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220 results for “force fields”
MD simulation of HpTonB(30-285) in 150mM NaCl with Amber ff03ws force field
<p>MD simulation of periplasmic part of TonB protein from <em>Helicobacter Pylori</em> HpTonB(30-285) with Amber ff03ws force field with 150 mM NaCl. Trajectory contains the last 1000ns of the simulation.</p> <p>micro_nojump_nowater.xtc (10 ps saving frequency), nowater.tpr, and confENDprot.gro contain only protein.</p> <p>1microsecondSKIP.xtc (100 ps saving frequency), md.tpr and confEND.gro contain also solvent.</p> <p>Force field parameters for proteins and counterions are dowloaded from https://github.com/bestlab/force_fields, for NaCl from https://bitbucket.org/hseara/ions</p>
MD simulation of HpTonB(30-285) in 40mM NaCl with Amber ff03ws force field
<p>MD simulation of periplasmic part of TonB protein from <em>Helicobacter Pylori</em> HpTonB(30-285) with Amber ff03ws force field with 40 mM NaCl. Trajectory contains the last 1000ns of the simulation.</p> <p>nojump_nowater.xtc (10 ps saving frequency), md_noSOL.tpr, and confENDprot.gro contain only protein.</p> <p>micro_40mMNaClskip.xtc (100 ps saving frequency), md.tpr and confEND.gro contain also solvent.</p> <p>Force field parameters for proteins and counterions are dowloaded from https://github.com/bestlab/force_fields, for NaCl from https://bitbucket.org/hseara/ions</p>
Amyloid-beta 16-22 peptide monomer simulation (without salt) with the CHARMM-Drude force field and OpenMM (Run 3)
<p>Amyloid-beta 16-22 peptide (monomer) simulations with the CHARMM-Drude force field and OpenMM. Initial structures are obtained from CHARMM-GUI. This is the third independent simulation runs out of three. The system does not contain any ions.</p> <p>Total trajectory length is 1 microseconds. Frame saving frequency is 10 ps.</p> <p>All the simulation parameters and force field files are uploaded into this repository. Simulations are done with OpenMM v. 7.5.1.</p> <p> </p>
Amyloid-beta 16-22 peptide monomer simulation (150 mM NaCl) with the CHARMM36m force field and Gromacs (Run 2)
<p>MD simulations of the Amyloid-beta 16-22 monomer at 150 mM NaCl concentration with CHARMM36m force field and Gromacs. This repository contains the first out of three independent runs. </p> <p>Files belong to the publication "<a href="https://doi.org/10.1021/acs.jcim.0c01063">https://doi.org/10.1021/acs.jcim.0c01063</a>"</p> <p>All the simulation parameters and force field files are uploaded into this repository. Simulations are done with Gromacs 2018.3</p> <p>Total simulation time is 500 ns. Frames are saved with 100 ps frequency. </p>
Amyloid-beta 16-22 peptide monomer simulation (150 mM NaCl) with the CHARMM36m force field and Gromacs (Run 1)
<p>MD simulations of the Amyloid-beta 16-22 monomer at 150 mM NaCl concentration with CHARMM36m force field and Gromacs. This repository contains the first out of three independent runs. </p> <p>Files belong to the publication "<a href="https://doi.org/10.1021/acs.jcim.0c01063">https://doi.org/10.1021/acs.jcim.0c01063</a>"</p> <p>All the simulation parameters and force field files are uploaded into this repository. Simulations are done with Gromacs 2018.3</p> <p>Total simulation time is 500 ns. Frames are saved with 100 ps frequency. </p>
MD simulation of POPC bilayer with OPLS3e force field, 200 mM CaCl2 part 2
<p>MD simulation of POPC bilayer with OPLS3e force field, 200 mM CaCl<sub>2</sub> part 2 (500-1000ns)</p> <p>Dataset contains trajectories (_trj) for the last 500ns of the 1000ns trajectory, topology (-out.cms), and other files</p> <p>For the ease of the upload, trajectory files (_trj) are divided to 100ns pieces and tarred (named desmond_md_cacl200_x-xns.tar.gz)</p> <p>System: POPC bilayer in water</p> <p>Number of lipids: 200 (100/leaflet)</p> <p>Number of waters: 8880</p> <p>Salt: CaCl<sub>2</sub></p> <p>Concentration: 200 mM</p> <p>Number of cations: 32</p> <p>Simulation time: 1000 ns (in this dataset 500-1000ns)</p> <p>Simulation engine: Desmond 2019-4</p> <p>Temperature: 300 K</p> <p>Related dataset: MD simulation of POPC bilayer with OPLS3e force field, 200 mM CaCl<sub>2</sub> part 1</p>
