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35 results for “hydrogen bond”
Mechanically Resistant Poly(N-vinylcaprolactam) Microgels with Sacrificial Supramolecular Catechin Hydrogen Bonds
<p>Original data corresponding to the plots of Figures 2, 4, 5 of the manuscript and S1-S16 of the Supporting Information in *.csv format and raw data for NMR measurements.</p>
Automatic learning of hydrogen-bond fixes in an AMBER RNA force field - dataset
<p>Supporting data related to manuscript "Automatic learning of hydrogen-bond fixes in an AMBER RNA force field"</p>
Charting Hydrogen Bond Anisotropy
<p>Interaction energies of hydrogen bonded dimers using quantum mechanics. Each dome is a systematic scan of interaction geometries, where a target molecule is kept fixed, and a probe is moved in spherical coordinates. Collectively, the positions of the probe look like a dome over the target molecule. There are about 2000 geometries in each dome. The goal is to see how the interaction energy depends on the geometry of the interaction.<br> <br> </p>
Crossover from Hydrogen to Chemical Bonding
<p>The files contain the data that are shown in the figures of the Main Text and of the Supplementary Materials of the research article:</p> <p>Bogdan Dereka, Qi Yu, Nicholas H. C. Lewis, William B. Carpenter, Joel M. Bowman, Andrei Tokmakoff "Crossover from Hydrogen to Chemical Bonding"</p>
Metadata of " Stability of Selected Hydrogen Bonded Semiconductors in Organic Electronic Devices"
<p>Metadata of " Stability of Selected Hydrogen Bonded Semiconductors in Organic Electronic Devices"</p>
Supplementary Data for "How Strong is the Hydrogen Bond in Hybrid Perovskites?
<p>DFT optimised structures for the hybrid perovskites with the X organic cation and the Y anion:</p> <p>POSCAR-X-Y-D3</p> <p>NMRdata.zip with NMR data for the four Zn formate perovskites and the X organic cation:</p> <p>X.dx </p>
Neural-network-based molecular dynamics simulations reveal that proton transport in water is doubly gated by sequential hydrogen-bond exchange: Neural network potentials training data
<h1>Neural network potentials of an excess proton in bulk water, training data</h1> <p>This dataset contains 2188 configurations labeled at two hybrid DFT levels (revPBE0-D3 and B3LYP-D3).</p> <p>The configurations are given as a single XYZ file: configurations.xyz</p> <p>The box dimensions are written in box.txt</p> <p>The energies for all configurations at a given level of theory are written in energies_LEVEL.txt (one configuration per line)</p> <p>The atomic forces for each configuration at a given level of theory are gathered in a XYZ file: forces_LEVEL.xyz</p> <p>The relative displacements of the Wannier centroids, with respect to the closest oxygen atom, for each configuration at a given level of theory, are in the following XYZ file: wannier-centroids-displacements_LEVEL.xyz</p>
Dataset for "Control of Substrate Conformation by Hydrogen Bonding in a Retaining β-Endoglycosidase"
<p>This data set contains files related to the article "<strong>Control of Substrate Conformation by Hydrogen Bonding in a Retaining β-Endoglycosidase</strong>" by Alba Nin-Hill, Albert Ardèvol, Xevi Biarnés, Antoni Planas and Carme Rovira. </p><p><strong>ABSTRACT</strong></p><p>Bacterial β-glycosidases are hydrolytic enzymes that depolymerize polysaccharides such as β-cellulose, β-glucans and β-xylans from different sources are used in a myriad of biomedical and industrial applications. It has been shown that a conformational change of the substrate, from a relaxed 4<i>C</i>1 conformation to a distorted 1<i>S</i>3/1,4<i>B</i> conformation of the reactive sugar, is necessary for catalysis. However, the molecular determinants that stabilize the substrate's distortion are poorly understood. Here we use quantum mechanics/molecular mechanics (QM/MM)-based molecular dynamics methods to assess the impact of the interaction between the reactive sugar, <i>i.e. </i>the one at subsite<i> -1,</i> and the catalytic nucleophile (a glutamate) on substrate conformation. We show that the hydrogen bond involving the C2 exocyclic group and the nucleophile controls substrate conformation: its presence preserves sugar distortion, whereas its absence (<i>e.g.</i> in an enzyme mutant) knocks it out. We also show that 2-deoxy-2-fluoro derivatives, widely used to trap the reaction intermediates by X-ray crystallography, reproduce the conformation of the hydrolysable substrate at the experimental conditions. These results highlight the importance of the 2-OH···nucleophile interaction in substrate recognition and catalysis in endo-glycosidases and can inform mutational campaigns aimed to search for more efficient enzymes.</p><p> </p><p><strong>DESCRIPTION OF THE DATASET</strong></p><p>The data is compressed in a .rar file in where we would find the following folders:</p><ol><li>Model1_WT</li><li>Model2_2deoxy2F_lowpH</li><li>Model3_2deoxy2F_neutralpH</li><li>Model4_Glu105Gln_lowpH</li><li>Model5_Glu105Gln_neutralpH</li><li>Model6_Glu105Asp_neutralpH</li><li>Model7_Glu105Ala_lowpH</li><li>Model8_Glu105Ile_lowpH</li><li>Model8_Glu105Ile_lowpH</li><li>Model10_Glu105Ile_neutralpH</li><li>scripts</li></ol><p>Each folder contains the first frame of the production phase of the QM/MM MD simulations in a .pdb format and the representative structures of the whole simulation obtained by clustering in a .nc format.</p><p>In the scripts folder we can find the scripts used to calculate and analyze the QM/MM MD simulations and a README.txt file with their proper descriptions.</p><p> </p><p>More data can be made available upon reasonable request.</p>
