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691 results for “Molecular Dynamics”
Dataset of "Molecular dynamics of evaporative cooling of water clusters"
<p>The cooling of water clusters through evaporation into a vacuum is studied using classical molecular dynamics with the SPC water model, and the results are compared with semimacroscopic theory. A model based on the Hertz–Knudsen equation underestimates the cooling rates. A modified approach, which accounts for the Kelvin equation, provides better results. While the rotational temperature of the clusters is in equilibrium with their internal temperature, the translational temperature of the clusters “as individual particles” remains unchanged.</p>
Dataset of "Molecular Dynamics Simulations Unveil the Aggregation Patterns and Salting out of Polyarginines at Zwitterionic POPC Bilayers in Solutions of Various Ionic Strengths"
<p>Molecular dynamics simulations are performed for a series of model cell-penetrating peptides (in particular nona-arginines) in aqueous solutions, in contact with model phosphocholine (POPC) membranes in conditions of different ionic strengths. The unusual aggregation properties of peptides at model lipid bilayers are analyzed and different sizes and lifetimes of aggregates are presented.<br>This dataset contains molecular dynamics simulation data with trajectories, input files, and topology files for all studied systems. They contain low peptide concentration in water, low NaCl concentration, high NaCl concentration, low CaCl2 concentration, and high CaCl2 concentration.<br>In addition to low peptide concentration, high peptide concentration in water, low NaCl concentration, high NaCl concentration, low CaCl2 concentration, and high CaCl2 concentration are also studied.</p>
Data for: Temperature-controlled Molecular Bonding Hysteresis: Interphase Dynamics of a Nanoparticle-modified Polymer Network
<p>The data is supplementary to the publication "Temperature-controlled Molecular Bonding Hysteresis: Interphase Dynamics of a Nanoparticle-modified Polymer Network", DOI: <a title="DOI URL" href="https://doi.org/10.1021/acs.jpclett.4c00406">10.1021/acs.jpclett.4c00406</a></p> <p>Key words: Thermal volume expansion, Interphase dynamics, Temperature-modulated optical refractometry, Nanoparticles, Optical Remanence, Hysteresis, Refractive index</p> <p>The data sets contain measured and processed data on the interphase dynamics of a nanoparticle modified epoxy resin collected via Temperature-modulated optical refractometry (TMOR).</p> <p>Material details:</p> <ul> <li>Cycloaliphatic epoxy resin + Anhydride curing agent + 1-methylimidazole</li> <li>Core-shell rubber nanoparticles, 100 nm, dispersed in a cycloaliphatic epoxy carrier resin</li> </ul> <p>Funding received from:</p> <ul> <li>German Research Foundation (DFG), project number: 521902629.</li> </ul>
Inactive to active transition of human Thymidine Kinase 1 revealed by Molecular Dynamics simulations
<p>The trajectories and input files for the manuscript <em>Inactive to active transition of human Thymidine</em></p> <p><em>Kinase 1 revealed by Molecular Dynamics simulations</em> (<a href="https://doi.org/10.1021/acs.jcim.1c01157">https://doi.org/10.1021/acs.jcim.1c01157</a>) </p> <p>ABSTRACT</p> <p>Despite its importance for the nucleoside (and nucleoside prodrug) metabolism, the structure<br> of the active conformation of human Thymidine Kinase 1 (hTK1) remains elusive. We perform<br> microsecond molecular dynamics simulations of the inactive enzyme form bound to a<br> bisubstrate inhibitor that was shown experimentally to activate another TK1-like kinase,<br> Thermotoga maritima TK (TmTK). Our results are in excellent agreement with the<br> experimental findings for the TmTK closed-to-open state transition. We show that the inhibitor<br> induces an increase of the enzyme radius of gyration due to the expansion on one of the dimer<br> interfaces; the structural changes observed, including the active site pocket volume increase,<br> decrease in monomer-monomer buried surface area and of the number of hydrogen bonds (as<br> compared to the inactive enzyme control simulation), show that the catalytically competent<br> (open) conformation of hTK1 can be assumed in the presence of an activating ligand.</p>
