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1,805 results for “Molecules”
Bioactivity of small-molecule compounds against Haemonchus contortus
<div> <div> <div> <p>This dataset of small-molecule compounds and their effects on <em>H. contortus </em>was assembled based on the results obtained from screening two compound libraries (Medicines for Malaria Venture Pathogen Box, Compounds Australia Open Scaffolds set) to assess the effect of compounds on the motility of exsheathed third-stage larvae (xL3) of <em>H. contortus </em>(Preston et al., 2016, 2017). Additionally, select literature data were included to augment the in-house generated data.</p> </div> </div> </div>
AIMEl-DB: Atomic Properties for 44K small organic molecules
<h3>AIMEl-DB: Atomic Properties for 44K small organic molecules</h3> <p>This dataset comprises atomic properties of 44K (44 470) molecules selected from the QM9 database. The file names are based on the same indexing system used for QM9. </p> <p>This dataset includes four types of files:</p> <ul> <li><strong>.com Files<br></strong>Input files for Gaussian 16. Simple-point energy calculations were carried out using the keywords<br><code># B3LYP/6-31G(2df,p) scf=(maxcycle=9999) nosymm output=wfx</code><br><br></li> <li><strong>.log Files<br></strong>Output files from Gaussian 16 calculation with the aformentioned parameters.<br><br></li> <li><strong>.wfx Files<br></strong>Wave function files from Gaussian 16 calculation. These files were used as inputs for QTAIM calculations. <br><br></li> <li><strong>.sumviz Files<br></strong>Output file from AIMAll software. The keywords used for the calculations were<br><code>aimqb -nogui -scp=false -nproc=8 -naat=4 input.wfx</code><br>Each .sumviz file contains more than 30 properties based on the Quantum Theory of Atoms in Molecules (QTAIM).<br><br></li> <li><strong>.csv Files<br></strong>These files contain the results of a in-house treament of .sumviz data. They cointain two calculated atomic properties:<br><br> <ol> <li>Total magnitude of the dipole moment, |mu|</li> <li>Total magnitude of the quadrupole moment, |Q|</li> </ol> </li> </ul> <p> and two extracted atomic properties:<br><br> 3. Electronic Population, N<br> 4. Atomic Energy, E</p> <p> </p> <p>The <code>aimel_merged_44k.csv</code> presents the concatenation of the 44 470 <strong>csv Files. </strong></p> <p>Additionaly, the <code>aimel_merged_38k.csv</code> presents the concatenation of the 38 876 <strong>csv Files. </strong>This file corresponds to the version 1.0 of the dataset. </p> <p><br>If you find this dataset useful, please cite the original paper:</p> <p>Meza-González, B., Ramírez-Palma, D.I., Carpio-Martínez, P. <em>et al.</em> Quantum Topological Atomic Properties of 44K molecules. <em>Sci Data</em> <strong>11</strong>, 945 (2024). https://doi.org/10.1038/s41597-024-03723-0</p> <p> </p> <p> </p>
Microbiome homeostasis on rice leaves is regulated by a precursor molecule of lignin biosynthesis
<p>A GWAS pipeline for identification of the loci associated with >3000 bacterial species (Selected from over 6000 bacterial species of rice Phyllosphere).</p><p> </p>
Accelerated lignocellulosic molecule adsorption structure determination dataset
<p>Dataset containing all structures from the accelerated structure search for lignocellulosic molecules. Part of the data corresponds to DFT data, while the largest portion of structures correspond to data acquired using a machine learned interatomic potential (NequIP) trained on the former. The energies attached to each structure are atomisation energies. Contains both isolated adsorbates and adsorption structures. The dataset also contains configuration files for the NequIP training. </p>
Aquamarine: Quantum-Mechanical Exploration of Conformers and Solvent Effects in Large Drug-like Molecules