MD simulation of POPC bilayer with OPLS3e force field, 50 mM CaCl2 part 2
<p>MD simulation of POPC bilayer with OPLS3e force field, 50 mM CaCl<sub>2</sub> part 2 (500-1000ns)</p> <p>Dataset contains trajectories (_trj) for the last 500ns of the 1000ns trajectory, topology (-out.cms), and other files.</p> <p>For the ease of the upload, trajectory files (_trj) are divided to 100ns pieces and tarred (named desmond_md_cacl50_x-xns.tar.gz)</p> <p>System: POPC bilayer in water</p> <p>Number of lipids: 200 (100/leaflet)</p> <p>Number of waters: 8880</p> <p>Salt: CaCl<sub>2</sub></p> <p>Concentration: 50 mM</p> <p>Number of cations: 8</p> <p>Simulation time: 1000 ns (in this dataset 500-1000ns)</p> <p>Simulation engine: Desmond 2019-4</p> <p>Temperature: 300 K</p> <p>Related dataset: MD simulation of POPC bilayer with OPLS3e force field, 50 mM CaCl<sub>2</sub> part 1</p>
MD simulation of POPC bilayer with OPLS3e force field, 1000 mM NaCl part 2
<p>MD simulation of POPC bilayer with OPLS3e force field, 1000 mM NaCl part 2 (500-1000ns)</p> <p>Dataset contains trajectories (_trj) for the last 500ns of the 1000ns trajectory, topology (-out.cms), and other files.</p> <p>For the ease of the upload, trajectory files (_trj) are divided to 100ns pieces and tarred (named desmond_md_nacl1000_x-xns.tar.gz)</p> <p>System: POPC bilayer in water</p> <p>Number of lipids: 200 (100/leaflet)</p> <p>Number of waters: 8880</p> <p>Salt: NaCl</p> <p>Concentration: 1000 mM</p> <p>Number of cations: 160</p> <p>Simulation time: 1000 ns (in this dataset 500-1000ns)</p> <p>Simulation engine: Desmond 2019-4</p> <p>Temperature: 300 K</p> <p>Related dataset: MD simulation of POPC bilayer with OPLS3e force field, 1000 mM NaCl part 1</p>
MD simulation of POPC bilayer with OPLS3e force field, 1000 mM CaCl2 part 1
<p>MD simulation of POPC bilayer with OPLS3e force field, 1000 mM CaCl<sub>2</sub> part 1</p> <p>Dataset contains trajectories (_trj) for the first 500ns of the 1000ns trajectory, topology (-out.cms) and input files (.cfg, .msj, .cms).</p> <p>For the ease of the upload, trajectory files (_trj) are divided to 100ns pieces and tarred (named desmond_md_cacl1000_x-xns.tar.gz).</p> <p>Dataset also contains Gromacs converted files (.xtc, .gro and .top). Converted trajectories is also for the first 500 ns of 1000 ns, and are as 100 ns pieces for analysis since simulation did not equilibrate during 1000 ns.</p> <p>System: POPC bilayer in water</p> <p>Number of lipids: 200 (100/leaflet)</p> <p>Number of waters: 8880</p> <p>Salt: CaCl<sub>2</sub></p> <p>Concentration: 1000 mM</p> <p>Number of cations: 160</p> <p>Simulation time: 1000 ns (in this dataset 0-500ns)</p> <p>Simulation engine: Desmond 2019-4</p> <p>Temperature: 300 K</p> <p>Related dataset: MD simulation of POPC bilayer with OPLS3e force field, 1000 mM CaCl<sub>2</sub> part 2</p>
MD simulation of POPC bilayer with OPLS4 force field. 5 w/l
<p>MD simulation of POPC bilayer with OPLS4 force field. 5w/l</p> <p>Dataset contains trajectories (_trj), topologies (-out.cms), input files and converted gromacs format files</p> <p>For the ease of the upload, trajectory file (_trj) is divided into 4 pieces and tarred (named <span>desmond_md_popc</span>_5wl_opls4_x-xns.tar.gz)</p> <p>System: POPC bilayer in water</p> <p>Number of lipids: 200 (100/leaflet)</p> <p>Number of waters: 1000</p> <p>Simulation time: 1000 ns</p> <p>Simulation engine: Desmond 2022-2</p> <p> </p> <p>Temperature: 300 K</p>
Pure POPE membrane simulations with the AMOEBA force field at 310K (OpenMM)
<p>MD simulation data of a pure POPE membrane with the AMOEBA force field generated with the OpenMM simulation engine at 310K.</p> <p>Parameters from https://doi.org/10.1080/00268976.2018.1436201</p>
MD Simulation data for a pure DOPC bilayer (1000 mM CaCl2) with AMOEBA force field + OpenMM