Atomistic trajectories from ab-initio molecular dynamics simulations of wetted TiO2 nanoparticle
<p>This repository contains atomistic trajectories from ab-initio molecular dynamics simulations of water and TiO2 nanoparticle described in the paper:</p> <p>E. G. Brandt, L. Agosta and A.P.Lyubartsev, " Reactive wetting properties of TiO2 nanoparticles predicted by ab initio molecular dynamics simulations", Nanoscale, 8, 13385-13398 (2016) DOI: 10.1039/c6nr02791a</p> <p>The trajectories are saved in the .xtc format, and initial structures with specification of atom types are given in the .pdb format.</p> <p>The name of each file contains brief information about the simulated system:</p> <p>TiO2 : composition of the nanoparticle<br> n24 : number of TiO2 units in the nanoparticle<br> anatase/brookite/rutile : type of crystall structure<br> - a number 0 - 30 : number of water molecules in the simulation<br> 2fs - the time step</p> <p>For more details, see the referred paper</p>
Dataset For Molecular Dynamics Simulations of Thin Film Rupture
<p>Data files for production runs for the key results reported in "Life and Death of a Thin Liquid Film", (2024) by Muhammad Rizwanur Rahman, Li Shen, James P. Ewen, D. M. Heyes, Daniele Dini, and E. R. Smith. The directory named "spontaneous-rupture-equilibrated-state-for-production-runs" contains data files of different initial film thicknesses, and the directory named "synthetic-rupture-equilibrated-state-for-production-runs" contains data files for films with similar initial thickness, but with different patterns of synthetic damages caused to the film. These files should be used as the restart file for production phase under NVE ensemble. </p> <p>Codes to run these files, and process the data are described in github: https://github.com/MuhammadRRahman/Thin-Film-Rupture-NEMD.git.</p>
Growth of hexagonal boron nitride from molten nickel solutions: a reactive molecular dynamics study
<p>Authors: Amin Ahmadisharaf and Jeffrey Comer</p> <p><br>Publication: Amin Ahmadisharaf, Bin Liu, James H. Edgar, and Jeffrey Comer (2025) Growth of Hexagonal Boron Nitride from Molten Nickel Solutions: A Reactive Molecular Dynamics Study. ACS Applied Materials & Interfaces. <a href="https://doi.org/10.1021/acsami.4c16991">doi.org/10.1021/acsami.4c16991</a></p> <p>Funding: Department of Energy Office of Science, grant DE-SC0021264, <a>https://pamspublic.science.energy.gov/WebPAMSExternal/Interface/Common/ViewPublicAbstract.aspx?rv=5e6ffff5-0daa-47e8-a3d0-20f594b7bfb8&rtc=24&PRoleId=10</a></p> <p>**************************************</p> <p>This data set for the manuscript entitled "Growth of Hexagonal Boron Nitride from Molten Nickel Solutions: A Reactive Molecular Dynamics Study" includes all files needed to run and analyze the simulations described in the this manuscript in the molecular dynamics software LAMMPS, as well as the output of the simulations. The files are organized into directories corresponding to the figures of the main text. They include force field parameter files (in ReaxFF format), LAMMPS configuration files (*.in), ReaxFF control files (*.control), LAMMPS log files (*.log), and LAMMPS output including restart files (in binary LAMMPS format) and trajectories in dcd format (downsampled to 12.5 or 25 ps per frame) and also PDB and PSF files are useful for visualization with VMD. Analysis is performed by python and shell scripts (Bash-compatible) that call VMD Tcl scripts or python scripts. These scripts and their output are also included.</p> <p>The species analysis is performed by the VMD Tcl script "Figure3/analysis/count_hBN_species_NNB_BN.tcl" using the parameters given in "Figure3/analysis/doCount.sh".</p> <p>The directory contents are as follows.</p> <p>--------------------------------------------------------------<br>Figure-1: Parallel tempering simulations of the boron-nickel system and calculation of the boron concentration along the z-dimension of the nickel slab.