<p>Open challenges in computational drug design include the understanding and accurate description of solvent effects as well as collective dispersion interactions for realistic drug-like molecules. Both interactions profoundly influence the conformational stability of drug molecules and, consequently, the determination of other important quantum-mechanical (QM) observables. In this context, we here introduce the Aquamarine (AQM) dataset -- an extensive QM dataset that contains the structural and electronic information -- of 59,786 low-and high-energy conformers of 1,653 molecules containing up to 54 non-hydrogen atoms (including C, N, O, F, P, S and Cl). To gain insights into the solvent effects, we have carried out QM calculations of structures and properties in gas phase and in an aqueous solution modeled with implicit solvent. AQM contains over 40 global (molecular) and local (atom-in-a-molecule) physicochemical properties (including ground-state and response properties) per molecular structure computed at the tightly converged PBE0+MBD level of theory for gas-phase molecules, whereas PBE0+MBD supplemented with the modified Poisson-Boltzmann (MPB) model of water was used for solvated molecules. By treating both molecule-solvent and dispersion interactions, the AQM dataset can help understand the impact of both interactions in structure-property and property-property relationships of realistic drug-like molecules. Therefore, we propose the AQM dataset as a benchmark for current state-of-the-art machine learning methods for property prediction as well as for the <em>de novo</em> generation of large and flexible (solvated) molecules with pharmaceutical and biological relevance.</p>
Dataset supporting the paper "Transmitting Stepwise Rotation among Three Molecule-Gear on the Au(111) Surface. J.Phys.Chem.Lett. 11 6892 (2020)"
<p>Dataset corresponding to figure 3 of the paper "Transmitting Stepwise Rotation among Three Molecule-Gear on the Au(111) Surface. J.Phys.Chem.Lett. 11 6892 (2020), DOI: <a href="https://doi.org/10.1021/acs.jpclett.0c01747">10.1021/acs.jpclett.0c01747</a>"</p> <p>List of files:<br> There are two folders corresponding to brominated and debrominated structures:</p> <ul> <li>.siesta files: STM simulated images in WsXM format (<a href="http://www.wsxm.eu/">http://www.wsxm.eu/</a>) simulated using STMpw (<a href="https://doi.org/10.5281/zenodo.3581159">https://doi.org/10.5281/zenodo.3581159</a>).</li> <li>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>)</li> </ul>
Dataset supporting the paper "Doublet-Singlet-Doublet Transition in a Single Organic Molecule Magnet On-Surface Constructed with up to 3 Aluminum Atoms. Nano Letters 21, 8317 (2021)"
<p>Dataset corresponding to theoretical calculations in the paper "Doublet-Singlet-Doublet Transition in a Single Organic Molecule Magnet On-Surface Constructed with up to 3 Aluminum Atoms" Nano Letters 21, 8317 (2021), <a href="https://doi.org/10.1021/acs.nanolett.1c02881">https://doi.org/10.1021/acs.nanolett.1c02881</a></p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <ul> <li>.siesta files: STM images in WsXM format (http://www.wsxm.eu/) simulated using STMpw (<a href="https://doi.org/10.5281/zenodo.3581159">https://doi.org/10.5281/zenodo.3581159</a>).</li> <li>CONTCAR and POSCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>).</li> <li>.agr: grace files (<a href="https://plasma-gate.weizmann.ac.il/Grace/">https://plasma-gate.weizmann.ac.il/Grace/</a>).<br> </li> </ul>
A setup for studies of photoelectron circular dichroism from chiral molecules in aqueous solution - data
<p>Data set pertaining to the article "A setup for studies of photoelectron circular dichroism from chiral molecules in aqueous solution" | Review of Scientific Instruments, aip.org, doi: <a href="https://doi.org/10.1063/5.0072346">10.1063/5.0072346</a> .</p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus standard v2022.06, see<br> https://www.nexusformat.org/<br> https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.html</p> <p>NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br> * nexpy (distributed with python)<br> * https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>Files with extension .asc are ascii-files.</p> <p><br> The following files are provided:<br> fig-fenchone-rsi.asc : numeric form of traces shown in Fig. 7<br> fig-lfenchone-roi-rsi.asc : numeric form of traces shown in Fig. 8</p> <p>data relevant for Fig.s 7,8 and Table 1<br> gas-phase_1R-fenchone.h5 : data set of gas phase photoemission data for (1R,4S)-(−)-fenchone<br> gas-phase_1S-fenchone.h5 : data set of gas phase photoemission data for (1S,4R)-(+)-fenchone<br> liquid-phase_1R-fenchone.h5 : data set of liqiud phase photoemission data for (1R,4S)-(−)-fenchone<br> liquid-phase_1S-fenchone.h5 : data set of liquid phase photoemission data for (1S,4R)-(+)-fenchone</p> <p>data relevant for Fig. 9<br> gas-liq_1R-fenchone.h5 : data set for photoemission of (1R,4S)-(−)-fenchone (biased and grounded)</p> <p>data relevant for Fig. 10<br> flatjet_fig10a.h5<br> flatjet_fig10b.h5<br> flatjet_fig10c.h5</p> <p>Contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p>
