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119 results for “Gromacs”
GMX_lipid17.ff: Gromacs Port of the amber LIPID17 force field
<p>This is a Gromacs port of the amber LIPID17 force field. To use this force field, the user can construct the lipid bilayer using Charmm-GUI and convert the atom names to the amber atom names using charmmlipid2amber.py. This port has also retained the modular feature of the LIPID17 force field, where the user can customise the head group or acryl chain and use pdb2gmx to construct the topology.</p> <p>The coordinate files for the amber lipids can also be obtained from the `gro` folder. The force field `lipid17.ff`, itp file `lipid17.itp` and a custom PI head group are all included in the attached compressed file. For the details of the generation and validation protocol, please consult the relevant <a href="https://github.com/xiki-tempula/gmx_lipid17.ff">Github</a> page.</p>
Aldeghi et al. Files for absolute free energy calculations in gromacs.
<p>These are the files for performing absolute free energy calculations using gromacs as reported in "Accurate calculation of the absolute free energy of binding for drug molecules. Aldeghi M, Heifetz A, Bodkin MJ, Knapp S, Biggin PC.<br /> Chem Sci. 2016 Jan 14;7(1):207-218. DOI: 10.1039/C5SC02678D"</p> <p> </p> <p>The files should prove useful for anyone wishing to try out their own methodology for comparison purposes or even just to repeat the work on a known dataset. The data is presented as a zip archive that should unpack into a directory called "Aldeghi-et-al-chemical-science-2016". There are four sub-directories in there and a README.txt file which should explain the details of the data.</p> <p> </p>
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>
Set simulations small pure bilayers with cholesterol (max 128 lipids) using charmm36 ff in gromacs (DPPC)
<p>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:</p> <ol> <li>DPPC_128_CHL1_32_310K</li> </ol> <p>For further information read the Readme file provided for each simulation.</p>
Simulations POPC bilayers (512 lipids) using charmm36 ff in gromacs
<p>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:</p> <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> <p>For further information read the Readme file provided for each simulation.</p>
All-atom Gromacs Trajectory of POPC/TOCL bilayer mixture
<p>All-atom bilayer mixture of POPC/TOCL 1:1 simulated in an NPT ensemble with Gromacs and the CHARMM36 force field from Castillo et al, 2022, Mol. Pharmaceutics. 19:1839-1852 (<a href="https://doi.org/10.1021/acs.molpharmaceut.1c00926">https://doi.org/10.1021/acs.molpharmaceut.1c00926</a>). The trajectory represents 540 ns with frames output every 20 ps. The bilayer has 120 lipids total (60 lipids per leaflet) and is hydrated with 100 waters/lipid and sodium ions to neutralize the system. The simulation was done at 37C (310.15K).</p> <p>POPC is 16:0,18:1 PC; TOCL is tetraoleoyl cardiolipin</p>
All-atom Gromacs Trajectory of POPC/POPE/TOCL bilayer mixture
<p>All-atom bilayer mixture of POPC/POPE//TOCL 50/25/25 mol% simulated in an NPT ensemble with Gromacs and the CHARMM36 force field from Castillo et al, 2022, Mol. Pharmaceutics. 19:1839-1852 (<a href="https://doi.org/10.1021/acs.molpharmaceut.1c00926">https://doi.org/10.1021/acs.molpharmaceut.1c00926</a>). The trajectory represents 570 ns with frames output every 20 ps. The bilayer has 120 lipids total (60 lipids per leaflet) and is hydrated with 75 waters/lipid and sodium ions to neutralize the system. The simulation was done at 37C (310.15K).</p> <p>POPC is 16:0,18:1 PC; POPE is 16:0,18:1 PE; TOCL is tetraoleoyl cardiolipin</p>
All-atom Gromacs Trajectory of POPE/TOCL bilayer mixture
<p>All-atom bilayer mixture of POPE/TOCL 1:1 simulated in an NPT ensemble with Gromacs and the CHARMM36 force field from Castillo et al, 2022, Mol. Pharmaceutics. 19:1839-1852 (<a href="https://doi.org/10.1021/acs.molpharmaceut.1c00926">https://doi.org/10.1021/acs.molpharmaceut.1c00926</a>). The trajectory represents 530 ns with frames output every 20 ps. The bilayer has 120 lipids total (60 lipids per leaflet) and is hydrated with 100 waters/lipid and sodium ions to neutralize the system. The simulation was done at 37C (310.15K).</p> <p>POPE is 16:0,18:1 PE; TOCL is tetraoleoyl cardiolipin</p>
charmm2gmx: An Automated Method to Port the CHARMM Additive Force Field to GROMACS