</p> <p>The analysis of the boron concentration profile is performed by the VMD Tcl scripts calcRatioZRef.tcl and calcConcZRef.tcl using the parameters given in "Figure1/analysis/step3_conc_profile.sh". Also, the reorganization of the parallel tempering trajectories into frames at a single temperature is performed by the VMD Tcl script extractReplicaFrames.tcl based on "Figure1/analysis/step1_sort_frames.sh".</p> <p><br>--------------------------------------------------------------<br>Figure-2: Simulation of hBN sheet growth at 1750 K and calculation of largest cluster.</p> <p><br>--------------------------------------------------------------<br>Figure-3: Simulations of different boron-to-nickel ratios at varying nitrogen pressures at 1750 K and the calculation of the largest hBN cluster formed under different scenarios. The suffixes "liu", "long_liu", and "low_liu" correspond to pressures of 100.0, 50.0, and 25.0 atm respectively.</p> <p>The analysis of hBN clusters is performed by the VMD Tcl script "Figure3/analysis/" using the parameters given in "Figure3/analysis/doCount.sh". The related simulations files and outputs for panel A in this figure are located in Figure 5 directory.</p> <p><br>--------------------------------------------------------------<br>Figure-4: Recognition and counting the different boron-nitrogen motifs in the simulation was performed in Figure 2.</p> <p>The related simulations files and outputs for panel B and C in this figure are located in Figure 5 directory.</p> <p><br>--------------------------------------------------------------<br>Figure-5: Simulation of the temperature effect on hBN growth, and recognition and counting of the different boron-nitrogen motifs at 1750, 1800, 1900, 2000, 2200, and 2700 K.. </p> <p><br>--------------------------------------------------------------<br>Figure-6: Recognition of existing motifs for nitrogen atoms in the growth path of hBN and calculation of the probabilities of transitions between different motifs across all nitrogen atoms.</p> <p>The related simulations files and outputs for all panels in this figure are located in Figure 5 directory.</p> <p><br>--------------------------------------------------------------<br>Figure-7: Comparing the ReaxFF and ab initio simulations of small B-N motifs(B--N--B and B--N) in a nickel slab and calculation of bond lengths and angle values.</p> <p><br>--------------------------------------------------------------<br>Figure-8: Diffusion simulations of four different systems at 1800 K: nickel with a single B atom, nickel with a single N atom, nickel with a free B-N-B molecule, and nickel with a small hBN sheet and Mean Squared Displacement (MSD) values were calculated and compared to assess the surface mobility of the different particles.</p> <p> </p>
All-atom 500-nano seconds Molecular Dynamics Simulations of SARS-CoV-2 Spike Receptor-binding Domain bound with ACE2
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of of SARS-CoV2 Spike Protein/ACE2 complex (PDB ID: 6M0J). In order to decrease the size of the file only protein rajectories were provided. Simulation has been performed with Desmond. Protein was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 500 nano-seconds (ns) production run was performed for the simulation.</p>
Representative Structures from Molecular Dynamics Simulations of the Inward Facing and Outward Facing States of LaINDY
<p>This upload is a supplementary data set for the following publication: <a href="https://doi.org/10.7554/eLife.61350">D. B. Sauer, N. Trebesch, J. J. Marden, N. Cocco, J. Song, A. Koide, S. Koide, E. Tajkhorshid, and D.-N. Wang. "Structural basis for the reaction cycle of DASS dicarboxylate transporters." <em>eLife</em>. <strong>9</strong>, e61350. DOI: 10.7554/eLife.61350</a>. Please see the main publication for the methods, analysis, and discussion associated with this data set.</p>
Broadband Dielectric Spectroscopy Study of Biobased Poly(alkylene 2,5-furanoate)s' Molecular Dynamics
<p><strong>Related publication:</strong><br> Soccio, M.; Martínez-Tong, D.E.; Guidotti, G.; Robles-Hernández, B.; Munari, A.; Lotti, N.; Alegria, A. Broadband Dielectric Spectroscopy Study of Biobased Poly(alkylene 2,5-furanoate)s’ Molecular Dynamics. <em>Polymers</em> 2020, <em>12</em>, 1355.<br> <a href="https://doi.org/10.3390/polym12061355">10.3390/polym12061355</a></p> <p><strong>EUSMI proposal codes:</strong><br> E171100040, E171100043</p>