Datasets for "Single-molecule and super-resolved imaging deciphers membrane behaviour of onco-immunogenic CCR5"
<p><strong>Flow cytometry</strong></p> <p>Modality / instrument: <em>Flow cytometer</em> <em>(CytoFLEX LX, Beckman Coulter)</em></p> <p>File format:<em> FCS + XIT (CytExpert, Beckman Coulter).</em></p> <p>Samples and acquisitions:</p> <p>Fluorescent fusions in live Chinese Hamster ovary (CHO) cells.</p> <table> <tbody> <tr> <td> <p><em>File</em></p> </td> <td> <p><em>Cell line</em></p> </td> <td> <p><em>Runs</em></p> </td> <td> <p><em>Cells counted</em></p> </td> </tr> <tr> <td> <p>CONTROL.fcs</p> </td> <td> <p>CHO wild-type</p> </td> <td> <p>1</p> </td> <td> <p>7000</p> </td> </tr> <tr> <td> <p>GFP-CCR5.fcs</p> </td> <td> <p>CHO-GFP-CCR5</p> </td> <td> <p>1</p> </td> <td> <p>7000</p> </td> </tr> <tr> <td> <p>Exp_20220916_1_GFP.xit</p> </td> <td> <p>N/A - metadata</p> </td> </tr> </tbody> </table> <p>Approx. size 6 MB</p> <p> </p> <p><strong>PaTCH microscopy images</strong></p> <p>Imaging modality / instrument: <em>Brightfield</em> + <em>PaTCH fluorescence microscopy</em></p> <p>Image format:<em> OME TIFF (16 bit) + MicroManager metadata files</em></p> <p>Microscope settings:</p> <p><em>488 nm triggered excitation; split red/green detection, cropped to green (GFP) channel only; 10 ms/frame laser exposure; 13.5 ms/frame-to-frame; 53 nm/px. Photometrics Prime95b CMOS.</em></p> <p>Samples and acquisitions:</p> <p>Fluorescent fusions of GFP-CCR5 receptor in live CHO cells imaged with and without 100 nM CCL5 ligand. Each subfolder corresponds to a field of view and contains one brightfield and one PaTCH acquisition of the same cell.</p> <table> <tbody> <tr> <td> <p>Folder</p> </td> <td> <p>Condition</p> </td> <td> <p>Fields of view</p> </td> </tr> <tr> <td> <p>AC6 CONTROL sc</p> </td> <td> <p>CCL5-</p> </td> <td> <p>11</p> </td> </tr> <tr> <td> <p>AC6 CCL5 sc</p> </td> <td> <p>CCL5+ (100 nM)</p> </td> <td> <p>10</p> </td> </tr> </tbody> </table> <p>Approx. size before compression: 14 GB</p> <p> </p> <p><strong>Structured illumination microscopy - volumetric stacks</strong></p> <p>Imaging modality / instrument: <em>SIM fluorescence microscopy (custom setup at NPL based on Olympus IX71)</em></p> <p>Image format:<em> OME TIFF (16 bit) with intrinsic metadata (voxel size)</em></p> <p>Microscope settings: <em>638 nm excitation; 60x/1.3 NA; Flash 4.0, Hamamatsu Photonics. For additional details see the reference below (Hunter et al, bioRxiv).</em></p> <p>Samples and acquisitions:</p> <p>Dylight 650-MC-5 labeled CCR5 receptor in fixed CHO-CCR5 cells, imaged with and without 100 nM CCL5 ligand. Each acquisition is of a unique field of view and contains one SIM reconstruction as an XYZ volumetric stack. ‘Basal membrane’ acquisitions consist of 5 slices at 200 nm z-intervals across the range of the basal membrane. ‘Whole cell' acquisitions are made up of 7 slices with 500 nm z-interval ranging from just below the basal membrane to just above the apical membrane. </p> <table> <tbody> <tr> <td>Folder</td> <td>Subfolder/condition</td> <td>Fields of view</td> </tr> <tr> <td>Basal membrane</td> <td>CCL5-</td> <td>5</td> </tr> <tr> <td>Basal membrane</td> <td>CCL5+ (100 nM)</td> <td>6</td> </tr> <tr> <td>Whole cells</td> <td>CCL5-</td> <td>5</td> </tr> <tr> <td>Whole cells</td> <td>CCL5+ (100 nM)</td> <td>8</td> </tr> </tbody> </table> <p>Approx. size before compression: 300 MB</p>
Experimental data for "Yu-Shiba-Rusinov bands in a self-assembled kagome lattice of magnetic molecules"
<p>Here, we provide all original data used in the manuscript "Yu-Shiba-Rusinov bands in a self-assembled kagome lattice of magnetic molecules"</p> <p>We acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through projects 277101999 (CRC 183, project C03) and FR2726/10-1.</p>
Laboratory simulations of benzene oxidation and formation of highly oxygenated organic molecules (HOM)