Hydrogen-bonded xanthones as potential UV absorbers. The synthesis of xanthones from bio-renewable cardanol utilizing a ceric ammonium sulfate (CAS) mediated oxidation reaction
<p>The synthesis of hydrogen-bonded xanthones using the bio-renewable phenol, cardanol is described. Cardanol was initially converted into hydroxy-benzophenones. These benzophenones were converted into xanthones utilizing an oxidative ceric ammonium sulfate (CAS) mediated reaction. Subsequent ruthenium-mediated late-stage oxidation of the xanthones provided hydrogen-bonded xanthones, which displayed good UVA and UVB absorbing properties.</p>
Data for "Sterics and Hydrogen Bonding Control Stereochemistry and Self-Sorting in BINOL-Based Assemblies"
<p>Written and performed by Andrew Tarzia. <br><br>Please contact me with any issues about this work: andrew.tarzia@gmail.com</p> <p><br>Previously uploaded in 10.5281/zenodo.8432296 and <a href="https://github.com/andrewtarzia/citable_data" rel="noopener noreferrer">https://github.com/andrewtarzia/citable_data</a></p> <p>scripts:</p> <ul> <li>latex_table.py - writes a latex table with relative structure energies from a .csv file with structure energies in au.</li> <li>strain_energy.py - extracts ligands from structures defined in 'cage_dir' (most of the process is hard coded). For each extracted ligand, the script will find its lowest energy conformer in 'low_c_dir' and calculate the strain energy, which is output to a json file for each structure.</li> <li>strain_energy_dft.py - same as strain_energy.py, however the ligand energies are read in from low_e_dft_spe.csv (pre calculated at DFT level).</li> </ul> <p> </p> <p>directories:</p> <ul> <li>./ : main directory contains: <ul> <li>python scripts <ul> <li>these use an outdated code base: <a href="https://github.com/andrewtarzia/atools">https://github.com/andrewtarzia/atools</a> - if you have issues, contact me</li> </ul> </li> <li>initial structures "name".xyz</li> <li>.csv files with extracted structure energies <ul> <li>low_e_dft_spe.csv - energies of free and extracted ligands at DFT level, used by strain_energy_dft.py to calculate strain energies.</li> <li>spe1_energies.csv - energies of all structures after xtb optimisation at def2-svp level</li> <li>spe2_energies.csv - energies of all structures after DFT (def2-svp) optimisation at def2-tzvp level</li> <li>xtb_energies.csv - energies of all structures after xtb optimisation at GFN2-xTB level </li> </ul> </li> <li>extracted ligand structures (NA is number of atoms in ligand): <ul> <li>"name"_xtb_sgNA....mol -> from the xtb optimised structure</li> <li>"name"_xtb_dft_sgNA....mol -> from the xtb optimised structure</li> </ul> </li> </ul> </li> <li>./xtb1_opts : contains input and output structures for GFN2-xTB optimisations</li> <li>./orca_spe1 : contains input and output SPE calculations of xtb optimised structures at Def2-SVP level</li> <li>./orca_opt : contains input and output structures of DFT optimisation of xtb optimised structures at Def2-SVP level </li> <li>./orca_spe2 : contains input and output SPE calculations of DFT optimised structures at Def2-TZVP level</li> <li>./low_e_bb_confs : contains input and output of lowest energy conformer search of free ligands (binolA, binolB, longC, longD; names match those in the paper) <ul> <li>cr_*/ directories contain input and output of CREST conformer searches -- produces "name"_opt.mol/.xyz in</li> </ul> </li> <li>./low_e_bb_confs <ul> <li>dft_opt/ directory contains input and output of DFT optimisation of lowest energy conformers from CREST -- produces "name"_dopt.mol/.xyz in ./low_e_bb_confs</li> </ul> </li> <li>./low_dft_spe : contains input and output SPE calculations of DFT optimised lowest energy conformers of ligand structures (binolA, binolB, longC, longD) and extracted ligand structures at Def2-TZVP level</li> </ul>
Data for "Water Sorption Controls Extreme Single-Crystal-to-Single Crystal Molecular Reorganization in Hydrogen Bonded Organic Frameworks"
