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3 results for “Predicted NMR data”

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zenodo36/100

Simulated and experimental data distributed to the CASP13 participants in protein structure prediction assisted with sparse NMR data

<p>All simulated and experimental data&nbsp;distributed to the CASP participants in protein structure prediction assisted with sparse NMR data in CASP13.</p> <p>Also available at&nbsp;http://predictioncenter.org/casp13/results.cgi?view=targets&amp;model=first&amp;tr_type=others&amp;sub_type=N&amp;groups_id=</p> <p>&nbsp;</p>

opencc-by-4.0Sep 2019View details →
zenodo36/100

Supplementary Data for: Benchmark of density functional theory in the prediction of chemical shielding anisotropies for anisotropic NMR based structural elucidation

<p>Additional&nbsp; Data for the research paper titled: Benchmark of density functional theory in the prediction of chemical shielding anisotropies for anisotropic NMR based structural elucidation.</p> <p>Anisotropy Benchmark for Carbon NS372:</p> <ul> <li>Chemical Shielding Tensor for the molecules in the NS372 test set for carbon (XLSX)</li> <li>Coordinate files for the molcules of the NS372 test set that contained carbon (in NS372-Carbon-COORD-Files.zip)</li> </ul> <p>DFT Benchmark for RCSA for Natural Products:</p> <ul> <li>Chemical Shielding Tensor used for the RCSA analysis of 6 Natural Products (CSV)</li> <li>Turbomole Input and Ouput files for the DFT calculation of the natural products (in RAW_DATA_for_RCSA_Analysis.zip)</li> <li>ConArch+ Input and Ouput files for the RCSA analysis using&nbsp;&nbsp;(in RAW_DATA_for_RCSA_Analysis.zip)</li> <li>Coordinate files used for the RCSA analysis&nbsp; (in RAW_DATA_for_RCSA_Analysis.zip)</li> </ul> <p>&nbsp;</p>

opencc-by-4.0Oct 2024View details →
zenodo32/100

Predicted carbon-13 NMR data of Natural Products (PNMRNP)

<p>PNMRNP is an SDF file that reports the structure, properties and classification of 211,280 natural products.</p> <p>The starting point of this work (January 2019) was&nbsp;<a href="https://github.com/oolonek/ISDB/tree/master/Data/dbs">ISDB</a> which contains csv files of the UNPD data base (Gu J et al., PLOS ONE 2013, 8, e62839, doi:10.1371/journal.pone.0062839) and which are packaged with the ISDB mass spectrometry fragmentation database (Allard PM et al., <em>Anal. Chem.</em> 2016, 88, 6, 3317-3323, doi: 10.1021/acs.analchem.5b04804).</p> <p>Starting from InChI strings of compounds, 2D structures with configuration data were produced mainly from the&nbsp;<a href="http://www.rdkit.org">RDKit cheminformatic toolkit</a>.&nbsp;<a href="http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi">Pubchem</a> identifiers were searched for the compounds and used as keys to give names and synonyms to molecules. Carbon atoms in molecular structures were associated to <sup>13</sup>C NMR chemical shift values using&nbsp;<a href="https://nmrshiftdb.nmr.uni-koeln.de">nmrshiftdb2</a>. A three-level classification of compounds according to sub-structure presence is proposed. A compound may be classified as a terpene (level 1) as a sesquiterpene (level 2) and as an eudesmane (level 3).</p> <p>Version 2 of PNMRNP includes the classification of organic compounds according to <a href="http://classyfire.wishartlab.com">ClassyFire</a>.</p> <p>Version 3 of PNMRNP includes <sup>13</sup>C NMR chemical shifts calculated using ACD/Labs C+H NMR Predictors and DB.</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2020View details →

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