Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

21

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

21 results for “Chemical calculations”

Learn how ShareScore rates datasets ↗
zenodo44/100

Intermolecular interactions in G protein-coupled receptor allosteric sites at the membrane interface from molecular dynamics simulations and quantum chemical calculations

<p>Allosteric modulators are called to be promising candidates in G protein-coupled receptor (GPCR) drug development by displaying target selectivity and fewer side effects. Among the allosteric sites known to date, extrahelical cavities represent an uncharacteristic binding location that raises many questions about the ligand interactions and stability; the binding site structure, and how all of these are affected by lipid molecules. In this work, we analyze the dynamics and interactions in the PAR2, C5aR1, and GCGR receptors unbound and bound to allosteric modulators at the receptor-lipid interface using molecular dynamics simulations in three lipid compositions. In addition, we performed quantum chemical calculations to further explore electrostatic interactions and the strength of atom pairwise contacts in the stabilization of the ligand-receptor complexes. We show that besides classical hydrogen bonds weak polar interactions such as O-HC, O-Br, and S-HC contacts and aromatic interactions contribute to the binding of allosteric modulators at the extrahelical sites in the middle of the membrane. The allosteric cavities are open and detectable in various membrane compositions but not always predicted as druggable. &nbsp;The availability of polar atoms for interactions in such cavities can be assessed by water molecules from the simulations. Although ligand-lipid interactions are weak, the lipid tails play a role in sizing and shaping the large part of the allosteric cavity.&nbsp;</p> <p>You will find the following files:</p> <ul> <li>Input files of the equilibration and production protocols of MD simulations (MD_simulations_inputs.zip)</li> <li>Input files and coordinate files of F-SAPT and NCIPLOT calculations (quantum_chemical_coordiates_inputs.zip)</li> </ul>

opencc-by-4.0Jun 2022View details →
zenodo44/100

Rereferenced Chemical Shift files used to select dihedrals for the 5 secondary structure conformations used to calculate Conformational Variability (ConVa).

<p>These Chemical Shifts in this repository were processed with ShiftCrypt (1) and then processed as described in the manuscript.&nbsp;</p> <p>&nbsp;</p> <p>1- Gabriele Orlando, Daniele Raimondi, Luciano Porto Kagami, Wim F Vranken, ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values,&nbsp;<em>Nucleic Acids Research</em>, Volume 48, Issue W1, 02 July 2020, Pages W36&ndash;W40,&nbsp;<a href="https://doi.org/10.1093/nar/gkaa391">https://doi.org/10.1093/nar/gkaa391</a></p>

opencc-by-4.0Apr 2023View details →
zenodo40/100

Electron concentration profiles calculated using different plasma chemical models during solar X-ray flares

<p>The files contain electron concentration <em>Ne</em> profiles during solar X-ray flares&nbsp;that occurred on&nbsp;24-25 October 2013 and 9-11&nbsp;June 2014. The altitude range is 50-90 km.</p> <p>Values of&nbsp;electron concentration were calculated using four-, five- and eight-component models of the ionospheric D-region. Results are obtained&nbsp;on four VLF paths: from European transmitters ICV, FTA, GQD, DHO to Mikhnevo geophysical observatory (55&deg;N 38&deg;E).</p> <p>The data is presented as MATLAB files. Each .mat file&nbsp;contains data and&nbsp;variable &quot;description&quot; with data&#39;s structure information.</p>

