Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
56
datasets available to search
ShareScore release 0.9.0
Dataset results
56 results for “DPPC”
OpenMM simulations of DPPC using the CHARMM Drude2023 force field
<p>The dataset contains a PSF, a formatted coordinate file (CRD), and DCD files with the final 200 ns from<br> each of 3 replicate simulations from the paper</p> <p><br> <strong>Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion:<br> Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids</strong><br> Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,*<br> Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda*<br> https://doi.org/10.1021/acs.jctc.3c00203</p> <p><br> DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file; each file has frames spaced at 10 ps over a 50 ns interval.</p>
Movies of the ripple phase in DPPC bilayers
<p>This was a cover article in the Biophysical Journal:</p> <ul> <li><strong>Cover article:</strong> <a href="https://doi.org/10.1016/j.bpj.2022.11.024"><em>Elucidating Lipid Conformations in the Ripple Phase: Machine Learning Reveals Four Lipid Populations</em></a></li> <li><strong>Biophys J Blog:</strong> <a href="https://www.biophysics.org/blog/ripple-me-this-elucidating-lipid-conformations-in-the-ripple-phase"><em>Ripple Me This: Elucidating Lipid Conformations in the Ripple Phase</em></a></li> </ul> <p><strong>Reference:</strong></p> <ul> <li><em>Elucidating Lipid Conformations in the Ripple Phase: Machine Learning Reveals Four Lipid Populations</em>. Davies, Matthew; Reyes-Figueroa, A. D.; Gurtovenko, Andrey A.; Frankel, Daniel; <a href="https://www.researchgate.net/profile/Mikko-Karttunen-2">Karttunen, Mikko</a>. <em>Biophys. J.</em> 122, P442-450 (2023). DOI link: <a href="https://doi.org/10.1016/j.bpj.2022.11.024">https://doi.org/10.1016/j.bpj.2022.11.024</a></li> </ul>
256 DPPC Molecules bilayer in pure Water, simulated at 288K (gel) or 358K (fluid)
<p><strong>Publication:</strong> MLLPA: A Machine Learning-assisted Python module to study phase-specific events in lipid membranes</p> <p><strong>Published on:</strong> 08 April 2021</p> <p><strong>Journal</strong>: <em><a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.26508">J Comp Chem</a>, </em>2021, DOI: 10.1002/jcc.26508</p> <p><strong>Description</strong>: Simulation files used to train our Python module to identify the thermodynamic phase of individual lipid molecules in a bilayer, as well as the simulation files analysed by the machine learning models. More information on the module can be found on <a href="https://vivien-walter.github.io/mllpa/">its website</a>.</p> <p>The training files are named dppc_gel.gro and dppc_fluid.gro. They respectively correspond to the final frame of the systems simulated at 288K and 358K. All other files are the files analysed by the module.</p> <p><strong>System composition:</strong></p> <ul> <li>DPPC molecules: 256 with 130 atoms each</li> <li>Water molecules: 42,492 with 3 atoms each </li> <li>Simulation box dimensions (approx.): 9 x 9 x 20 nm</li> </ul> <p><strong>Simulation details:</strong></p> <ul> <li>Software: Gromacs (v. 2020)</li> <li>Forcefield: Charmm36 (v. June 2015) - Water: TIP3P</li> <li>Thermostat: Nose-hoover (0.4ps, 2 groups)</li> <li>Barostat: Parrinello-Rahman semi-isotropic (2.0ps, 1.0 bar on each axis, 4.5e-5 bar-1)</li> <li>Duration: 25 ns (after stabilisation)</li> </ul>
DPPC @ 323K, new FF by Tjörnhammar & Edholm
<p>Trajectory of 144 DPPC molecules @ 323K. Force field and initial structure from http://pubs.acs.org/doi/full/10.1021/ct500589z</p>
DPPC_Slipids
<p>MD simulation trajectory and related files for fully hydrated DPPC bilayer. Slipids force field (doi:10.1021/jp212503e) was used with Gromacs 4.6.6. Conditions: T=323K, 128 lipids, 3840 tip3p waters.</p>
DPPC_Berger
<p>MD simulation trajectory and related files for fully hydrated DPPC bilayer. Berger-DPPC-98 force field delivered by Peter Tieleman (http://wcm.ucalgary.ca/tieleman/downloads) was used with Gromacs 4.6.6. Conditions: T=323K, 72 lipids, 2880 SPC waters. 60 ns trajectory.</p>