Molecular Details Underlying Dynamic Structures and Regulation of the Human 26S Proteasome
<p>The 26S proteasome is the macromolecular machine responsible for ATP/ubiquitin dependent degradation. As aberration in proteasomal degradation has been implicated in many human diseases, structural analysis of the human 26S proteasome complex is essential to advance our understanding of its action and regulation mechanisms. In recent years, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for elucidating structural topologies of large protein assemblies, with its unique capability of studying protein complexes in cells. To facilitate the identification of cross-linked peptides, we have previously developed a robust amine reactive sulfoxide-containing MS-cleavable cross-linker, disuccinimidyl sulfoxide (DSSO). To better understand the structure and regulation of the human 26S proteasome, we have established new DSSO-based in vivo and in vitro XL-MS workflows by coupling with HB-tag based affinity purification to comprehensively examine protein-protein interactions within the 26S proteasome. In total, we have identified 447 unique lysine-to-lysine linkages delineating 67 inter-protein and 26 intra-protein interactions, representing the largest cross-link dataset for proteasome complexes. In combination with EM maps and computational modeling, the architecture of the 26S proteasome was determined to infer its structural dynamics. In particular, three proteasome subunits Rpn1, Rpn6 and Rpt6 displayed multiple conformations that have not been previously reported. Additionally, cross-links between proteasome subunits and 15 proteasome interacting proteins including 9 known and 6 novel ones have been determined to demonstrate their physical interactions at the amino-acid level. Our results have provided new insights on the dynamics of the 26S human proteasome and the methodologies presented here can be applied to study other protein complexes.</p> <p>For more information about how to reproduce this modeling, see https://salilab.org/26S-PIPs or the README file.</p>
Data for the publication "Sodium Triflate Water-in-Salt Electrolyte in Advanced Battery Applications: A First-principles Based Molecular Dynamics Study"
<p>The datasets 'CONTCAR_aiMLMD' and 'CONTCAR_AIMD' represent the final structures obtained from the aiMLMD and AIMD simulations, respectively. These simulations were conducted using VASP at T=333K and c=9.25 m.</p> <p>The datasets 'NP.rdf' and 'MSD_NP.xlsx' represent the radial pair distribution functions at different time steps and the time-dependent variations of mean squared displacement for sodium in 10 segments of the classical MD trajectory. The associated MD simulation was performed using a nonpolarizable force field in the LAMMPS package at T=333K and c=9.25 m. The file 'dataNP.lmp' includes the initial configuration for this simulation. The GROMOS parameters were employed for LJ interactions of sodium and all other force field parameters were set according to Table 1 in the manuscript.</p> <p>The datasets 'P.rdf' and 'MSD_P.xlsx,' respectively, represent the radial pair distribution functions at different time steps and the time-dependent variations of mean squared displacement for sodium in 10 segments of the classical MD trajectory. These data were obtained employing the Drude oscillator model in the LAMMPS package at T=333K and c=10 m. The file 'dataP.lmp' includes the initial configuration for this simulation. The simulation was conducted using the optimal force field parameters 'Sys. 1,' as described in table 3 of the manuscript.</p> <p>The second column in the files 'NP.rdf' and 'NP.rdf' represents the distance from sodium. The subsequent odd columns display the radial distribution functions for the Na-C, Na-F, Na-S, Na-O, Na-Na, Na-Hw, and Na-Ow pairs, while the even columns present the coordination numbers for the same atom pairs.</p>
Two 100 ns NVT molecular dynamics simulations of dsDNA and dsRNA "GGGG" 18-mers (GCGGGGGGGGGGGGGGGC)