opencc-by-4.0Mar 2022View details →
zenodo40/100

Quantum Chemical Calculations for the Reaction of Methoxide with OTP and CL

<p>DFT calculations at the BP/def2-TZVPD level are executed with Turbomole 7.3 and COSMO-RS calculations with COSMOtherm 19.0.4.</p> <p>&nbsp;</p> <p>One folder is used for one molecule which take part in the following reactions.<br> Educt + Nu- -&gt; Intermediate -&gt; Product<br> Charged system:<br> CL &nbsp;+ MeO- -&gt; 2a- -&gt; 3a-<br> OTP + MeO- -&gt; 2b- -&gt; 3b-<br> Neutral system:<br> CL &nbsp;+ MeOH -&gt; 2aH -&gt; 3aH<br> OTP + MeOH -&gt; 2bH -&gt; 3bH</p> <p>Folderstructure:<br> opt: Geometric structure optimization with PBEh-3c, frequency analysis<br> sp-vac: Electronic Structure of the vacuum state<br> sp-sol: Electronic Structure of the solute as ideal conductor<br> sp-cosmors: Calculation of solvation enthalpy</p> <p>Quantum Chemical Data Collection (QCDC) creates data.json<br> Further information can be found here:<br> https://github.com/lucasteiner/qcdc<br> &nbsp;</p>

opencc-by-4.0Jul 2023View details →
zenodo36/100

Data Set "Benchmarking of Vibrational Exciton Models Against Quantum-Chemical Localized-Mode Calculations"

<p>This data set accompanies the publication "Benchmarking of Vibrational Exciton Models Against Quantum-Chemical Localized-Mode Calculations"&nbsp;<br>by Anna M. van Bodegraven, Kevin Focke, Mario Wolter, and Christoph R. Jacob&nbsp;<br>(TU Braunschweig, Germany)&nbsp;</p> <p>It contains the following files:</p> <p><br>Directory '01_AIM':</p> <p>&nbsp; &nbsp; - input (structure.pdb, topol.top and *_input.txt) and results (*.log and<br>&nbsp; &nbsp; &nbsp; Hamiltonian/AtomPos/Dipole/Parameters.txt) from frequency calculations<br>&nbsp; &nbsp; &nbsp; with the Amide-I-maps (AIM) program for six polypeptide test cases<br>&nbsp; &nbsp; &nbsp; (1gpB_310, ala_310, ala_hairpin, ala_helix, ala_strand, and trpzip), &nbsp; &nbsp;<br>&nbsp; &nbsp; &nbsp; each in vacuo or water with three different maps (Jansen, Skinner,&nbsp;<br>&nbsp; &nbsp; &nbsp; Tokmakoff) for 11 snapshots based on a MD run.<br>&nbsp; &nbsp; To rerun the calculations, you will have to change the paths in&nbsp;<br>&nbsp; &nbsp; the *_input.txt files (topfile, trjfile, sourcedir) accordingly<br>&nbsp; &nbsp;&nbsp;<br>Directory '02_SNF':</p> <p>&nbsp; &nbsp; - results (*.dat, *.out, coord and control) from frequency calculations&nbsp;<br>&nbsp; &nbsp; &nbsp; using Turbomole, SNF, and LocVib for six polypeptide test cases<br>&nbsp; &nbsp; &nbsp; (1gpB_310, ala_310, ala_hairpin, ala_helix, ala_strand, and trpzip)&nbsp;<br>&nbsp; &nbsp; &nbsp; each in vacuo or water for snapshots based on an MD run.<br>&nbsp; &nbsp; &nbsp;&nbsp;<br>Directory '03_NMA':</p> <p>&nbsp; &nbsp; - coordinates and results from pyADF for NMA molecules each alligned&nbsp;<br>&nbsp; &nbsp; &nbsp; with a peptide bond from the six polypeptide test cases<br>&nbsp; &nbsp; &nbsp; (1gpB_310, ala_310, ala_hairpin, ala_helix, ala_strand, and trpzip)&nbsp;<br>&nbsp; &nbsp; &nbsp; each in water for 11 snapshots based on a MD run and input&nbsp;<br>&nbsp; &nbsp; &nbsp; (*_input.txt) and results (*.log and Hamiltonian/AtomPos/Dipole/Parameters.txt)&nbsp;<br>&nbsp; &nbsp; &nbsp; from calculations with the Amide-I-maps (AIM) program<br>&nbsp; &nbsp; &nbsp;&nbsp;<br>Directory '04_Handling_Data':</p> <p>&nbsp; &nbsp; - contains all used notebooks to extract the data, plot the figures&nbsp;<br>&nbsp; &nbsp; &nbsp; and calculate the errors<br>&nbsp; &nbsp; - RMSD_Error_vacuo/water.ipynb is used to calculate the overall shifts&nbsp;<br>&nbsp; &nbsp; &nbsp; and generates a map-dependent mean value to shift the frequencies of AIM<br>&nbsp; &nbsp; - Frequencies.ipynb and Couplings.ipynb are used to plot the figures&nbsp;<br>&nbsp; &nbsp; - RMSD_values_vacuo/water.ipynb show the calculations for the statistical&nbsp;<br>&nbsp; &nbsp; &nbsp; analysis<br>&nbsp; &nbsp; To use the notebooks, start with the Dictionary_setup_for_data_for_paper.ipynb&nbsp;<br>&nbsp; &nbsp; to set up the main dictionary from the calculated data</p>

