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393 results for “Molecular dynamics simulations”
Structural Dynamics of an Excited Donor-Acceptor Complex from Ultrafast Polarized Infrared Spectroscopy, Molecular Dynamics Simulations, and Quantum Chemical Calculations
<p>The files contains all the data that are shown in the figures of the article:</p> <p>Rumble, C.; Vauthey, E. Structural Dynamics of an Excited Donor-Acceptor Complex from Ultrafast Polarized Infrared Spectroscopy, Molecular Dynamics Simulations, and Quantum Chemical Calculations. Phys. Chem. Chem. Phys. 21 (2019). 10.1039/C9CP00795D</p>
Molecular Dynamics (MD) Simulation Data for Dynamics Underlie the Drug Recognition Mechanism by the Efflux Transporter EmrE
<p>MD simulations on the proton bound (PDB 8UWU), deprotonated on E14A (PDB 8UWU), TPP Bound (PDB 8UWU) on our NMR derived structures.</p> <p> </p> <p>MD simulations on the proton bound (7MH6) and deprotonated on E14A (7MH6) on X-ray structures. </p> <p> </p> <p>Total raw simulation data would be too large for uploading to repositories. To reduce size of file, starting structure and tpr files are uploaded. Final structure at 2.5 μs are also uploaded. </p>
BaTiO3 coarse-grained molecular dynamics simulations
<p>This repository contains the simulation results for BaTiO3 using coarse-grained molecular dynamics package <a title="Feram" href="https://loto.sourceforge.net/feram/" target="_blank" rel="noopener">Feram</a>.</p> <p>The files (1: data.avg, 2: *.csv) use the space-separated format or comma-separated format.</p> <p>(1) data.avg columns:<br>T: temperature in Kelvin<br>Ex Ey Ez: external_E_field along x,y,z in V/Angstrom.<br>exx eyy ezz eyz ezx exy: strain tensor<br>ux uy uz: dipole displacements in Angstrom<br>uxux uyuy uzuz uyuz uzux uxuy: cross-terms of dipole displacements in Angstrom^2<br>dk: dipo_kinetic in eV/u.c.<br>lr: long_range in eV/u.c.<br>dEf: dipole_E_field in V/Angstrom<br>unhar: unharmonic in eV/u.c.<br>s_ho: homo_strain in eV/u.c.<br>c_ho: homo_coupling in eV/u.c.<br>s_inho: inho_strain in eV/u.c.<br>c_inho: inho_coupling in eV/u.c.<br>etot: total energy in eV/u.c.<br>HNP: H_Nose_Poincare in eV/u.c.<br>e2: e2<br>dkt: dipo_kinetic_true in eV/u.c.<br>ak: acuou_kinetic in eV/u.c.<br>sr: short_range in eV/u.c.<br>mod: inho_modulation in eV/u.c.<br>px py pz: px py pz<br>ppx ppy ppz ppyz ppzx ppxy: ppx ppy ppz ppyz ppzx ppxy<br>mx my mz: <ux>, <uy>, <uz> in Angstrom<br>amx amy amz: <|ux|>, <|uy|>, <|uz|> in Angstrom</p> <p>(2) *.csv contains header in each file.</p> <p>(3) avg2csv.ipynb contains script to convert files.</p>
All-atom molecular dynamics simulations of iRFP713/C15S/V254C/N136R
<p>The trajectories of all-atom MD simulations of monomeric and dimeric iRFP713/C15S/V254C/N136R with PCB (phycocyanobilin) and BV (biliverdin).</p> <p> </p> <p>Simulations have been performed using the CHARMM36 force field, running with the GROMACS 2022 package.</p>
Molecular Dynamics Simulation and Docking Studies Reveals Inhibition of NF-kB signaling as a Promising Therapeutic Drug Target for reduction in Cytokines Storms
<p><span>The complexes of the top identified molecules with NF-kB-kB site, as well as all the designed molecules used in the screening process. </span></p>
Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study.
