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opencc-by-4.0Jun 2020View details →

Biogenic supported lipid bilayers as a tool to investigate nano-bio interfaces

Colorimentric Nanoplasmonic Assay (CONAN) assay of EVs from TRAMP cells. UV/VIS spectrophotometer analysis of samples of EVs from TRAMP cell line incubated with gold nanoparticles, following the protocol described in Montis et al. <a href="https://doi.org/10.1016/j.jcis.2020.03.014">https://doi.org/10.1016/j.jcis.2020.03.014</a>

Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% DOPS with Na+ counterions using ff99 Ions

System: Symmetric bilayer of anionic DOPS (1,2-Dioleoyl-sn-glycero-3-phosphoserine 100 mol-%) lipids with sodium (Na+) counter ions. Number of DOPS: 128. Number of Na+-ions: 128. Number of waters: 4480. Lipid model: 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)]. Ion models:  Amber ff99 [J Åqvist J. Phys. Chem. 94 8021 (1990)]. Water model: TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein J. Chem. Phys. 79 926 (1983)]. Simulation engine: Amber16 [DA Case et al. AMBER 2017 UCSF (2017)]. Number of independent repeats per setup: 2. Trajectory lengths per repeat: 400 ns + 100 ns. Previously equilibrated for: 100 ns. Sampling rate: every 10 ps. Time integration step: 2 fs. Thermodynamic ensemble: NpT.  Temperature coupling: 'Langevin' at T = 303 K. Pressure coupling: 'Berendsen' [J. Chem. Phys. 81 3684 (1984); J. Chem. Phys. 103 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension. Electrostatics: PME [J. Chem. Phys. 98 10089 (1993); J. Chem. Theory Comput. 9 3878 (2013)]. Van der Waals: Turned off between 1.0 nm and 1.5 nm. Constraints: Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [J. Comput. Phys. 23 327 (1977)], in water using SETTLE [J. Comput. Chem. 13 952 (1992)]. Used in publications: OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).

Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% POPS with Na+ counterions using Joung-Cheatham Ions

System: Symmetric bilayer of anionic POPS (palmitoyl-oleoyl-phosphatidylserine 100 mol-%) lipids with sodium (Na+) counter ions. Number of POPS: 128. Number of Na+-ions: 128. Number of waters: 4480. Lipid model: 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)]. Ion model: Joung–Cheatham [IS Joung, TE Cheatham III J. Phys. Chem. B 112 9020 (2008)]. Water model: TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein J. Chem. Phys. 79 926 (1983)]. Simulation engine: Amber16 [DA Case et al. AMBER 2017 UCSF (2017)]. Number of independent repeats per setup: 2. Trajectory lengths per repeat: 400 ns + 100 ns. Previously equilibrated for: 100 ns. Sampling rate: every 10 ps. Time integration step: 2 fs. Thermodynamic ensemble: NpT.  Temperature coupling: 'Langevin' at T = 298 K. Pressure coupling: 'Berendsen' [J. Chem. Phys. 81 3684 (1984); J. Chem. Phys. 103 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension. Electrostatics: PME [J. Chem. Phys. 98 10089 (1993); J. Chem. Theory Comput. 9 3878 (2013)]. Van der Waals: Turned off between 1.0 nm and 1.5 nm. Constraints: Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [J. Comput. Phys. 23 327 (1977)], in water using SETTLE [J. Comput. Chem. 13 952 (1992)]. Used in publications: OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).

Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% POPS with Na+ counterions using ff99 ions

System: Symmetric bilayer of anionic POPS (palmitoyl-oleoyl-phosphatidylserine 100 mol-%) lipids with sodium (Na+) counter ions. Number of POPS: 128. Number of Na+-ions: 128. Number of waters: 4480. Lipid model: 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)]. Ion model: Amber ff99 [J Åqvist J. Phys. Chem. 94 8021 (1990)]. Water model: TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein J. Chem. Phys. 79 926 (1983)]. Simulation engine: Amber16 [DA Case et al. AMBER 2017 UCSF (2017)]. Number of independent repeats per setup: 2. Trajectory lengths per repeat: 400 ns + 100 ns. Previously equilibrated for: 100 ns. Sampling rate: every 10 ps. Time integration step: 2 fs. Thermodynamic ensemble: NpT.  Temperature coupling: 'Langevin' at T = 298 K. Pressure coupling: 'Berendsen' [J. Chem. Phys. 81 3684 (1984); J. Chem. Phys. 103 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension. Electrostatics: PME [J. Chem. Phys. 98 10089 (1993); J. Chem. Theory Comput. 9 3878 (2013)]. Van der Waals: Turned off between 1.0 nm and 1.5 nm. Constraints: Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [J. Comput. Phys. 23 327 (1977)], in water using SETTLE [J. Comput. Chem. 13 952 (1992)]. Used in publications: OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).

Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% DOPS with Na+ counterions using Joung-Cheetham Ions

System: Symmetric bilayer of anionic DOPS (1,2-Dioleoyl-sn-glycero-3-phosphoserine 100 mol-%) lipids with sodium (Na+) counter ions. Number of DOPS: 128. Number of Na+-ions: 128. Number of waters: 4480. Lipid model: 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)]. Ion models: Joung–Cheatham [IS Joung, TE Cheatham III J. Phys. Chem. B 112 9020 (2008)]. Water model: TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein J. Chem. Phys. 79 926 (1983)]. Simulation engine: Amber16 [DA Case et al. AMBER 2017 UCSF (2017)]. Number of independent repeats per setup: 2. Trajectory lengths per repeat: 400 ns + 100 ns. Previously equilibrated for: 100 ns. Sampling rate: every 10 ps. Time integration step: 2 fs. Thermodynamic ensemble: NpT.  Temperature coupling: 'Langevin' at T = 303 K. Pressure coupling: 'Berendsen' [J. Chem. Phys. 81 3684 (1984); J. Chem. Phys. 103 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension. Electrostatics: PME [J. Chem. Phys. 98 10089 (1993); J. Chem. Theory Comput. 9 3878 (2013)]. Van der Waals: Turned off between 1.0 nm and 1.5 nm. Constraints: Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [J. Comput. Phys. 23 327 (1977)], in water using SETTLE [J. Comput. Chem. 13 952 (1992)]. Used in publications: OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).

opencc-by-4.0Oct 2023View details →

Gaussian-accelerated Molecular Dynamics simulations of CCR8-CCL1-Gprotein complex in a POPC lipid bilayer

Gaussian-accelerated Molecular Dynamics simulations of the CCR8-CCL1-Gprotein complex in a POPC lipid bilayer. Simulation system was prepared with OpenMM v7.7 and simulations were performed using the GaMD-OpenMM package (https://github.com/MiaoLab20/gamd-openmm) with a modification to include the MDTraj h5 file formate reporter as the output file format. These simulations were then converted to pdb topologies and dcd trajectories using MDTraj. Files include:CCL1_CCR8_noSer23_oriented_repaired1_system.pdb : system topologyCCL1_CCR8_config.xml : config for running GaMD-OpenMMCCL1_CCR8_N_1ns_imaged_structure.pdb : initial topology/structureCCL1_CCR8_N_1ns_imaged_trajectory.dcd : trajectory file Simulations can be loaded in python using MDTraj:import mdtrajtrj = mdtraj.load(<dcd file>, top=<pdb file>)

opencc-by-4.0Dec 2016View details →

Set simulations small pure bilayers with cholesterol (max 128 lipids) using charmm36 ff in gromacs (DPPC)

Collection simulations of small pure bilayers (max 128 phospholipids) with cholesterol in gromacs using the charmm36 force field. The list of systems describing their particular simulation conditions can be found below: <ol> <li>DPPC_128_CHL1_32_310K</li> </ol> For further information read the Readme file provided for each simulation.

opencc-by-4.0Oct 2017View details →

Simulations POPC bilayers (512 lipids) using charmm36 ff in gromacs

Collection simulations of POPC (512 lipids) bilayers in gromacs using the charmm36 force field. The list of systems can be found below where the several parameter are: <ol> <li>POPC_512_310K (500ns)</li> <li>POPC_512_NaCl_150mM_310K (500ns)</li> <li>POPC_512_NaCl_150mM_310K_tip3p (500ns)</li> <li>POPC_512_NaCl_Dang_150mM_310K (500ns)</li> </ol> For further information read the Readme file provided for each simulation.

dryad40/100

Reconstitution of phase-separated signaling clusters and actin polymerization on supported lipid bilayers