opencc-by-4.0Nov 2024View details →
zenodo36/100

Data for: Alchemical free-energy calculations at quantum-chemical precision

<p><span><span>In the last decade, machine-learned potentials (MLP) have </span><span>demonstrated</span><span> the capability to predict vario</span><span>us</span><span> QM properties learned from&nbsp;</span><span>a set of reference</span><span> QM calculations. </span><span>Accordingly</span><span>,</span><span> hybrid QM/MM simulation</span><span>s </span><span>can be accelerated</span><span> by replacement of </span><span>expensive</span><span> QM calculation</span><span>s</span><span> with </span><span>efficient </span><span>MLP </span><span>energy prediction</span><span>s</span><span>.</span> <span>At the same time</span><span>, alchemical free energy </span><span>perturbation</span><span>s</span><span> (FEP) </span><span>remain</span> <span>un</span><span>ach</span><span>ie</span><span>vable</span><span> at the QM level of theory.</span> <span>In this work</span><span>,</span><span> we extend the capabilities of the Buffer Region Neural Network </span><span>(</span><span>BuRNN</span><span>) </span><span>QM</span><span>/MM</span><span> scheme towards </span><span>FEP</span><span>.</span> <span>BuRNN</span> <span>introduces a buffer region that experiences full electronic polarization by the QM region to minimize artifacts</span> <span>at </span><span>the </span><span>QM/MM interface</span><span>. </span><span>A </span><span>MLP</span> <span>is </span><span>used to </span><span>predict the energies for the QM </span><span>region</span><span> and its interactions with the buffer region</span><span>. Furthermore, </span><span>BuRNN</span> <span>allow</span><span>s</span><span> us to implement </span><span>FEP </span><span>directly into</span> <span>the </span><span>MLP </span><span>H</span><span>amiltonian</span><span>. </span><span>Here</span><span>, </span><span>we describe the alchemical change </span><span>from methanol to methane in water </span><span>at</span><span> the </span><span>MLP</span><span>/MM level as a proof of concept.</span></span><span>&nbsp;</span></p>

opencc-by-4.0Nov 2024View details →
zenodo36/100

Data Set "Accurate quantum-chemical fragmentation calculations for ion–water clusters with the density-based many-body expansion"

<p>This data set accompanies the publication &quot;Accurate quantum-chemical fragmentation calculations for ion&ndash;water clusters with the density-based many-body expansion&quot;</p> <p>It contains:</p> <p>- xyz files of all considered molecular structures.</p> <p>- PyADF input scripts for running the eb-MBE and db-MBE calculations.</p> <p>- raw results data from the eb-MBE and db-MBE calculations</p> <p>- Jupyter notebooks for generating the plots and tables</p>

opencc-by-4.0Sep 2022View details →
zenodo36/100

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&nbsp; 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).&nbsp; 10.1039/C9CP00795D</p>

opencc-by-4.0Dec 2018View details →
zenodo36/100

Data Set "Quantum-chemical calculation of two-dimensional infrared spectra using localized-mode VSCF/VCI"