<p>This repository contains the representative structures of the 20 clusters obtained, which constitute the “MD-adapted structure ensemble”: i.e., sets of atomic coordinates that capture the flexibility and the pre-miR20b (<a href="https://zenodo.org/api/files/ee12021f-4398-465a-9ff6-ddb7be32765f/ensemble_MD_2n7x.pdb?versionId=310a80f6-aa64-445d-8641-45faf9f1ac03">ensemble_MD_2n7x.pdb</a>) and Rbfox/pre-miR20b (<a href="https://zenodo.org/api/files/ee12021f-4398-465a-9ff6-ddb7be32765f/ensemble_MD_2n82.pdb?versionId=82d7afcb-8a92-4daa-8150-789dbd7b2474">ensemble_MD_2n82.pdb</a>) conformers suggested by MD simulations while still retaining the highest possible level of agreement with the primary NMR data.</p>
Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study.-PART 8
<p>Simulations of the miR20b RNA with the Case vdW modification to amber force field and OPC water molecules.</p>
Interaction of N-3-oxododecanoyl homoserine lactone with transcriptional regulator LasR of Pseudomonas aeruginosa: Insights from molecular docking and dynamics simulations
<p>Dataset and supplementary files of the research: Interaction of N-3-oxododecanoyl homoserine lactone with transcriptional regulator LasR of Pseudomonas aeruginosa: Insights from molecular docking and dynamics simulations (https://doi.org/10.1101/121681)</p> <p>- Supporting Information</p> <p>- Input: Parameters and initial structures</p> <p>- Output: Trajectories, Docking poses</p> <p>Gromacs (multi-core with CUDA) was used for the simulations.</p> <p>Autodock Vina, FlexAid and rDock were used for molecular docking.</p>
Revisiting the allosteric regulation of sodium cation on the binding of adenosine at the human A2A adenosine receptors: insights from Supervised Molecular Dynamics (SuMD) simulations.
<p><strong>SuMD trajectories Videos </strong></p> <p> </p> <p><strong>Video 1: </strong>Sodium binding pathway on the antagonist-bound state of A<sub>2A</sub>R.</p> <p>The video is composed of four synchronized and animated panels that depict the molecular trajectory obtained by the SuMD simulation considering different aspects of the simulation. The time evolution is reported in a nanosecond. In the first panel (upper-left), the molecular representation of the macromolecular system is shown. The A<sub>2A</sub>R antagonist-bound state backbone is represented by the ribbon style (cyan colour) and the residues within 4 Å of sodium ion during the entire simulation are dynamically shown. Na<sup>+</sup> is rendered showing its VdW volume in yellow. In the second panel (upper-right), the dynamic distance of sodium center of mass (CM) from the A<sub>2A</sub>R allosteric binding site during the trajectory is reported. In the third panel (lower-left), the MMGBSA energy profile is reported. The animated red circle highlights the value of the corresponding frame. The trend is depicted by a continuous black line obtained by smoothing the raw data (grey circles) using a Bezier curve procedure. In the fourth panel (lower-right) cumulative electrostatic interactions are reported for the 15 A<sub>2A</sub>R residues most contacted by sodium during the whole simulation.</p> <p> </p> <p><strong>Video 2: </strong>Adenosine different binding pathways collection on the two relevant states of A<sub>2A</sub>R</p> <p>The video is composed of two panels, which summarizes the recognition process of the adenosine agonist, sampled by means of the supervised molecular dynamics methodology, in the two pharmacologically relevant states of the receptor. In particular, on the right side are shown simultaneously all ten replicas collected starting from the agonist-bound conformation of the A<sub>2A</sub>R (pink ribbon). The meta-binding site located at the level of the ECL2 and the orthosteric binding site were highlighted. On the left side are represented simultaneously all ten replicas collected starting from the antagonist-bound conformation of the A<sub>2A</sub>R (cyan ribbon). The meta-binding site located at the level of the ECL2 and the extracellular receptor vestibule were highlighted.</p> <p> </p> <p><strong>Video 3: </strong>Adenosine binding pathway on the agonist-bound state of A<sub>2A</sub>R.