<p>Validation dataset for the paper "charmm2gmx: An Automated Method to Port the CHARMM Additive Force Field to GROMACS". The dataset includes molecular dynamics input and output files, as well as scripts for running the simulations and analyzing the results, used for validating the ported CHARMM parameters.</p> <p>CHARMM is one of the most widely used biomolecular force fields. Although developed in close connection with a dedicated molecular simulation engine of the same name, it is also usable with other codes. GROMACS is a well-established, highly optimized and multi-purpose software for molecular dynamics, versatile enough to accommodate many different force field potential functions and the associated algorithms. Due to conceptional differences related to software design and the large amount of numeric data inherent to residue topologies and parameter sets, conversion from one software format to another is not straightforward. Here, we present an automated and validated means to port the CHARMM force field to a format read by the GROMACS engine, harmonizing the different capabilities of the two codes in a self-documenting and reproducible way, with a bare minimum of user interaction required. Being based entirely on the upstream data files, the presented approach does not involve any hard-wired/boilerplate code, in contrast with previous attempts to solve the same problem. The heuristic approach used for perceiving local internal geometry is directly applicable for analogous transformations of other force fields.</p> <p> </p>
Inputs for computational electrophysiology of the Glycine Receptor with GROMACS 19
<p>Inputs for computational electrophysiology of the Glycine Receptor (D&B-open model, doi:10.5281/zenodo.3476169) with GROMACS 19 and the CHARMM36 force-field, using:</p> <p>1- a single membrane system with the application of a constant electric field.</p> <p>2- a double membrane system with the application of the charge imbalance protocol.</p> <p>The model of the glycine receptor was reduced to its transmembrane domain and simulated with atomic positional restraints.</p> <p>Related to the published article: "On the functional annotation of open-channel structures in the glycine receptor".</p>
Supplementary Information for Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS
<p>Supplementary information for<br> Páll, S., Zhmurov, A., Bauer, P., Abraham, M., Lundborg, M., Gray, A., Hess, B, & Lindahl, E.. (2020). Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS. The Journal of Chemical Physics, 2020</p> <p>Contains benchmark methodology description as well as all inputs used in the application performance benchmarks included the paper.</p>
MD simulation trajectory and related files for POPC bilayer in low hydration (Berger model delivered by Tieleman, Gromacs 4.5)
<p>Equilibrated POPC lipid bilayer simulation in low hydration (7 water per lipid molecule) ran with Gromacs 4.5, Berger force field delivered by Peter Tieleman (http://wcm.ucalgary.ca/tieleman/downloads) with fixed double bond dihedrals, 60ns, T=298K, 128 POPC molecules, 896 water molecules. This data is used in 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 the nmrlipids.blogspot.fi project and the original publications related to the force field.</p>
MD simulation trajectory and related files for POPC bilayer in low hydration (GAFFlipid, Gromacs 4.5)
<p>Equilibrated POPC lipid bilayer simulation ran with Gromacs 4.5, GAFFlipid force field (http://dx.doi.org/10.1039/C2SM26007G) in low hydration, 40ns, T=303K, 126 POPC molecules, 896 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>
MD simulation trajectory and related files for POPC bilayer (Lipid14, Gromacs 4.5)
<p>Equilibrated POPC lipid bilayer simulation ran with Gromacs 4.5, Lipid14 force field (http://dx.doi.org/10.1021/ct4010307), 50ns, T=303K, 72 POPC molecules, 2234 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.</p>
MD simulation trajectory and related files for DPPC bilayer (CHARMM36, Gromacs 4.5)
<p>Equilibrated DPPC lipid bilayer simulation ran with Gromacs 4.5, CHARMM36 force field (dx.doi.org/10.1021/jp101759q), 25ns, T=323K, 72 POPC molecules, 2189 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/10.1021/jp101759q).</p>
MD simulation trajectories of Glycerol for different POPC/Cholesterol concentrations (0,10,15,20,25,35,50%). CHARMM36, Gromacs 4.6.3. 2014.
<p>MD simulation trajectories files, for fully hydrated POPC + CHOLESTEROL bilayer. The CHARMM36 force field was used with Gromacs 4.6.3. Conditions: T=298K and different cholesterol concentrations described in the name of each file. 170 ns each trajectory, last 100 ns analyzed.</p> <p> </p>
Bug in CCFD stress profile calculation of GROMACS-LS?