<p>This data set accompanies the publication &quot;Quantum-chemical calculation of two-dimensional infrared spectra using localized-mode VSCF/VCI&quot;</p> <p>It contains:</p> <p>-&nbsp; xyz files of all considered molecular structures.</p> <p>- Results data from the harmonic and anharmonic vibrational calculations.</p> <p>- Data and code for calculating 2D-IR spectra.</p>

opencc-by-4.0Nov 2022View details →
zenodo32/100

Insights from quantum chemical calculations into inner and outer-sphere complexation of plutonium(IV) by monoamide and carbamide extractants - Dataset

<p>Supplementary information for &quot;Insights from quantum chemical calculations into inner and outer-sphere complexation of plutonium(IV) by monoamide and carbamide extractants&quot;<br> The attached &#39;Pu-inner-outer.zip&#39; unpacks two directories that contains the optimized molecular structures in xyz format.<br> - Inner-sphere/ for the inner-sphere complexes<br> - Outer-sphere/ for the outer-sphere complexes in their geometries I and II<br> &nbsp;</p>

opencc-by-4.0Oct 2020View details →
zenodo32/100

Equilibrium chemical composition of impact-produced hot cloud during isentropic expansion. The initial temperature T0 is 4000 K, the initial pressure P0 is 5, 20, and 80 bar. Calculations are performed using the EQL program. Abundances of considered species are presented in molar fractions.The elemental composition of impact-produced cloud is taken as a mixture of CI chondrite, mare basalts, and ferroan anorthosite with a ratio of 1:25:25 by mass as in Berezhnoy (2013).

<p>Considered species include ions, neutral gas-phase species, and condensates. Ions are written as ...(+) (for example, Al(+)). Condensates (solids and liquids) are written as ...(c) or ...(c;...). Examples of condensates are Al2O3(c) and Al2O3(c; gamma). For species marked in theirs names as (cr, l) in Gurvich et al. (1989) (for example, Al2O3(cr, l)) it is possible to determine a state of matter (liquid or solid). The content of studied species is 0 if the relative molar fraction is less than 1e-21.&nbsp;</p> <p>The elemental composition of impact-produced cloud is taken as a mixture of CI chondrite, mare basalts, and ferroan anorthosite with a ratio of 1:25:25 by mass as in Berezhnoy (2013).&nbsp;&nbsp;</p> <p>Calculations of the equilibrium chemical composition of impact-produced clouds were performed starting from an initial temperature of 4000 K at different initial pressures of 5, 20, and 80 bar, corresponding to entropies equal to 7.2, 5.56, and 4.25 kJ / (kg&times;K), respectively.&nbsp;</p> <p>Berezhnoy, A.A., 2013. Chemistry of impact events on the Moon. Icarus 226, 205-211.</p> <p>Gurvich L.V., Veitz I.V. et al. Thermodynamic properties of individual substances. Fourth edition in 5 volumes. Hemisphere Pub Co. New York-London, 1989.</p>

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

Fig. 5. Linear correlation between the experimental and calculated 13C NMR chemical shifts for 1A and 1B in (±)-hyperzewalsins A D, four pairs of nor-monocyclic polyprenylated acylphloroglucinols with immunosuppressive activity from hypericum przewalskii maxim

Fig. 5. Linear correlation between the experimental and calculated 13C NMR chemical shifts for 1A and 1B.

opennotspecifiedJul 2021View details →
zenodo32/100

Fig. 4 in Dihydro-furanones from Hyptis species: Chemical correlations and DFT-NMR/ECD calculations for stereochemical assignments

Fig. 4. The four most relevant global-minimum energy conformations of 1 modeled in CHCl3 solution accounting for the 78% of the total population.