<p>Supporting information for "Molecular origin of distinct hydration dynamics in double helical DNA and RNA sequences" by E. Frezza, D. Laage and E. Duboué-Dijon, <span><em>J. Phys. Chem. Lett.</em></span> <span>2024</span><span>, 15</span><span>, </span><span>4351–4358</span><br>Two 100 ns-long NVT molecular dynamics simulation: one of dsDNA "GGGG" 18-mer (GCGGGGGGGGGGGGGGGC) and one of the analogous dsRNA. The nucleic acid is explicitly solvated in water and neutralized with 0.15M KCl. Simulations were performed using the Gromacs 5 software. DNA is described with the Amber 99SB-ILDN force field with the BSC0 modifications, RNA is described with the Amber 99SB-ILDN force field with the BSC0 and χOL3 modifications, the SPC/E force field is used for water, and the Joung Cheatham paraeters for ions. The shared coordinates are saved every 500fs, twice less frequently than the original trajectories used for the publication, to reduce the size of the shared dataset below the allowed size limit.</p>
Data related to the article "Impedance of nanocapacitors from molecular simulations to understand the dynamics of confined electrolytes"
<p>Contains input files and data used to generate the figures of the article:</p> <p>Impedance of nanocapacitors from molecular simulations to understand the dynamics of confined electrolytes<br>(Giovanni Pireddu, Connie J. Fairchild, Samuel P. Niblett, Stephen J. Cox and Benjamin Rotenberg)</p> <p>ChemRxiv: https://doi.org/10.26434/chemrxiv-2023-2ccrw</p> <p>Published version: to be inserted upon publication</p> <p>The folder EXAMPLE_INPUT_FILES contains typical [MetalWalls](https://doi.org/10.21105/joss.02373) ([repository](https://gitlab.com/ampere2/metalwalls)) and [LAMMPS]([repository](https://github.com/lammps/lammps)) input files used to perform the molecular simulations.</p> <p>The folder DATA_FIGURES contains the processed data used to plot all the figures of the paper (see below).</p> <p><br>Notes: <br>1) In the file names, the notation 'M01', 'M05', 'M10' and 'M15' refers to the salt concentration in each system (0.1, 0.5, 1.0 and 1.5, respectively). 'W' refers to pure water (0 M) systems.<br>2) In the file names, the notation 'd1', 'd2', 'd3', 'd4', refers to different interelectrode distances (d1= 2.56 nm; d2= 5.07 nm; d3= 9.80 nm; d4= 19.84 nm) <br>3) The files containing the polarization cross-correlation are marked with 'AxB' indicating the cross-correlation between the contributions A and B. Specifically A and B can be: <br> - T = total<br> - I = ion<br> - W = water</p> <p><br>Figure 1:<br>- Panel B<br> - 'Fig1_CapConcentration': Differential capacitance scaled by electrode area as a function of NaCl concentration<br>- Panel C<br> - 'Fig1_QACF_*': Electrode charge autocorrelation function<br>- Panel D<br> - 'Fig1_Norm_QACF_*': Normalized electrode charge autocorrelation function<br> - 'Fig1_NormChar_*': Normalized non-equilibrium charge response</p> <p>Figure 2:<br>- Panel A: <br> - 'Fig2_ReZ_*': Real part of impedance<br>- Panel B:<br> - 'Fig2_nImZ_*': Negative imaginary part of impedance<br>- Panel C:<br> - 'Fig2_ReZint_*': Real part of interfacial impedance<br> - 'Fig2_Resistivities.dat': Resistivity as a function of NaCl concentration (bulk, confined, Nernst-Einstein)<br>- Panel D:<br> - 'Fig2_nImZint_*': Negative imaginary part of interfacial impedance<br> - 'Fig2_ECM*': Capacitor contributions to the imaginary part of interfacial impedance (finite concentrations)<br> - 'Fig2_ECW1.dat': Capacitor contributions to the imaginary part of interfacial impedance (pure water). Full cell capacitance taken into account<br> - 'Fig2_ECW2.dat': Capacitor contributions to the imaginary part of interfacial impedance (pure water). Interfacial capacitance taken into account </p> <p>Figure 3:<br>- Panel A:<br> - 'Fig3_ReCond_Peyman_M10.dat': Real part of conductivity (data from: A Peyman, C Gabriel, E Grant, Complex permittivity of sodium chloride solutions at microwave frequencies. Bioelectromagnetics 28, 264–274 (2007))<br> - 'Fig3_ReCond_Querry_M10.dat': Real part of conductivity (data from: MR Querry, RC Waring, WE Holland, GM Hale, W Nijm, Optical Constants in the Infrared for Aqueous Solutions of NaClt. J. Opt. Soc. Am. 62 (1972)) <br> - 'Fig3_ReCond_Vinh_M10.dat': Real part of conductivity (data from: NQ Vinh, et al., High-precision gigahertz-to-terahertz spectroscopy of aqueous salt solutions as a probe of the femtosecond-to-picosecond dynamics of liquid water. The J.