<p>This dataset supplements the following manuscript:<br> Garmash, O., Rissanen, M. P., Pullinen, I., Schmitt, S., Kausiala, O., Tillmann, R., Percival, C., Bannan, T. J., Priestley, M., Hallquist, Å. M., Kleist, E., Kiendler-Scharr, A., Hallquist, M., Berndt, T., McFiggans, G., Wildt, J., Mentel, T., and Ehn, M.: Multi-generation OH oxidation as a source for highly oxygenated organic molecules from aromatics, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-582, in review, 2019.<br> It presents data from Table 1, Tables S1-S4 and Figures 5, A1 and A2, including model input data.</p>
GFN2-xTB structures of iCOM adsorbed on a cluster model of water molecules derived from a periodic model of crystalline ice
<p>This dataset contains the atomic coordinates in the <a href="http://www.moldraw.unito.it/">.</a>xyz format of the GFN2-xTB optimized structures of 20 iCOMs adsorbed at the surface of a cluster of 84 water molecules mimicking the periodic model of crystalline water icy grain as described by Ferrero, S.; Zamirri, L., Ceccarelli, C.; Witzel, A.; Rimola, A.; Ugliengo, P. ApJ, (2020) 904:11. For all considered structures we also provided a specific file in the Gaussian format with the computed harmonic frequencies. Each file can be easily converted in input for the variety of quantum mechanical programs, like VASP, QE, Gaussian 16 etc.</p> <p> </p> <p> </p>
Clinically approved small molecule antibiotics since 2010
<p>Properties of clinically approved small molecule antibiotics since 2010 are summarized.</p> <p>Properties include: Name Year approved Origin Mechanism of action Indication Administration Spectrum Protein binding Resistance Smiles Molweight cLogP cLogS H-Acceptors H-Donors Druglikeness DrugScore Total Molweight Monoisotopic Mass Total Surface Area Relative PSA Polar Surface Area LE from Molweight LLE from Molweight LELP from Molweight Shape Index Molecular Flexibility Molecular Complexity Structure of Smiles [idcode]</p> <p> </p> <p>Propeties in rows B to I were retrieved from the references cited in the dataset. <br> Properties in rows K - AC were calculated with DataWarrior. https://openmolecules.org/datawarrior/index.html</p>
Dataset supporting the paper "Thioetherification of Br-Mercaptobiphenyl Molecules on Au(111). Nano Letters 23, 1350 (2023)"
<p>Dataset corresponding to theoretical calculations in the paper "Thioetherification of Br-Mercaptobiphenyl Molecules on Au(111). Nano Letters 23, 1350 (2023)" DOI: <a href="https://doi.org/10.1021/acs.nanolett.2c04619">https://doi.org/10.1021/acs.nanolett.2c04619</a></p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <ul> <li>.dat files: STM images simulated using STMpw (<a href="https://doi.org/10.5281/zenodo.3581159">https://doi.org/10.5281/zenodo.3581159</a>). They can be processed with the programs and scripts in the Utils directory of STMpw.</li> <li>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>).</li> <li>.agr: grace files (<a href="https://plasma-gate.weizmann.ac.il/Grace/">https://plasma-gate.weizmann.ac.il/Grace/</a>).</li> </ul>
Hybrid quantum-classical machine learning for generative chemistry and drug design: Generated molecules
<p>Deep generative chemistry models emerge as powerful tools to expedite drug discovery. How- ever, the immense size and complexity of the structural space of all possible drug-like molecules pose significant obstacles, which could be overcome with hybrid architectures combining quantum computers with deep classical networks. As the first step toward this goal, we built a compact discrete variational autoencoder (DVAE) with a Restricted Boltzmann Machine (RBM) of reduced size in its latent layer. The size of the proposed model was small enough to fit on a state-of-the-art D-Wave quantum annealer and allowed training on a subset of the ChEMBL dataset of biologically active compounds. Finally, we generated 2331 novel chemical structures with medicinal chemistry and synthetic accessibility properties in the ranges typical for molecules from ChEMBL. The pre- sented results demonstrate the feasibility of using already existing or soon-to-be-available quantum computing devices as testbeds for future drug discovery applications.</p>
Single-molecule DNA methylation patterns of full-length human-specific LINE-1 (L1HS) retrotransposons in a panel of cell lines.