MD simulation trajectory and related files for DPPC bilayer in full hydration (Poger GROMOS 53A6_L, Gromacs 4.0.7, PME, traj 2)
<p>Equilibrated DPPC lipid bilayer simulation ran with Gromacs 4.0.7 using PME (Particle Mesh Ewald) for computing electrostatics, Poger GROMOS 53A6_L force field in full hydration (dx.doi.org/10.1002/jcc.21396), 100ns, T=323K, 128 DPPC molecules, 5841 water molecules. This data is ran for the nmrlipids.blospot.fi project. More details from nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi. If data is used, please cite nmrlipids.blogspot.fi project and the original publication of the parameters (dx.doi.org/10.1002/jcc.21396).</p>
MD simulation trajectory and related files for DPPC bilayer in full hydration (Poger GROMOS 53A6_L, Gromacs 4.0.7, Reaction Field, traj 1)
<p>Equilibrated DPPC lipid bilayer simulation ran with Gromacs 4.0.7 using Reaction Field for computing electrostatics, Poger GROMOS 53A6_L force field in full hydration (dx.doi.org/10.1002/jcc.21396), 100ns, T=323K, 128 DPPC molecules, 5841 water molecules. This data is ran for the nmrlipids.blospot.fi project. More details from nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi. If data is used, please cite nmrlipids.blogspot.fi project and the original publication of the parameters (dx.doi.org/10.1002/jcc.21396).</p>
MD simulation trajectory and related files for DPPC bilayer in full hydration (Poger GROMOS 53A6_L, Gromacs 4.0.7, Reaction Field, traj 2)
<p>Equilibrated DPPC lipid bilayer simulation ran with Gromacs 4.0.7 using Reaction Field for computing electrostatics, Poger GROMOS 53A6_L force field in full hydration (dx.doi.org/10.1002/jcc.21396), 100ns, T=323K, 128 DPPC molecules, 5841 water molecules. This data is ran for the nmrlipids.blospot.fi project. More details from nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi. If data is used, please cite nmrlipids.blogspot.fi project and the original publication of the parameters (dx.doi.org/10.1002/jcc.21396).</p> <p> </p>
MD simulation trajectory and related files for DPPC bilayer in full hydration (Poger GROMOS 53A6_L, Gromacs 4.0.7, PME, traj 1)
<p>Equilibrated DPPC lipid bilayer simulation ran with Gromacs 4.0.7 using PME (Particle Mesh Ewald) for computing electrostatics, Poger GROMOS 53A6_L force field in full hydration (dx.doi.org/10.1002/jcc.21396), 100ns, T=323K, 128 DPPC molecules, 5841 water molecules. This data is ran for the nmrlipids.blospot.fi project. More details from nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi. If data is used, please cite nmrlipids.blogspot.fi project and the original publication of the parameters (dx.doi.org/10.1002/jcc.21396).</p>
MD simulation trajectory and related files for DPPC bilayer (GAFFlipid, Gromacs 4.5)
<p>Equilibrated DPPC lipid bilayer simulation ran with Gromacs 4.5, GAFFlipid force field (http://dx.doi.org/10.1039/C2SM26007G), 50ns, T=323K, 72 DPPC molecules, 2197 water molecules. This data is ran for the nmrlipids.blospot.fi project. More details from nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi. If data is used, please cite nmrlipids.blogspot.fi project and the original publication of the parameters: Dickson et al. Soft Matter, 2012,8, 9617-9627 http://dx.doi.org/10.1039/C2SM26007G.</p>
DPPC_Berger_OPLS06
<p>MD simulation trajectory and related files for fully hydrated DPPC bilayer. The OPLSAA-compatible Berger-DPPC-06 force field (DOI:10.1088/0953--8984/18/28/S07) was used with Gromacs 5.1-beta. Conditions: T=323K, 72 lipids, 2880 SPC waters. 120 ns trajectory, last 60 ns analyzed.</p> <p> </p>
Simulation files for DPPC lipid membrane with Slipids force field for Gromacs MD simulation engine
<p>The goal was to study the effect of salt on the order <br /> parameters of the lipid head group and the glycerol <br /> backbone for the NMRlipids project, see <br /> http://nmrlipids.blogspot.fi for more information.</p>
Simulation files for DPPC lipid membrane with Slipids force field for Gromacs MD simulation engine