</p> <p>The video is composed of four synchronized and animated panels that depict the molecular trajectory obtained by the SuMD simulation considering different aspects of the simulation. The time evolution is reported in a nanosecond. In the first panel (upper-left), the molecular representation of the macromolecular system is shown. The A<sub>2A</sub>R agonist-bound state backbone is represented by the ribbon style (pink colour) and the residues within 4 Å of sodium ion during the entire simulation are dynamically shown. Adenosine molecule is rendered by orange carbon atoms and by a transparent surface. In the second panel (upper-right), the dynamic distance of agonist center of mass (CM) from the A<sub>2A</sub>R allosteric binding site during the trajectory is reported. In the third panel (lower-left), the MMGBSA energy profile is reported. The animated red circle highlights the value of the corresponding frame. The trend is depicted by a continuous black line obtained by smoothing the raw data (grey circles) using a Bezier curve procedure. In the fourth panel (lower-right) cumulative electrostatic interactions are reported for the 15 A<sub>2A</sub>R residues most contacted by adenosine during the whole simulation.</p>
Molecular dynamics simulations of the interaction of mutant human CYP2J2 (R111A) with arachidonic acid (POSES 1-3)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_mutR111A_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the R111A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p> <p>005.md : Production stage</p> <p>006.analysis : Basic energy graphs</p> <p>007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)</p>
Molecular dynamics simulations of the interaction of the double mutant human CYP2J2 (R117A and R111A) with arachidonic acid (POSES 4-6)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_mutR111A_R117A_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the double R111A + R117A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p>
Speciation data for "Pressure-induced coordination changes in a pyrolitic silicate melt from ab initio molecular dynamics simulations"
<p>With <em>ab initio</em> molecular dynamics simulations on pyrolite melt, we examine the detailed changes in elemental coordination as a function of pressure and temperature. We consider the average coordination as well as the proportion and distribution of coordination environments at pressures and temperatures encompassing the conditions at which molten silicates may exist in present-day Earth and those of the Early Earth's magma ocean. At ambient pressure and 2000 K, we find that the average coordination of cations with respect to oxygen is 4.0 for Si-O, 4.0 for Al-O, 3.7 for Fe-O, 4.6 for Mg-O, 5.9 for Na-O and 6.2 for Ca-O. Although the coordination for iron with respect to oxygen is underestimated, the coordination number for all other cations are consistent with experiments. At the base of the upper mantle (~15 GPa and 2000 K), the average coordination for Si-O remains at 4.0, but increases to 4.1 for Al-O, 4.2 for Fe-O, 4.9 for Mg-O, 8.0 for Na-O and 6.8 for Ca-O. The coordination environment for Na-O remains approximately constant up to core-mantle boundary conditions (135 GPa and 4000 K), but increases to about 6 for Si-O, 6.5 for Al-O, 6.5 for Fe-O, 8 for Mg-O, 9.5 for Ca-O. Our results have implications for melt properties, such as viscosity, transport coefficients, thermal conductivities and electrical conductivities, and will help interpret experimental results on silicate glasses.</p> <p>Detailed speciation statistics for pyrolite melt were determined using <em>a</em><em>b initio</em> molecular dynamics simulations with the Vienna Ab Initio Simulation Package (VASP) (Kresse and Furthmuller, 1996). Simulations were performed with a time step of 0.5-2 femtoseconds for 10-50 picoseconds, depending on the temperature and density. The composition of the Bulk Silicate Earth was modeled with a pyrolite melt with the stoichiometry NaCa<sub>2</sub>Fe<sub>4</sub>Mg<sub>30</sub>Al<sub>3</sub>Si<sub>24</sub>O<sub>89</sub>. Bond distances were determined from the pair distribution functions, which describe the probability of finding an atom type at a given distance from the reference atom. We used the first peak in the pair distribution function to approximate the average bond length; the distance at which the first minimum occurs marks the radius of the first coordination sphere of atoms that are directly bonded to the reference atom. We used this value to define the bond criterion between two atom types. Additional computational details can be found in the manuscript.</p>
Molecular dynamics simulation input files: Dynamics of amphiphilic poly($\varepsilon$-caprolactone) micelles with doxorubicin and transition temperature predictions using all-atom molecular dynamics simulation