<br>Chem. Phys. 142, 164502 (2015).)<br> - 'Fig3_ReCond_M10.dat': Real part of conductivity from MD simulations<br>- Panel B:<br> - 'Fig3_ReCond_M*/W.dat': Real part of conductivity from MD simulations<br> - 'Fig3_ReCond_Peyman_M*': Real part of conductivity (data from: A Peyman, C Gabriel, E Grant, Complex permittivity of sodium chloride solutions at microwave frequencies. Bioelectromagnetics 28, 264–274 (2007))<br>- Panel C:<br> - 'Fig3_Cond0.dat': Static conductivity as a function of concentration (MD data)<br> - 'Fig3_Cond0_Buchner.dat': Static conductivity as a function of concentration (data from: R Buchner, GT Hefter, PM May, Dielectric relaxation of aqueous nacl solutions. The J. Phys. Chem. A 103, 1–9 (1999))<br> - 'Fig3_Cond0_Peyman.dat': Static conductivity as a function of concentration (data from: A Peyman, C Gabriel, E Grant, Complex permittivity of sodium chloride solutions at microwave frequencies. Bioelectromagnetics 28, 264–274 (2007))</p> <p>Figure 4:<br>- Panel A: <br> - 'Fig4_ReZ_d*': Real part of impedance (MD simulations)<br> - 'Fig4_ReZEC_d*': Real part of impedance (equivalent circuit model)<br>- Panel B:<br> - 'Fig4_nImZ_d*': Negative imaginary part of impedance (MD simulations)<br> - 'Fig4_nImZEC_d*': Negative imaginary part of impedance (equivalent circuit model)</p> <p>Figure 5:<br>- 'Fig5_TauQ.dat': timescales from the total charge autocorrelation functions<br>- 'Fig5_iontot.dat': timescales from the TxI autocorrelation function<br>- 'Fig5_RC.dat': timescales from the RC estimates<br>- 'Fig5_RbulkC.dat': timescales from the RbulkC estimates<br>- 'Fig5_Taudiff.dat': timescales from the difference between electrolyte and pure water QACFs<br>- 'Fig5_taud.dat': tau_d analytical timescales<br>- 'Fig5_tauDebye.dat': tau_Debye analytical timescales<br>- 'Fig5_taumix.dat': tau_mix analytical timescales</p> <p>Figure 6:<br>- Panel A:<br> - 'Fig6_Static_*: Static correlation between polarization contributions as a function of salt concentration<br>- Panel B:<br> - 'Fig6_Dynamic_EQ_*_M01' Dynamical correlations between polarization contributions (equilibrium MD results)<br> - 'Fig6_Dynamic_NEQ_*_M01' Dynamical correlations between polarization contributions (non-equilibrium MD results)<br>- Panel C:<br> - 'Fig6_Dynamic_EQ_*_M10' Dynamical correlations between polarization contributions (equilibrium MD results)<br> - 'Fig6_Dynamic_NEQ_*_M10' Dynamical correlations between polarization contributions (non-equilibrium MD results)</p> <p> </p> <p> </p>
Data for "Dynamic of binary molecular systems – advantages and limitations of NMR relaxometry"
<p>Raw data for "Dynamic of binary molecular systems – advantages and limitations of NMR relaxometry". DOI of article: https://doi.org/10.1063/5.0188257</p>
Strong coupling electron-photon dynamics: a real-time investigation of energy redistribution in molecular polaritons - Dataset
<p>Dataset complement to "Strong coupling electron-photon dynamics: a real-time investigation of energy redistribution in molecular polaritons" - includes output and video files obtained using the <a href="https://etprogram.org/">eT program</a>, an open-source electronic (and molecular-polaritonic) structure program.</p> <p>See the paper at <a href="https://doi.org/10.1103/PhysRevResearch.6.033283">https://doi.org/10.1103/PhysRevResearch.6.033283</a></p>
Molecular Dynamic Simulation on the Role of CL5D in Accelerate the Product Dissociation of SIRT6
<p>The source data used to generate figures in the main text is stored in the ‘Source Data.xlsx’ file, and 'Source Data Description.docx' is a brief description of the source data table.<br>'SIRT6.prmtop' and 'SIRT6.inpcrd' are initial structure of SIRT6 system,'SIRT6-CL5D.prmtop' and 'SIRT6-CL5D.inpcrd' are initial structure of SIRT6-CL5D system.<br>'SIRT6_equ.pdb', 'SIRT6-CL5D'_equ.pdb are snapshots of the equilibrium structure of the SIRT6 system and the SIRT6-CL5D system, respectively.<br>'ramd.conf' is an example configuration file that uses RAMD simulations to obtain the AR6 dissociation path in the SIRT6 system, with the acceleration of 0.0625 kcal/Å/g and a cutoff distance of 0.005 Å.<br>'win1.conf' and 'win1.in' are example configuration files for the first window of the umbrella sampling, which calculates the dissociation energy barrier of AR6 in the SIRT6 system,'win1.in' is the parameter file for umbrella sampling, with A 2.5 kcal/mol/Ų spring constant, and window center is 9 Å.</p> <p> </p>