<p>the files denoted with 350 resp 700 resp 1000 have NaCl concentrations of 850 resp 1750 resp 2570 mM.</p> <p> </p> <p>The goal was to study the effect of salt on the order parameters of the lipid head group and the glycerol backbone for the NMRlipids project, see http://nmrlipids.blogspot.fi for more information.</p>
DPPC monolayer simulations with Slipids+OPC
<p>DPPC monolayers simulated at a varying area per lipid in the NVT ensemble. The Slipids lipid model [1] is employed together with the 4-point OPC water model [2].</p> <p>Each system contains two monolayers with 64 lipids each with a change in simulation box size, except for the system titled 'large'. '200large' contains 128 lipids per monolayer, '400large' 64 lipids per monolayer and '1500large' 17 lipids per monolayer. These 'large' monolayers all have the same simulation box size. All monolayers are separated by a water slab, and surrounded by vacuum. </p> <p>The number in the filename corresponds to the area per lipid in Ångströms. The starting structures were taken from [3], which also provides detailed information on system setup. The simulations in [3] used TIP3P water, which was replaced by OPC, followed by energy minimization and production runs. The 'large' monolayers were generated from the system 'md100' by replicating it four-fold (2x2) and subsequently removing lipids until the desired area per lipid was reached.</p> <p>All trajectories, 100 ns long, are simulated with Gromacs 4.6.x [4] using the parameters given in the mdp file. The topologies for the lipids can be obtained from http://www.fos.su.se/~sasha/SLipids/Downloads.html and for the OPC water model from https://bioinformatics.cs.vt.edu/~izadi/ .</p> <p>Note that .top and .ndx files are for all systems except for the "large" ones.</p> <p>[1] DOI: 10.1021/jp101759q<br> [2] DOI: 10.1021/jz501780a<br> [3] DOI: 10.1016/j.bbamem.2016.09.015<br> [4] DOI: 10.1093/bioinformatics/btt055</p>
DPPC monolayer simulations with Charmm36+OPC @ 323 K
<p>DPPC monolayers simulated at a varying area per lipid in the NVT ensemble. The Charmm36 lipid model [1] is employed together with the 4-point OPC water model [2].</p> <p>Each system contains two monolayers with 64 lipids each with a change in simulation box size, except for the system titled 'large'. '200large' contains 128 lipids per monolayer, '400large' 64 lipids per monolayer and '1500large' 17 lipids per monolayer. These 'large' monolayers all have the same simulation box size. All monolayers are separated by a water slab, and surrounded by vacuum. </p> <p>The number in the filename corresponds to the area per lipid in Ångströms. The starting structures were taken from [4], which also provides detailed information on system setup. The simulations in [3] used Slipids lipid model and TIP3P water model, which were replaced by Charmm36 lipid model and the OPC water model, followed by energy minimization and production runs. The 'large' monolayers were generated from the system 'md100' by replicating it four-fold (2x2) and subsequently removing lipids until the desired area per lipid was reached.</p> <p>All trajectories, 100 ns long, are simulated with Gromacs 5.0.x [4] using the parameters given in the mdp file. The topologies for the lipids can be obtained from Charmm-GUI and for the OPC water model from https://bioinformatics.cs.vt.edu/~izadi/ .</p> <p>[1] DOI: 10.1021/jp101759q<br> [2] DOI: 10.1021/jz501780a<br> [3] DOI: 10.1016/j.bbamem.2016.09.015<br> [4] DOI: 10.1016/j.softx.2015.06.001</p>
144 NaK channel proteins in a DPPC membrane
<p>144 NaK channels embedded in a DPPC membrane formed by 14400 lipid molecules simulated for 25 microseconds using the protein model by Sansom et al. [1,2] and the Martini lipid model [3]. The membrane is solvated by a total of 294163 water beads, counter ions, and a NaCl concentration of 154 mM. Files are compatible with Gromacs 4.6. and above.</p> <p>[1] Peter Bond and Mark Sansom, Insertion and assembly of membrane proteins via simulation, J. Am. Chem. Soc., 2006, 128 (8), pp 2697–2704</p> <p>[2] Kathryn A. Scott et al., Coarse-Grained MD Simulations of Membrane Protein-Bilayer Self-Assembly, Structure, 2008, 16 (4), pp 621–630</p> <p>[3] Siewert J. Marrink et al., Coarse Grained Model for Semiquantitative Lipid Simulations, J. Phys. Chem. B, 2004, 108 (2), pp 750–760</p>