<p>MD simulation data for the DOPC bilayer + 1000 mM CaCl2 with the AMOEBA-based force field developed by Li (<a href="https://doi.org/10.1080/00268976.2018.1436201">https://doi.org/10.1080/00268976.2018.1436201</a>).</p> <p>The simulation contains 72 DOPC lipids, 36 CaCl2 ions, and 2880 water molecules. The trajectory is 218,41 ns long (21841 frames with 10 ps saving frequency).</p> <p><strong>It has been discovered that (https://github.com/NMRLipids/Databank/issues/2#issuecomment-1357871243) the previously uploaded trajectory did not have the correct timestamp: the timestep between two consecutive simulation frames was not correctly embedded into the trajectory information. Therefore, with the latest version we are uploading the "unwrapped_all_fixed_dt.xtc" which has the correct timestamp. The frame saving frequency in this trajectory is 10 ps. </strong></p> <p><strong>This new update should not invalidate any previous calculations that did not explicitly read the timestamp information from the trajectory.</strong></p> <p><strong>This simulation consists of 12 sub-trajectories, each of which starts from the last frame of the previous one. These trajectories (originally in dcd format) were concatenated and saved in xtc format with MDAnalysis.</strong></p> <p> </p>
MD Simulation data for a pure DOPC bilayer (450 mM NaCl) with AMOEBA force field + OpenMM
<p>MD simulation data for the DOPC bilayer + 450 mM NaCl with the AMOEBA-based force field developed by Li (<a href="https://doi.org/10.1080/00268976.2018.1436201">https://doi.org/10.1080/00268976.2018.1436201</a>).</p> <p>The simulation contains 72 DOPC lipids, 17 NaCl ions, and 2880 water molecules. The trajectory is 218,41 ns long (21841 frames with 10 ps saving frequency).</p> <p><strong>It has been discovered that (https://github.com/NMRLipids/Databank/issues/2#issuecomment-1357871243) the previously uploaded trajectory did not have the correct timestamp: the timestep between two consecutive simulation frames was not correctly embedded into the trajectory information. Therefore, with the latest version we are uploading the "unwrapped_all_fixed_dt.xtc" which has the correct timestamp. The frame saving frequency in this trajectory is 10 ps. </strong></p> <p><strong>This new update should not invalidate any previous calculations that did not explicitly read the timestamp information from the trajectory.</strong></p> <p><strong>This simulation consists of 12 sub-trajectories, each of which starts from the last frame of the previous one. These trajectories (originally in dcd format) were concatenated and saved in xtc format with MDAnalysis.</strong></p> <p> </p>
MD Simulation data for a pure DOPC bilayer (450 mM CaCl2) with AMOEBA force field + OpenMM
<p>MD simulation data for the DOPC bilayer + 450 mM CaCl2 with the AMOEBA-based force field developed by Li (<a href="https://doi.org/10.1080/00268976.2018.1436201">https://doi.org/10.1080/00268976.2018.1436201</a>).</p> <p>The simulation contains 72 DOPC lipids, 16 CaCl2 ions, and 2880 water molecules. The trajectory is 218,41 ns long (21841 frames with 10 ps saving frequency).</p> <p><strong>It has been discovered that (https://github.com/NMRLipids/Databank/issues/2#issuecomment-1357871243) the previously uploaded trajectory did not have the correct timestamp: the timestep between two consecutive simulation frames was not correctly embedded into the trajectory information. Therefore, with the latest version we are uploading the "unwrapped_all_fixed_dt.xtc" which has the correct timestamp. The frame saving frequency in this trajectory is 10 ps. </strong></p> <p><strong>This new update should not invalidate any previous calculations that did not explicitly read the timestamp information from the trajectory.</strong></p> <p><strong>This simulation consists of 12 sub-trajectories, each of which starts from the last frame of the previous one. These trajectories (originally in dcd format) were concatenated and saved in xtc format with MDAnalysis.</strong></p> <p> </p>
Pure POPC membrane simulations with the CHARMM-Drude force field (OpenMM 7.5.0)