Dry trajectories of SARS-CoV-2 RBD from accelerated molecular dynamics simulation
<p>These are supplementary files to the preprint/paper "SARS-CoV-2 spike protein unlikely to bind to integrins via the Arg-Gly-Asp (RGD) motif of the Receptor Binding Domain: evidence from structural analysis and microscale accelerated molecular dynamics" (http://dx.doi.org/10.1101/2021.05.24.445335).</p> <p>The attached code in Jupyter notebook can be run after installing the virtual environment using the `environment.yml `</p> <p>The file `data.zip` needs to be extracted to the same path where the notebook is run from</p>
Molecular Dynamics simulations suggest possible activation and deactivation pathways in hERG channel
<ol> <li>equil_gating_4_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 4 equilibration trajectory</li> <li>equil_gating_6_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 6 equilibration trajectory</li> <li>equil_gating_8_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 8 equilibration trajectory</li> <li>equil_gating_4.dcd: 100 ns NPT trajectory of the hERG closed state with gating charge 4</li> <li>equil_gating_6.dcd: 100 ns NPT trajectory of the hERG closed state with gating charge 6</li> <li>equil_gating_8.dcd: 100 ns NPT trajectory of the hERG closed state with gating charge 8</li> <li>equil_open_assembly_xleap.prmtop: file topology of the hERG open state equilibration trajectory</li> <li>equil_open.dcd: 100 ns NPT trajectory of the hERG open state</li> <li>herg_closed_gating_4.pdb: PDB file of hERG closed state with gating charge 4 after Steered MD simulations</li> <li>herg_closed_gating_6.pdb: PDB file of hERG closed state with gating charge 6 after Steered MD simulations</li> <li>herg_closed_gating_8.pdb: PDB file of hERG closed state with gating charge 8 after Steered MD simulations</li> <li>TMD_O-C_closed_gating_8_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 8 TMD trajectory</li> <li>TMD_O-C_closed_gating_6_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 6 TMD trajectory</li> <li>TMD_O-C_closed_gating_4_assembly_xleap.prmtop: file topology of the hERG closed state with gating charge 4 TMD trajectory</li> <li>TMD_O-C_closed_gating_8.dcd: TMD trajectory of the hERG closed state with gating charge 8</li> <li>TMD_O-C_closed_gating_6.dcd: TMD trajectory of the hERG closed state with gating charge 6</li> <li>TMD_O-C_closed_gating_4.dcd: TMD trajectory of the hERG closed state with gating charge 4</li> </ol> <p>MD trajectories (equilibration and Targeted MD trajectories) in dcd format can be visualized using visualization tools such as VMD or PyMol after uploading the topology file.</p> <p>The directory data_supplementary-note-4.tar.bz2 contains the files related to the Supplementary Notes 4: "A practical example of pathway calculation".</p>
A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories
<p>Containes input data for MD simulations of 3 HSP90- small compound complexes from the paper</p> <p>A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories" from Daria B. Kokh, Bernd Doser , Stefan Richter , Fabian Ormersbach , Xingyi Cheng, Rebecca C. Wade, publishe in J. Chem. Phys. <strong>153</strong>, 125102 (2020); <a href="https://doi.org/10.1063/5.0019088">https://doi.org/10.1063/5.0019088</a></p> <ul> <li>ref.pdb - structure of the complex in PDB format</li> <li>ref.prmtop - topology file in AMBER</li> <li>ref-equal-NTP.pdb - structure after NTP equilibration </li> <li>ref-equal-NTP.rst7 - coordinates after NTP equilibration</li> <li>ref-equal-NTP.crd - coordinates after NTP equilibration </li> <li>gromacs.gro - coordinates in Gromacs format (after NTP equalibration)</li> <li>gromacs.top - Gromacs topology </li> </ul> <p> </p>
ScienceDex guides
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.