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10 results for “NMR relaxation”
Human thymidylate synthase NMR relaxation data
<p>Table of intensities of NMR signals of human thymidylate synthase in multiple bound forms from several NMR relaxation experiments. Bound forms studied include apo, dUMP (substrate) bound, TMP (product) bound, as well as apo and dUMP bound N-terminal truncation. Experiments include methyl 13C MQ and SQ CPMG, CHD2 methyl 13C CEST, CHD2 methyl 2H R2, solvent PRE, backbone amide RDC, and 15N relaxation. Details of the data collection can be found in the associated publication.</p>
Supporting data for manuscript describing Slice and Dice method to measure NMR relaxation with nested experiments
<p>This is a supporting dataset for the manuscript "Slice and Dice: Nested Spin-lattice Relaxation Measurements" by W. Trent Franks, Jacqueline Tognetti and Józef R. Lewandowski.</p> <ul> <li><strong>NMR_data.zip : </strong>Raw NMR data in the Bruker format for the experiments presented in the manuscript. The file expands to a directory called "Raw NMR Data" that contains: <ul> <li>ReadMe_NMR_data.txt - describing the datasets included in the file.</li> <li>Record 1: <sup>13</sup>C<sup><span class="math-tex">\(^\alpha\)</span></sup> individual experiment. Pulse program name: hRCH_CT1</li> <li>Record 2: <sup>13</sup>C' individual experiment. Pulse program name: hCOcaH_SP_T1</li> <li>Record 3: <sup>15</sup>N individual experiment. Pulse program name: hRNH_NT1b</li> <li>Record 10: <sup>13</sup>C<span class="math-tex">\(^\alpha\)</span> + <sup>13</sup>C' + <sup>15</sup>N Slice & Dice experiment. Pulse program name: hR[COca,Ca,N]Ha_T10818 corresponding to the final sequence: hR[N,COca,Ca]HR_T1</li> </ul> </li> <li><strong>Pulse_program.zip</strong>: The pulse program and include file for the Slice and Dice experiment described in the manuscript. The pulse program in Bruker format (war.hR[COca,Ca,N]H_T1 - this is a text file that can be opened with any text editor) was tested on a Bruker Avance III HD console. Both the pulse program file, war.hR[COca,Ca,N]H_T1, and include file, HCN_defs.incl, need to be placed in the pulse program directory (/opt/topspinXX/exp/stan/nmr/lists/pp/user where XX is replaced with the version of Topspin). The file expands to a directory "Pulse_program_incl" that contains: <ul> <li>war.hR[COca,Ca,N]H_T1 - pulse program</li> <li>HCN_defs.incl - include file</li> <li>ReadMe_SliceDice_pp.txt - details on how to set up the experiment.</li> </ul> </li> <li><strong>HowToProcessSliceAndDice.pdf</strong> : Instructions on how to process Slice and Dice experiment in Topspin.</li> <li><strong>MultiR1list.zip: </strong>A program written in Python 3 required to calculate delay lists for the nested experiment to be included in the pulse program. The file expands to a directory MultiT1list directory that contains: <ul> <li>MultiT1list.py - the program</li> <li>ReadMe_MultiT1list.txt - instructions on how to use the program</li> </ul> </li> <li><strong>SNDProcguide.py.zip</strong>: A program written in Python 2 (SNDProcguideV2.py), which generates macro for processing and sorting 2D planes in Topspin. The script also provides some tips on setting parameters for different 2Ds and sorted lists of relaxation delays. Example output of the script is also included. The parameters in the script are set for the supplied example data.</li> <li><strong>HowToProcess.mp4</strong> - a video working through an example of processing Slice and Dice data.</li> </ul> <p> </p> <p> </p>
Human thymidylate synthase NMR relaxation data
Open the record for dataset details and reuse information.
Supplementary data to the paper "Large scale voxel-based FEM formulation for NMR relaxation in porous media"
<p>This repository contains supplementary data to the paper "Large scale voxel-based FEM formulation for NMR relaxation in porous media", which is being considered for publication. The files are:<br><br>**_data.zip - Binary image files;</p> <p>FEM_T2_**.csv - T2 simulation results using finite elements;</p> <p>FEM_**_inv.csv - T2 inversion for the finite element simulations;</p> <p>RW_T2_**.csv - T2 simulation results using random walk;</p> <p>RW_**_inv.csv - T2 inversion for the random walk simulations;</p> <p>local_digital_correction.c - Vector containing the local geometry correction factors, accessed integers formed by the 8-bit binary key of the node neighborhood;</p> <p>Where ** is the rock type:</p> <p>AC - Austin Chalk</p> <p>BS - Berea Stripe</p> <p>DP - Desert Pink</p> <p>IB - Idaho Brown</p> <p>Obs.: in order to obtain the relaxation curves the following parameters were utilized in the simulations:</p> <p>Bulk diffusivity: 2500 micro-m2/s (all rock samples) </p> <p>Bulk relaxation: 2.6 s (all rock samples)</p> <p>Voxel size: {1.0; 2,0; 0.9; 2.0} micro-m (for AC, BS, DP, IB respectively)</p> <p>Surface relaxivity: {23.3; 12.1; 12.3; 8.3} micro-m/s (for AC, BS, DP, IB respectively)</p>
Magic Angle Spinning Effects on Longitudinal NMR Relaxation: 15N in L-Histidine
<p>Experimental datasets for the publication entitled: Magic Angle Spinning Effects on Longitudinal NMR Relaxation: <sup>15</sup>N in L-Histidine</p>
Dataset for "Sorption, anomalous water transport and dynamic porosity in cement paste: A spatially localised 1H NMR relaxation study and a proposed mechanism"