<p>MD simulation data of a pure POPC membrane with the CHARMM-Drude force field.</p> <p>All the input parameters are available in the *inp file.</p> <p>Total simulation duration is 500 ns. First 100 ns is discarded as equilibration. This data set contains 400 ns data with 40000 frames (saving frequency is 10 ps).</p> <p>In total, 64 POPC lipids in each leaflet, 6400 SWM4-NPD water molecules.</p> <p><strong>It has been discovered that (https://github.com/NMRLipids/Databank/issues/2#issuecomment-1357871243) the wrapped_full.dcd trajectory did not have the correct timestamp: the timestep between two consecutive simulation frames was not correctly embedded into the trajectory information. Therefore, with the latest version we are uploading the "wrapped_full.xtc" which has the correct timestamp. The frame saving frequency in this trajectory is 10 ps. The correction to the timestamp was done via MDAnalysis.</strong></p> <p><strong>This new update should not invalidate any previous calculations that did not explicitly read the timestamp information from the trajectory.</strong></p> <p> </p>
MD Simulation data for a pure DOPC bilayer (1000 mM NaCl) with AMOEBA force field + OpenMM
<p>MD simulation data for the DOPC bilayer + 1000 mM NaCl with the AMOEBA-based force field developed by Li (<a href="https://doi.org/10.1080/00268976.2018.1436201">https://doi.org/10.1080/00268976.2018.1436201</a>).</p> <p>The simulation contains 72 DOPC lipids, 35 NaCl ions, and 2880 water molecules. The trajectory is 201,61 ns long (20161 frames with 10 ps saving frequency).</p> <p><strong>It has been discovered that (https://github.com/NMRLipids/Databank/issues/2#issuecomment-1357871243) the previously uploaded trajectory did not have the correct timestamp: the timestep between two consecutive simulation frames was not correctly embedded into the trajectory information. Therefore, with the latest version we are uploading the "unwrapped_all_fixed_dt.xtc" which has the correct timestamp. The frame saving frequency in this trajectory is 10 ps. </strong></p> <p><strong>This new update should not invalidate any previous calculations that did not explicitly read the timestamp information from the trajectory.</strong></p> <p><strong>This simulation consists of 12 sub-trajectories, each of which starts from the last frame of the previous one. These trajectories (originally in dcd format) were concatenated and saved in xtc format with MDAnalysis.</strong></p>
Data for paper 'Machine Learning Force Fields for Molecular Liquids: Ethylene Carbonate / Ethyl Methyl Carbonate Binary Solvent'
<p>This data is supplied in conjunction with the paper:</p> <p>Magdău, I. B., Arismendi-Arrieta, D. J., Smith, H. E., Grey, C. P., Hermansson, K., and Csányi, G. NPJ Computational Materials, accepted. (2023). "Machine Learning Force Field for Molecular Liquids: Ethylene Carbonate / Ethyl Methyl Carbonate Binary Solvent."</p> <p>The archive contains the final EC:EMC training data and test sets (Volume Scans, Intra/Inter splits), final GAP potential and the MD trajectories described in the paper.</p> <p>The data is accompanied by a Jupyter Notebook: HowTo.ipynb (also compiled as *.pdf and *.html) which explains in detail the structure of the data and how to interact with it. The Notebook also demonstrates how to create volume scans, intra/inter splits and analyze configurations and MD trajectories.</p>
Motor Adaptation by Error Augmentation Force Field in Healthy Peoples' Upper Extremity
ClinicalTrials.gov study NCT02780817. IPD Sharing: YES. Countries: 1. Publications: 0.
Pelvic Obliquity Rehabilitation in Stroke Patients Using Robotically Generated Force Fields
ClinicalTrials.gov study NCT01684267. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Support Video of Modification of Glycerol Force Field for Simulating Diffusion-limited Silver Crystallization
<p>More support video for the paper crystals-630387</p> <p>"Modification of Glycerol Force Field for Simulating Diffusion-limited Silver Crystallization"</p> <p>SV2: The glycerol simulation run in the modified OPLS force field;</p> <p>SV3: The comparation of erythritol simulation run in the modified OPLS force field and the classic OPLS force field;</p> <p>SV4:The comparation of xylitol simulation run in the modified OPLS force field and the classic OPLS force field;</p> <p>SV5:The comparation of inositol simulation run in the modified OPLS force field and the classic OPLS force field.</p>
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