<p>The files uploaded contain the input files for simulations:<br><br>1) P10_Solv: Input files for drug-free micelles.<br>2) Micelle_Solv: Input files for drug-loaded micelles.</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>
Molecular dynamics simulations of RNA Pol I closed complex in WT and with modifications to DNA base pairs -27 and -28
<p><span>The starting structure for the modelling was cryo-EM based structure of <em>S. cerevisiae</em> pre-initiation complex, showing Pol I, RRN3 and CF bound on a rDNA promoter at 2.90 Å resolution. This structure (‘RNA Polymerase I closed conformation 2’; accession code: 6RQL) was downloaded from the PDB database and prepared using the Protein Preparation Workflow of Maestro with default settings. This included filling in missing sidechains, optimizing hydrogen bonds and protonation using PROPKA at pH 7.4, deleting water molecules >5Å from the heteroatoms and a short energy minimization using OPLS4 force field</span><span>. The initial structures for the complexes with DNA mutations were constructed from this pre-processed structure by manually mutating the base pairs at position -28 or -27 of the rDNA promoter from C</span><span>·</span><span>G to A</span><span>·</span><span>T (</span><span>tDNA·ntDNA)</span><span> and from A</span><span>·</span><span>T to C</span><span>·</span><span>G, respectively. </span><span></span><span>MD simulations (3*80 ns/system) were conducted with Desmond using default parameters from Schrödinger Suite version 2024-1 on the CSC (IT Center for Science, Finland) supercomputer Puhti. </span></p>
Trajectories of Microsecond Molecular Dynamics Simulations of the Orexin Receptor 2 System with Lemborexant
<p>This data set contains psf files and trajectories (.dcd files) of the performed simulations for the orexin receptor 2 system:</p> <p>1) the orexin type 2 receptor (OX2R) in complex with lemborexant, three replicas</p>
Trajectories of Microsecond Molecular Dynamics Simulations of the Orexin Receptor 2 System with Compound 1
<p>This data set contains psf files and trajectories (.dcd files) of the performed simulations for the orexin receptor 2 system:</p> <p>1) the orexin type 2 receptor (OX2R) in complex with compound 1, three replicas, 2 microseconds.</p>
Molecular Dynamics Simulation of MC-congeners in complex with PPP1 - Replicate 3
<p>This data sets contains Molecular Dynamics (MD) Simulation files and analysis. Microcystin (MC) congeners were simulated in solvent (water) and in complex with protein phosphatase 1 (PPP1). MD Simulation was repeated for three times. This data is replicate 3 and related data sets are available.</p> <p>Please cite the original publication when using all or part of the data:</p> <p>S. Jaeger-Honz, J. Nitschke, S. Altaner, K. Klein, D. R. Dietrich, F. Schreiber:<a href="https://doi.org/10.1016/j.cbi.2021.109766"> Investigation of microcystin conformation and binding towards PPP1 by molecular dynamics simulation</a>. <em>Chemico-Biological Interactions</em>, 2021</p>
Molecular Dynamics Simulation of MC-congeners in complex with PPP1 - Replicate 2
<p>This data sets contains Molecular Dynamics (MD) Simulation files and analysis. Microcystin (MC) congeners were simulated in solvent (water) and in complex with protein phosphatase 1 (PPP1). MD Simulation was repeated for three times. This data is replicate 2 and related data sets are available.</p> <p>Please cite the original publication when using all or part of the data:</p> <p>S. Jaeger-Honz, J. Nitschke, S. Altaner, K. Klein, D. R. Dietrich, F. Schreiber:<a href="https://doi.org/10.1016/j.cbi.2021.109766"> Investigation of microcystin conformation and binding towards PPP1 by molecular dynamics simulation</a>. <em>Chemico-Biological Interactions</em>, 2021</p>
Molecular Dynamics Simulation of MC-congeners in complex with PPP1 - Replicate 1
<p>This data sets contains Molecular Dynamics (MD) Simulation files and analysis. Microcystin (MC) congeners were simulated in solvent (water) and in complex with protein phosphatase 1 (PPP1). MD Simulation was repeated for three times. This data is replicate 1 and related data sets are available.</p> <p>Please cite the original publication when using all or part of the data:</p> <p>S. Jaeger-Honz, J. Nitschke, S. Altaner, K. Klein, D. R. Dietrich, F. Schreiber:<a href="https://doi.org/10.1016/j.cbi.2021.109766"> Investigation of microcystin conformation and binding towards PPP1 by molecular dynamics simulation</a>. <em>Chemico-Biological Interactions</em>, 2021</p>
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