DPPC monolayer simulations with Charmm36+TIP(S)3P @ 310 K
<p>POPC monolayers simulated at a varying area per lipid in the NVT ensemble. The Charmm36 lipid model [1] is employed together with the Charmm-specific TIP3P (TIPS3P) water model.</p> <p>Each system contains two monolayers with 64 lipids each. These monolayers are separated by a water slab, and surrounded by vacuum. </p> <p>The number in the filename corresponds to the area per lipid in Ångströms. The starting structures were taken from [2], which also provides detailed information on system setup. The simulations in [2] used TIP3P water and Slipids lipids, which were replaced by TIPS3P water and Charmm36 lipids, followed by energy minimization and production runs.</p> <p>All trajectories, 100 ns long, are simulated with Gromacs 5.0.x [3] using the parameters given in the mdp file. The topologies for the lipids can be obtained from Charmm-GUI.</p> <p>[1] DOI: 10.1021/jp101759q<br> [2] DOI: 10.1016/j.bbamem.2016.09.015<br> [3] DOI: 10.1016/j.softx.2015.06.001</p>
DPPC monolayer simulations with Charmm36+OPC @ 310 K
<p>POPC monolayers simulated at a varying area per lipid in the NVT ensemble. The Charmm36 lipid model [1] is employed together with the 4-point OPC water model [2].</p> <p>Each system contains two monolayers with 64 lipids each. These monolayers are separated by a water slab, and surrounded by vacuum. </p> <p>The number in the filename corresponds to the area per lipid in Ångströms. The starting structures were taken from [3], which also provides detailed information on system setup. The simulations in [3] used TIP3P water and Slipids lipids, which were replaced by OPC water and Charmm36 lipids, followed by energy minimization and production runs.</p> <p>All trajectories, 100 ns long, are simulated with Gromacs 5.0.x [4] using the parameters given in the mdp file. The topologies for the lipids can be obtained from Charmm-GUI and for the OPC water model from https://bioinformatics.cs.vt.edu/~izadi/ </p> <p>[1] DOI: 10.1021/jp101759q<br> [2] DOI: 10.1021/jz501780a<br> [3] DOI: 10.1016/j.bbamem.2016.09.015<br> [4] DOI: 10.1016/j.softx.2015.06.001</p>
Large DPPC monolayer simulations with Charmm36+OPC @ 310 K (Part 1/2)
<p>DPPC monolayers simulated at a varying area per lipid in the NVT ensemble. The Charmm36 lipid model [1] is employed together with the 4-point OPC water model [2]. Each system contains two monolayers with 256 lipids each. These monolayers are separated by a water slab, and surrounded by vacuum. </p> <p>The number in the filename corresponds to the area per lipid in Ångströms. The starting structures were generated by setting up a POPC monolayer system with an area per lipid of 50 Å^2, followed by a simulation during which the monolayer area was expanded using PLUMED. Next, POPC was replaced by DPPC, and the systems were energy minimized. Systems with area smaller than 51 Å^2 were generated by compressing the DPPC monolayer system with PLUMED.</p> <p>All trajectories, 100–200 ns long (until convergence of surface tension), are simulated with Gromacs 5.0.x [3] using the default Charmm36 monolayer simulations parameters given in the mdp file. Topology (.top) and index files are also common for all simulations. The topologies (.itp) for the lipids can be obtained from Charmm-GUI and for the OPC water model from https://bioinformatics.cs.vt.edu/~izadi/ .</p> <p>Part 2 of this upload is available at https://doi.org/10.5281/zenodo.838641</p> <p>Matti Javanainen, Antti Lamberg, Lukasz Cwiklik, Ilpo Vattulainen, and O. H. Samuli Ollila. <em>Atomistic Model for Nearly Quantitative Simulations of Langmuir Monolayers</em>, Langmuir <strong>2018</strong> 34 (7), 2565-2572, DOI: 10.1021/acs.langmuir.7b02855</p> <p>[1] DOI: 10.1021/jp101759q<br> [2] DOI: 10.1021/jz501780a<br> [3] DOI: 10.1016/j.softx.2015.06.001</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.