<p>In Martini simulations (15 us, last 5 us analyzed) of an asymmetric GM1+POPC lipid bilayer (5+95 upper, 0+100 lower leaflet) strong stress fluctuations arising from the dihedral contributions of CCF decomposition are found. It is possible that these are due to a slight bug in the GROMACS-LS (http://mdstress.org) code, because:</p> <p>1) The fluctuations do not show converge, when more data is added, see the attached plot ‘effect_of_sampling_rate.pdf’.</p> <p>2) The fluctuations (but no other features of the stress profiles) visibly depend on the chosen frame of reference, see ‘effect_of_centering_schemes.pdf’.</p> <p>3) The stress profiles calculated along the coordinates that lay in the membrane plane (x and y), are not constant in CCFD, see ‘profiles_along_x_and_y.pdf’.</p> <p> </p> <p>To assist debugging the code, this repository contains:</p> <p><strong>5to95_0to100_0.trr</strong> --- 1st 33.3% of a 5 us trajectory with snapshots every 100 ps<br> <strong>5to95_0to100_0.trr</strong> --- 2nd 33.3% of a 5 us trajectory with snapshots every 100 ps<br> <strong>5to95_0to100_0.trr</strong> --- 3rd 33.3% of a 5 us trajectory with snapshots every 100 ps</p> <p><strong>5to95_0to100.tpr</strong> --- tpr used for production (Gromacs 5.1.1)<br> <strong>5to95_0to100_rerun.tpr</strong> --- tpr used for stress analysis and centering</p> <p><strong>5to95_0to100.gro</strong> --- gro file after 15 us (10 us relaxation, 5 us production)</p> <p><strong>index.ndx</strong> --- index file used in production<br> <strong>5to95_0to100.ndx</strong> --- index file used in analysis</p> <p><strong>system.top</strong> --- topology file<br> <strong>martini_v2.0_ions.itp</strong> --- martini FF file (system.top expects this to be in folder toppar/)<br> <strong>martini_v2.0_lipids_all_201506.itp</strong> --- martini FF file (system.top expects this to be in folder toppar/)<br> <strong>martini_v2.2.itp</strong> --- martini FF file (system.top expects this to be in folder toppar/)</p> <p><strong>martini_straight_GM1_saveVels.mdp</strong> --- run input file used for production (Gromacs 5.1.1)<br> <strong>martini_straight_GM1_rerunForP.mdp</strong> --- run input file used for analysis and centering</p> <p><strong>effect_of_sampling_rate.pdf</strong> --- plot of results showing that fluctuations in CCFD do not appear to converge when data is added<br> <strong>profiles_along_x_and_y.pdf</strong> --- plot of results showing that in CCFD pressure profiles along the membrane directions are not constant<br> <strong>effect_of_centering_schemes.pdf</strong> --- plot of results showing that choice of center of mass (here three possibilities are shown: CoM of POPC GL1 beads, CoM of POPCs, and CoM of all lipids) visibly affects CCFD fluctuations, but not other features of the stress profile<br> <strong>effect_of_centering_schemes_2.pdf</strong> --- plot of results (similar to 'effect_of_centering_schemes.pdf', but the center of the bilayer is at 3.7 nm instead at 0.0 / 7.4 nm)<br> <strong>individual_components.pdf</strong> --- plot of results showing that the fluctuations in CCFD arise from dihedrals<br> <strong>CCFD_gridsize.pdf</strong> --- plot of results showing that decreasing gridsize has no clear effect on the CCFD fluctuations</p>
MD simulation trajectory of a lipid bilayer: 70/30 mol% POPC/Cholesterol . SLIPIDS, Gromacs 4.6.3. 2016.
<p>MD simulation trajectory files, for fully hydrated POPC + CHOLESTEROL bilayer (70/30 mol%) [358 POPC, 154 CHOL, 21183 WAT]. The SLIPIDS force field was used with Gromacs 4.6.3. Conditions: T=298K. 170 ns each trajectory, last 100 ns analyzed.</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>
MD simulation trajectory of a lipid bilayer: 50/50 mol% POPC/Cholesterol . SLIPIDS, Gromacs 4.6.3. 2016.
<p>MD simulation trajectory files, for fully hydrated POPC + CHOLESTEROL bilayer (50/50 mol%) [256 POPC, 256 CHOL, 20334 WAT]. The SLIPIDS force field was used with Gromacs 4.6.3. Conditions: T=298K. 170 ns each trajectory, last 100 ns analyzed.</p>
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