<p>Paper DOI: <a href="https://doi.org/10.1002/chem.202201929">10.1002/chem.202201929</a></p> <p>Previously uploaded in 10.5281/zenodo.8432296 and <a href="https://github.com/andrewtarzia/citable_data" rel="noopener noreferrer">https://github.com/andrewtarzia/citable_data</a></p> <p>Each .out file is generated from zeo_runs_production.py, which includes the output from Zeo++ for the probe radius and sampling value in the file name.</p> <p>zeo_runs.py tests sampling values to check for convergence, those output files are not included here.</p> <p>Each python script includes the list of CIFs to run the analysis on. Only the CIFs shown in the manuscript are included here, as testing was done on a series to see the effect of symmetry, disorder and cell size.</p>
Simultaneous hydrogen bonds with different binding modes: the acceptor "rules" but the donor "chooses"
<p>Supporting information for the paper: Simultaneous hydrogen bonds with different binding modes: the acceptor “rules” but the donor “chooses</p>
Dataset for the article "Polarizable Embedding Potentials through Molecular Fractionation with Conjugate Caps including Hydrogen Bonds"
<p>This dataset contains additional material related to the article: "Polarizable Embedding Potentials through Molecular Fractionation with Conjugate Caps including Hydrogen Bonds". The published article can be found at <a href="https://doi.org/10.1021/acs.jctc.3c00613">https://doi.org/10.1021/acs.jctc.3c00613</a>. A preprint is freely available at <a href="https://doi.org/10.26434/chemrxiv-2023-vb01m-v2">https://doi.org/10.26434/chemrxiv-2023-vb01m-v2</a>. Each folder contains a <em>Readme.md</em> for further description.</p>
Hydrogen Bonding Bottlebrush Networks: Self-healing Materials from Super-soft to Stiff
Open the record for dataset details and reuse information.
Acid dissociation constants in selected dipolar non-hydrogen-bond-donor solvents
<p>This compilation includes more than <strong>9000</strong> p<em>K</em><sub>a</sub><strong> </strong>values determined in seven dipolar non-hydrogen-bond-donor solvents (dimethyl sulfoxide, acetonitrile, <em>N,N</em>-dimethylformamide, pyridine, acetone, propylene carbonate, tetrahydrofuran) for close to <strong>5000</strong> acids collected from around <strong>800</strong> original works published during the last sixty years. The data have been critically evaluated on the basis of defined quality criteria and depending on situation, kept as they were originally published, marked as doubtful/unreliable (2700 values) or corrected (around 2400 values).</p> <p>To enable automated processing and mining, the data are presented as an XLSX file, together with structural codes, compound class qualifiers and comments.</p> <p><strong>All citations should refer to the manuscript: </strong></p> <blockquote> <p>Ivo Leito, Ivari Kaljurand, Mare Piirsalu, Sofja Tshepelevitsh, Jonathan Wenyuan Zheng, Martí Rosés, Jean-François Gal. Acid Dissociation Constants in Selected Dipolar non-Hydrogen-Bond-Donor Solvents. <em>Pure Appl. Chem</em>. <strong>2025 </strong>https://doi.org/10.1515/pac-2024-0276</p> </blockquote>
Hydrogen-Bonded Organic Frameworks Based on Endless-Stacked Amides for Iodine Capture and Detection
<p>Raw data of </p>
Ionic Hydrogen Bond-Assisted Catalytic Construction of Nitrogen Stereogenic Center via Formal Desymmetrization of Remote Diols
<p><span>The folder /DFT_structures/ contains the DFT-optimized geometries (in .xyz format together with the gas-phase energy, E) accompanying the paper</span></p> <p><span>"Ionic Hydrogen Bond-Assisted Catalytic Construction of Nitrogen Stereogenic Center via Formal Desymmetrization of Remote Diols"</span></p> <p><span>Where conformers occur, they are always named from the lowest Gibbs energy to the highest in ascending order from c1 (sometimes omitted), c2, c3, .., etc.</span></p> <p><span>The folder /xTB_structures/ contain structures crest_best_major_full_F.xyz and crest_best_minor_full_F.xyz, which are the most stable GFN2-xTB optimized structures from CREST conformational sampling while constraining the model system with chiral phosphoric acid C-3 added to the system.</span></p>
Semiconductor Porous Hydrogen-Bonded Organic Frameworks Based on Tetrathiafulvalene Derivatives
<p>Relevant data for publication with DOI:</p> <table> <tbody> <tr> <td><a href="https://doi.org/10.1021/jacs.1c07802"><span>https://doi.org/10.1021/jacs.1c07802</span></a></td> </tr> </tbody> </table>
Quantum alchemy beyond singlets: Bonding in diatomic molecules with hydrogen
<p>Data at the time of submission.</p>
From Networked to Isolated: Observing Water Hydrogen Bonds in Concentrated Electrolytes with Two Dimensional Infrared Spectroscopy
<p>The files contain the data that are shown in the figures of the Main Text and of the Supplementary Materials of the research article:</p> <p>From Networked to Isolated: Observing Water Hydrogen Bonds in Concentrated Electrolytes with Two Dimensional Infrared Spectroscopy</p> <p>Nicholas H. C. Lewis, Bogdan Dereka, Yong Zhang, Edward J. Maginn, and Andrei Tokmakoff</p> <p>J. Phys. Chem. B, (2022)</p>
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