more details at nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi</p> <p>[1] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field, J. Lee et al.<strong>,</strong> JCTC,<strong> </strong>DOI: 10.1021/acs.jctc.5b00935</p>
POPC/Cholesterol (70:30) lipid membrane, 303K, Charmm36 force field, simulation files and 200 ns trajectory for Gromacs MD simulation engine v5.1.2
<p>The starting structure was obtained from CHARMM-GUI Membrane Builder v1.7 (http://www.charmm-gui.org/) online tool. [1]</p> <p>All runs were performed with Gromacs 5.1.2 software package and CHARMM36 additive force field parameters obtained from CHARMM-GUI input files [1]. Conditions: T=303, 128 POPC molecules, 5120 tip3p waters, 200ns trajectory (preceded with equilibration)</p> <p>These data were originally obtained for the nmrlipids.blospot.fi project.</p> <p>Find more details at nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi</p> <p>[1] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field, J. Lee et al.<strong>,</strong> JCTC,<strong> </strong>DOI: 10.1021/acs.jctc.5b00935</p>
POPC/Cholesterol (70:30) lipid membrane, 303K, Charmm36 force field, simulation files and 100 ns trajectory for openMM simulation engine v7
<p>The starting structure was obtained from CHARMM-GUI Membrane Builder v1.7 (http://www.charmm-gui.org/) online tool. [1]</p> <p>All runs were performed with openMM simulation engine v7 and CHARMM36 additive force field parameters obtained from CHARMM-GUI input files [1]. Conditions: T=303, 84 POPC and 36 Cholesterol molecules, 4800 tip3p waters, 100ns trajectory (preceded with equilibration).</p> <p>These data were originally obtained for the nmrlipids.blospot.fi project.</p> <p>Find more details at nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi</p> <p>[1] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field, J. Lee et al.<strong>,</strong> JCTC,<strong> </strong>DOI: 10.1021/acs.jctc.5b00935</p>
POPC/Cholesterol (50:50) lipid membrane, 303K, Charmm36 force field from charmm-gui, simulation files and 100 ns trajectory for openMM simulation engine v7
<p>The starting structure was obtained from CHARMM-GUI Membrane Builder v1.7 (http://www.charmm-gui.org/) online tool. [1]</p> <p>All runs were performed with openMM simulation engine v7 and CHARMM36 additive force field parameters obtained from CHARMM-GUI input files [1]. Conditions: T=303, 80 POPC and 80 Cholesterol molecules, 7200 tip3p waters, 100ns trajectory (preceded with equilibration)</p> <p>These data were originally obtained for the nmrlipids.blospot.fi project.</p> <p>Find more details at nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi</p> <p>[1] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field, J. Lee et al.<strong>,</strong> JCTC,<strong> </strong>DOI: 10.1021/acs.jctc.5b00935</p>
POPC/Cholesterol (70:30) lipid membrane, 303K, Charmm36 force field through the use of Gromacs input files, simulation files and 100 ns trajectory for openMM simulation engine v7
<p>The starting structure was obtained from CHARMM-GUI Membrane Builder v1.7 (http://www.charmm-gui.org/) online tool. [1]</p> <p>All runs were performed with openMM simulation engine v7 and CHARMM36 additive force field parameters obtained from CHARMM-GUI input files [1]. Specifically, Gromacs file format provided by [1] was specifically used for this simulation.</p> <p>Conditions: T=303, 84 POPC and 36 Cholesterol molecules, 4800 tip3p waters, 100ns trajectory (preceded with equilibration).</p> <p>These data were originally obtained for the nmrlipids.blospot.fi project.</p> <p>Find more details at nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi</p> <p>[1] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field, J. Lee et al.<strong>,</strong> JCTC,<strong> </strong>DOI: 10.1021/acs.jctc.5b00935</p>
POPC/Cholesterol (50:50) lipid membrane, 303K, Charmm36 force field, simulation files and 100 ns trajectory for GROMACS simulation engine v5
<p>All runs were performed with GROMACS simulation engine v5 and CHARMM36 additive force field parameters obtained from MacKerell lab website (http://mackerell.umaryland.edu/charmm_ff.shtml, also available at</p> <p>https://doi.org/10.5281/zenodo.209080). Conditions: T=303, 80 POPC and 80 Cholesterol molecules, 7200 tip3p waters, 100ns trajectory (preceded with equilibration). </p> <p>These data were originally obtained for the nmrlipids.blospot.fi project.</p> <p>Find more details at nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.