Liquid–liquid phase separation driven by weak interactions between multivalent molecules contributes to the cellular organization by promoting the formation of biomolecular condensates. At membranes, phase separation can promote the assembly of transmembrane proteins with their cytoplasmic binding partners into micron-sized membrane-associated condensates. For example, phase separation promotes clustering of nephrin, a transmembrane adhesion molecule, resulting in increased Arp2/3 complex-dependent actin polymerization. In vitro reconstitution is a powerful approach to understanding phase separation in biological systems. With a bottom-up approach, we can determine the molecules necessary and sufficient for phase separation, map the phase diagram by quantifying de-mixing over a range of molecular concentrations, assess the material properties of the condensed phase using fluorescence recovery after photobleaching (FRAP), and even determine how phase separation impacts downstream biochemical activity. Here, we describe a detailed protocol to reconstitute nephrin clusters on supported lipid bilayers with purified recombinant protein. We also describe how to measure Arp2/3 complex-dependent actin polymerization on bilayers using fluorescence microscopy. These different protocols can be performed independently or combined as needed. These general techniques can be applied to reconstitute and study phase-separated signaling clusters of many different receptors or to generally understand how actin polymerization is regulated at membranes.

opencc-zeroMay 2023View details →

opencc-by-4.0Jun 2023View details →

Lipid membrane simulations with flat-bottom and double-bilayer setups, part 2/2

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> 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)] 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> Abbreviations in the names of simulation files: <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 z coordinates set to zero</li> </ul>

opencc-by-4.0Jun 2023View details →

Lipid membrane simulations with flat-bottom and double-bilayer setups, part 1/2

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> 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)] 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> Abbreviations in the names of simulation files: <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 z coordinates set to zero</li> </ul>

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Data from: Functional regulation of aquaporin dynamics by lipid bilayer composition

Open the record for dataset details and reuse information.

publicFeb 2024View details →

dryad40/100

Reconstitution of phase-separated signaling clusters and actin polymerization on supported lipid bilayers

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publicMay 2023View details →

opencc-by-4.0Dec 2019View details →

Simulation of a POPE bilayer, lipid model based on OPLS-aa by Rog et al.

A 500 ns-long simulation of a bilayer consisting of 144 POPE lipids and 40 water molecules per lipid. All GROMACS-compatible input and output files are required. Topologies are provided by their original authors. If you use the topologies, please cite the papers indicated in the POPE.itp file.

opencc-zeroJul 2015View details →

DOPC lipid bilayer simulation trajectory and files from Franova et al. BBA 1838 (2014) 1406–1411

Simulation files for pure DOPC (no pyrene present) simulation from "Can pyrene probes be used to measure lateral pressure profiles of lipid membranes? Perspective through atomistic simulations" Franova et al. Biochimica et Biophysica Acta 1838 (2014) 1406–1411

DOPC lipid bilayer with PYR6 simulation trajectory and files from Franova et al. BBA 1838 (2014) 1406–1411

Simulation files for DOPC with PYR6 simulation from "Can pyrene probes be used to measure lateral pressure profiles of lipid membranes? Perspective through atomistic simulations" Franova et al. Biochimica et Biophysica Acta 1838 (2014) 1406–1411

DOPC lipid bilayer with PYR8 simulation trajectory and files from Franova et al. BBA 1838 (2014) 1406–1411

Simulation files for DOPC with PYR8 simulation from "Can pyrene probes be used to measure lateral pressure profiles of lipid membranes? Perspective through atomistic simulations" Franova et al. Biochimica et Biophysica Acta 1838 (2014) 1406–1411

DOPC lipid bilayer with PYR4 simulation trajectory and files from Franova et al. BBA 1838 (2014) 1406–1411

Simulation files for DOPC with PYR4 simulation from "Can pyrene probes be used to measure lateral pressure profiles of lipid membranes? Perspective through atomistic simulations" Franova et al. Biochimica et Biophysica Acta 1838 (2014) 1406–1411

DOPC lipid bilayer with PYR10 simulation trajectory and files from Franova et al. BBA 1838 (2014) 1406–1411

Simulation files for DOPC with PYR10 simulation from "Can pyrene probes be used to measure lateral pressure profiles of lipid membranes? Perspective through atomistic simulations" Franova et al. Biochimica et Biophysica Acta 1838 (2014) 1406–1411