<p>This record is the dataset for Figures 4, 5, 6, 7, 8 and 9 in the journal article "Sorption, anomalous water transport and dynamic porosity in cement paste: A spatially localised 1H NMR relaxation study and a proposed mechanism" published in Cement and Concrete Research, Volume 133, July 2020, 106045, https://doi.org/10.1016/j.cemconres.2020.106045.</p> <p>Abstract: The link between anomalous water sorption and dynamic porosity in cement pastes is explored using spatially resolved GARField1H nuclear magnetic resonance (NMR) relaxation analysis. A model is developed in which the effective capillary diffusion coefficient is dependent on the instantaneous pore size distribution. This and earlier data show changes in pore size distribution resultant from changes in saturation that do not occur instantaneously with changes in degree of saturation. Therefore, it is assumed that the pore size distribution is always relaxing exponentially towards a (saturation dependent) equilibrium. It follows that the diffusivity is sample history (i.e. time) dependent as well as saturation dependent. This is sufficient to explain anomalies in rapid capillary water sorption. The same concepts are applied to slow drying. In this case, porosity changes occur on a timescale much shorter than drying so the system is always in dynamic equilibrium and anomalies are therefore not seen.</p>
3x 1 µs all-atom MD trajectories; AMBER ff15ipq & SPC/Eb; T4 Lysozyme; 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Simulation data for "Fitting side-chain NMR relaxation data using molecular simulations" (https://doi.org/10.1101/2020.08.18.256024).</p> <ul> <li>3 x 1 µs all-atom MD simulations of T4 Lysozyme</li> <li>Force field: AMBER ff15ipq with modified methyl rotation barriers<sup>1</sup></li> <li>Water model: SPC/Eb</li> <li>Compressed protein coordinates saved every 1 ps to enable calculation of side-chain NMR relaxation parameters</li> </ul> <p>Contains:</p> <ul> <li>3 x GROMACS .xtc trajectory files for 3 independent simulations</li> <li>3 x corresponding GROMACS .tpr topology files</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2020). Predicting NMR relaxation of proteins from molecular dynamics simulations with accurate methyl rotation barriers. <em>Journal of Chemical Physics</em>, <em>152</em>(8). https://doi.org/10.1063/1.5135379</p>
5x 1 µs all-atom MD trajectories; AMBER ff99SB*-ILDN & TIP4P/2005; T4 Lysozyme; 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Simulation data for "Fitting side-chain NMR relaxation data using molecular simulations" (https://doi.org/10.1101/2020.08.18.256024).</p> <ul> <li>5 x 1 µs all-atom MD simulations of T4 Lysozyme</li> <li>Force field: AMBER ff99SB*-ILDN with modified methyl rotation barriers<sup>1</sup></li> <li>Water model: TIP4P/2005</li> <li>Compressed protein coordinates saved every 1 ps to enable calculation of side-chain NMR relaxation parameters</li> </ul> <p>Contains:</p> <ul> <li>5 x GROMACS .xtc trajectory files for 5 independent simulations</li> <li>5 x corresponding GROMACS .tpr topology files</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2018). Accurate Methyl Group Dynamics in Protein Simulations with AMBER Force Fields. <em>The Journal of Physical Chemistry B</em>, <em>122</em>(19), 5038–5048. https://doi.org/10.1021/acs.jpcb.8b02769</p>
3x 5 µs all-atom MD trajectories; AMBER ff99SB*-ILDN & TIP4P/2005; T4 Lysozyme; 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Simulation data for "Fitting side-chain NMR relaxation data using molecular simulations" (https://doi.org/10.1101/2020.08.18.256024).</p> <ul> <li>3 x 5 µs all-atom MD simulations of T4 Lysozyme</li> <li>Force field: AMBER ff99SB*-ILDN with modified methyl rotation barriers<sup>1</sup></li> <li>Water model: TIP4P/2005</li> <li>Compressed protein coordinates saved every 1 ps to enable calculation of side-chain NMR relaxation parameters</li> </ul> <p>Contains:</p> <ul> <li>3 x GROMACS .xtc trajectory files for 3 independent simulations</li> <li>3 x corresponding GROMACS .tpr topology files</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2018). Accurate Methyl Group Dynamics in Protein Simulations with AMBER Force Fields. <em>The Journal of Physical Chemistry B</em>, <em>122</em>(19), 5038–5048. https://doi.org/10.1021/acs.jpcb.8b02769</p>
Rotamer distributions and spectral densities for 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Rotamer distributions and spectral density functions of methyl-bearing side chains of T4-Lysozyme from all-atom molecular dynamics simulations.</p> <p>3 sets of all-atom MD simulations:</p> <ul> <li>3 x 5 µs a99*-ILDN + modified methyl rotation barriers<sup>1</sup> & TIP4P/2005 water</li> <li>5 x 1 µs a99*-ILDN + modified methyl rotation barriers<sup>1</sup> & TIP4P/2005 water</li> <li>3 x 1 µs a15ipq + modified methyl rotation barriers<sup>2</sup> & SPC/Eb water</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2018). Accurate Methyl Group Dynamics in Protein Simulations with AMBER Force Fields. <em>The Journal of Physical Chemistry B</em>, <em>122</em>(19), 5038–5048. https://doi.org/10.1021/acs.jpcb.8b02769<br> <sup>2</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2020). Predicting NMR relaxation of proteins from molecular dynamics simulations with accurate methyl rotation barriers. <em>Journal of Chemical Physics</em>, <em>152</em>(8). https://doi.org/10.1063/1.5135379</p>
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OpenNeuro
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