opennotspecifiedNov 2020View details →
zenodo32/100

Fig. 3. Chemical correlations between 5,6 in Dihydro-furanones from Hyptis species: Chemical correlations and DFT-NMR/ECD calculations for stereochemical assignments

Fig. 3. Chemical correlations between 5,6-dihydro-2H-pyran-2-ones and 2(5H)-furanones. A possible biogenetic correlation is indicated by a dotter arrow.

opennotspecifiedNov 2020View details →
zenodo32/100

Fig. 1. 1H in Dihydro-furanones from Hyptis species: Chemical correlations and DFT-NMR/ECD calculations for stereochemical assignments

Fig. 1. 1H NMR spectral sections of peracetylated montecofuranolide (2). (A) Simulated spectrum using DFT 3J of peracetyl-5′-epi-synrotolide (5) in gas H,H phase with chemical shifts of the experimental spectrum of compound 2 and coupling constants of monticolide A (6) for J ′ ′ 3 -4 proS = 8.7 Hz, J ′ ′ 3 -4 proR = 4 Hz to simulate the multiplicity for H-4′. (B) Fully simulated spectrum obtained by iteration of chemical shifts, 3J, and linewidths of compound 2. (C) ExperiH,H mental spectrum in CDCl3 (400 MHz).

opennotspecifiedNov 2020View details →
dryad28/100

Data from: Accurate geometries for "mountain pass" regions of the Ramachandran plot using quantum chemical calculations

Unusual local arrangements of protein in Ramachandran space is not well represented by standard geometry tools used in either protein structure refinement using simple harmonic geometry restraints or in protein simulations using molecular mechanics force fields. By contrast, quantum chemical computations using small poly-peptide molecular models can predict accurate geometries for any well-defined backbone Ramachandran orientation. For conformations along transition regions – ϕ from -60 to 60° – a very good agreement with representative high-resolution experimental X-ray (≤1.5 Å) protein structures is obtained for both backbone C^{-1}-N-C_{alpha} angle and the nonbonded O^{-1}…C distance, while "standard geometry" leads to the "clashing" of O…C atoms and Amber FF99SB predicts distances too large by about 0.15 Å. These results confirm that quantum chemistry computations add valuable support for detailed analysis of local structural arrangements in proteins, providing improved or missing data for less understood high-energy or unusual regions.

opencc-zeroDec 2017View details →
zenodo28/100

Fig. 4. Experimental and calculated ECD spectra for 1 and 10 in Chemical constituents of Entandrophragma angolense and their anti-inflammatory activity

Fig. 4. Experimental and calculated ECD spectra for 1 and 10.

opennotspecifiedSep 2022View details →
zenodo28/100

Fig. 2 in Dihydro-furanones from Hyptis species: Chemical correlations and DFT-NMR/ECD calculations for stereochemical assignments

Fig. 2. ECD spectra of monticofuranolide (1 in red) and pectinolide O (11 in blue).

opennotspecifiedNov 2020View details →
zenodo28/100

Bulk chemical composition of rock samples used to calculate their seismic velocity at lower crustal conditions

<p>These data are linked to a published study, whose aim is to compare the seismic velocity variations, derived from tomographic models (here the CIFALPS profile in the Alps, derived from Nouibat et al., 2022) and interpreted as rock transformations, with the seismic velocities of field samples. One way to predict seismic velocity at lower crustal conditions is to consider natural rocks as isotropic and to calculate their seismic properties from the relative abundance of mineral phases using their acknowledged properties (Abers and Hacker, 2016). In this process, the bulk chemical composition of the samples constitutes the starting data for this study. The subsequent work is based solely on thermodynamic models (here mainly using Holland and Powel, 1998 database) and the physical properties of the mineral phases (database from Abers and Hacker, 2016).</p>

opencc-by-4.0Sep 2023View details →
dryad28/100

Data from: Accurate geometries for “mountain pass” regions of the Ramachandran plot using quantum chemical calculations

Open the record for dataset details and reuse information.

publicJan 2019View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record