<p>We used bs-ATLAS-seq to comprehensively map the genomic location and assess the DNA methylation status of full-length human-specific LINE-1 elements (L1HS). The approach capture region 1-210 of L1HS elements, which corresponds to the most 5' end of its promoter sequence. This was performed in a panel of 12 human primary or transformed cell lines (BJ, IMR90, MRC5, H1, K562, HCT116, HeLa S3, HepG2, MCF7, HEK-293, HEK-293T, 2102Ep), many being shared with the encode project.</p> <p>These datasets provide a visualization for DNA methylation patterns at the single molecule level for each L1HS loci.</p>
Super-Resolved FRET Imaging by Confocal Fluorescence-Lifetime Single-Molecule Localization Microscopy
<p>FRET-based methods are a special tool for detecting interactions between (bio)molecules and their immediate environment. The spatial distribution of molecular interactions and functional states can be seen using FLIM (Fluorescence Lifetime IMaging) and FRET imaging. The spatial information, accuracy, and dynamic range of the observed signals are, however, constrained by the fact that conventional FLIM and FRET imaging only provides average information over an ensemble of molecules within a diffraction-limited volume. On the other hand, conventional Single Molecule Localization Microscopy (SMLM) relies on highly sensitive multi-pixel detectors (e.g. sCMOS or EM-CCD) whose time resolution is not suitable for fluorescence lifetime measurements.</p> <p>Here, we demonstrate a method for obtaining super-resolved FRET imaging using confocal fluorescence-lifetime single-molecule localization microscopy. The proof of concept was carried out using a DNA origami sample for performing DNA-PAINT measurements in combination with fluorogenic probes for reducing background signal. With this method, We show that FRET events separated by sub-diffraction distances can be distinguished based on lifetime modifications.</p>
Single molecule nanotribology: understanding friction and adhesion at a single molecule level
<p>Data presented in the annual conference SAOG2019 (Surface Science and Thin Films Community of Switzerland 2019). </p> <p>Here we discuss the effect of molecular vibrations on its friction properties. This is intended to provide an overview of the results published in the following peer-reviewed freely available papers:<br> Nature Communications 10, 685 (2019). [DOI:10.1038/s41467-019-08531-4 ]<br> Nano Lett. 20, 652 (2020). [DOI: 10.1021/acs.nanolett.9b04418]<br> (Please cite them, if you found this information useful.)</p> <p> </p>
829 drug-like molecules intrinsic solubility dataset
<p>Data collection, curation as well as feature calculation are described in 10.26434/chemrxiv.12746948</p> <p>Please cite the paper if you intend to use the data.</p> <ol> <li>descriptors.csv - File with SMILES index and descriptor data</li> <li>fingerprints.csv - File with SMILES index and fingerprints</li> <li>solubility_data.csv - File with SMILES index, splitting indices and target: logS<sub>0</sub></li> </ol>
Addressable Nanoantennas with Cleared Hotspots for Single-Molecule Detection on a Portable Smartphone Microscope
<p>The advent of highly sensitive photodetectors and the development of photostabilization strategies made detecting the fluorescence of single molecules a routine task in many labs around the world. However, to this day, this process requires cost-intensive optical instruments due to the truly nanoscopic signal of a single emitter. Simplifying single-molecule detection would enable many exciting applications, <em>e.g.</em> in point-of-care diagnostic settings, where costly equipment would be prohibitive. Here, we introduce addressable NanoAntennas with Cleared HOtSpots (NACHOS) that are scaffolded by DNA origami nanostructures and can be specifically tailored for the incorporation of bioassays. Single emitters placed in the NACHOS emit up to 461-fold (average of 89±7-fold) brighter enabling their detection with a customary smartphone camera and an 8-US-dollar objective lens. To prove the applicability of our system, we built a portable, battery-powered smartphone microscope and successfully carried out an exemplary single-molecule detection assay for DNA specific to antibiotic-resistant <em>Klebsiella pneumonia</em> „on the road “. Here we demonstrate the raw data on which our findings based on.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research 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.
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.