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220 results for “force fields”
DFT torsiondrive data for: MACE-OFF23: Transferable Machine Learning Force Fields for Organic Molecules
<p>MACE-OFF23: Transferable Machine Learning Force Fields for Organic Molecules</p> <div><a href="https://arxiv.org/search/physics?searchtype=author&query=Kov%C3%A1cs,+D+P">Dávid Péter Kovács</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Moore,+J+H">J. Harry Moore</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Browning,+N+J">Nicholas J. Browning</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Batatia,+I">Ilyes Batatia</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Horton,+J+T">Joshua T. Horton</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Kapil,+V">Venkat Kapil</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Witt,+W+C">William C. Witt</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Magd%C4%83u,+I">Ioan-Bogdan Magdău</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Cole,+D+J">Daniel J. Cole</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Cs%C3%A1nyi,+G">Gábor Csányi </a><a href="https://doi.org/10.48550/arXiv.2312.15211">https://doi.org/10.48550/arXiv.2312.15211</a></div> <p> </p> <p>Supporting data including raw outputs from SPICE consistent torsion drives on the TorsionNet500 and OpenFF Biaryl datasets and HDF5 versions formated to be consistent with the rest of the SPICE dataset. See the <a href="../records/10975225">SPICE release</a> for more details. </p>
NaCl force field study: All the radial distribution functions and final configurations (PDB)
<p>The package contains all the radial distribution functions and final configurations (PDB) from our NaCl force field study</p> <ul> <li><a href="http://dx.doi.org/10.1002/jcc.10417">Systematic comparison of force fields for microscopic simulations of NaCl in aqueous solutions: Diffusion, free energy of hydration and structural properties</a>, M. Patra and M. Karttunen, physics/0211059. J. Comp. Chem. 25, 678-689 (2004) .</li> </ul> <p> </p> <p> </p>
Developing and Benchmarking Sulfate and Sulfamate Force Field Parameters via Ab Initio Molecular Dynamics Simulations to Accurately Model Glycosaminoglycan Electrostatic Interactions
<p>To cite and for more details: Riopedre-Fernandez et al. <em>J. Chem. Inf. Model.</em> <strong>2024</strong>, 64 (18), 7122–7134. DOI: <a href="https://doi.org/10.1021/acs.jcim.4c00981">https://doi.org/10.1021/acs.jcim.4c00981</a></p> <p>The dataset includes molecular dynamics simulations of sulfated saccharides and their sulfated analogs in the presence of calcium cations in aqueous solution. Several force field parameter sets were compared (CHARMM36, GLYCAM06, AMOEBA, Drude) and new have been developed (prosECCo75 and GLYCAM-ECC75).</p> <p>The uploaded files contain the following simulation input files or/and simulation trajectories:</p> <p>1) Sulfated_Molecules_Umbrella_Sampling_AIMD: Umbrella sampling ab initio molecular dynamics simulations of calcium-methylsufate and calcium N-methylsulfamate ion pairs in water.</p> <p>2) Sulfated_Molecules_Umbrella_Sampling_FFMD: Umbrella sampling force field molecular dynamics simulations of calcium-methylsufate and calcium N-methylsulfamate ion pairs in water.</p> <p>3) Sulfated_Molecules_AWH_FFMD: Accelerated weight histogram force field molecular dynamics simulations of calcium interacting with both methylsufate and N-methylsulfamate in water.</p> <p>4) Disaccharides_FFMD: Unbiased force field molecular dynamics simulations of calcium-sulfated disaccharide aqueous solutions.</p> <p>UPD. Version 2.0 has updated one of the disaccharide-containing simulations (GLYCAM06, N-sulfation) due to incorrect calcium LJ parameters in the original upload.</p>
Free Energy-based Refinement of DNA Force Field via Modification of Multiple Non-bonding Energy Terms
<p>Relevant files of the benchmark DNA simulations.</p> <p>*.xtc --> truncated OPESE trajectory file.</p> <p>*.tar --> compressed initial structures.</p> <p>*.mdp --> GROMACS molecular dynamics parameter file.</p> <p>*.dat --> PLUMED input file for OPESE simulation.</p> <p> </p>
bd oxidase force field parameters
<p>Amber force field parameters for E. coli cytochrome bd oxidase (PDB: 6RKO)</p>
Dataset for Journal of Applied Physics 130, 124502 (2021) - Force microscopy cantilevers locally heated in a fluid: temperature fields and effects on the dynamics
<p><strong>"Fig7.fig"</strong>: Matlab figures including all the measured and treated data used to plot figure 7 of the article.</p> <p><strong>"Fig7_data.mat "</strong>: Matlab files containing the data to plot figure 7 of the article.</p> <p><strong>"Fig7_plot.m "</strong>: Matlab scripts to plot the data of the Matlab files "Fig7_data.mat"</p> <p><strong>"Fig10.fig"</strong>: Matlab figures including all the measured and treated data used to plot figure 10 of the article.</p> <p><strong>"Fig13.fig"</strong>: Matlab figures including all the measured and treated data used to plot figure 13 (in the appendix) of the article.</p> <p> </p>
Research data supporting: "A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields"
<p>This repository contains the data used in the paper of Capelli <em>et al. </em>"A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields", published on Journal of Physical Chemistry B (DOI: 0.1021/acs.jpcb.1c02503).<br> <br> The archive traj_processed.tar.gz contains the trajectories converted in xyz format with the dimensions of the box.</p> <p>The archive trajectories_xtc.tar.gz contains the raw trajectories (of the membranes without solvent) in gromacs xtc format with a .tpr binary file. <br> </p>
DPPC lipid bilayer simulation with CHARMM36-LJPME force field using OpenMM
<p>DPPC lipid bilayer simulation (300 ns) with CHARMM36-LJPME force field using OpenMM at 323K.</p> <p>Used in <a href="http://doi.org/10.1021/acs.jctc.1c00951">https://doi.org/10.1021/acs.jctc.1c00951</a></p> <p>The force field parameters were downloaded from <a href="https://terpconnect.umd.edu/%7Ejbklauda/ff.html">https://terpconnect.umd.edu/%7Ejbklauda/ff.html</a>.</p> <p><a href="https://zenodo.org/api/files/1e89f677-91a8-472d-aebb-144fddd58d23/trajCORRECT1-2.dcd?versionId=5317fd88-6b98-4905-b171-53c1cd199cfe">trajCORRECT1-2.dcd </a>has incorrect timestamps. traj1-2.xtc has correct timestamps.<br> </p>
Collaborative Assessment of Molecular Geometries and Energies from the Open Force Field
<p>OpenFF Industry Public Dataset optimized at the (1) B3LYP-D3BJ / DZVP; (2) OpenFF-2.0.0; (3) Gaff-2.11-AM1BCC; (3) OPLS4 + default parameters; (4) OPLS4 + custom parameters.</p> <p>For (1) the corresponding tar.gz archive contains (a) sdf files of the final, optimized geometries and (b) json files with molecular properties of the final step of the optimization.</p> <p>For (2-4) the corresponding tar.gz archive contains sdf files of the final, optimized geometries.</p> <p>Note: The optimization carried out with both OPLS4 including default and custom parameters (4) was performed using the ffld_server to include virtual sites.</p>
Pure POPE membrane simulations with the CHARMM-Drude force field at 310K (OpenMM)
<p>MD simulation data of a pure POPE membrane with the CHARMM-Drude force field generated with the OpenMM simulation engine at 310K.</p> <p>Parameters from CHARMM-GUI.</p>
MD Simulation data for a pure DOPC bilayer without salt with AMOEBA force field + OpenMM
<p>MD simulation data for the DOPC bilayer 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 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> <p> </p>
MD Simulation data for a pure POPE bilayer with AMOEBA force field + OpenMM
<p>MD simulation data for the POPE bilayer 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 POPE lipids and 2880 water molecules. The trajectory is 305,94 ns long (30594 frames with 10 ps saving frequency).</p> <p><strong>It has been discovered that (https://github.com/NMRLipids/Databank/issues/2#issuecomment-1357871243) the openmm_combined.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>
RIG-I and RNA complex MD simulations in ff19SB+OL3, ff14SB+OL3, OPLS4 and AMOEBA force fields
<p>MD simulation trajectories of RIG-I variant in complex with RNA. 10*100ns in AMOEBA (a single file from OpenMM), 4*500ns in Amber(ff19sb+OL3, ff14sb+Ol3, polarizable water in amberpol), 4*500ns in Desmond (opls4). </p>
Cas12j-RNA simulations in ff19SB+OL3, ff14SB+OL3, OPLS4 and AMOEBA force fields
<p>MD simulations of Cas12j-RNA complex in different force fields. AMOEBA 10*100ns (in a single file), Amber simulations (ff19sb+ff14sb+amberpol) 4*500 ns and Desmond simulations (opls4) 4*500ns. </p>
Ago2-RNA complex simulations in AMOEBA force field
<p>10*100ns simulations of Ago2-RNA complex in the AMOEBA force field. The simulations were conducted using OpenMM. </p>
Supporting Data for "Does a Machine-Learned Potential Perform Better Than an Optimally Tuned Traditional Force Field? A Case Study on Fluorohydrins"
<p>Supporting Data for "Does a Machine-Learned Potential Perform Better Than an Optimally Tuned Traditional Force Field? A Case Study on Fluorohydrins"</p>
OpenMM simulations of DLPC 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<br> Each file has 50 ns of data, with coordinate sets spaced at 10 ps between frames.</p>
OpenMM simulations of POPE using the CHARMM Drude2023 force field
<p><br> 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>
OpenMM simulations of DMPC 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>DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file Each file has 50 ns of data, with coordinate sets spaced at 10 ps between frames.</p>
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>
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