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873 results for “ligands”
Developing a Tryptophan Fluorescence Assay for Screening Ligands against USP5 Zf-UBD
<p>Development of a fluorescence based assay by measuring changes in UV tryptophan fluorescence of USP5 zinc finger ubiquitin binding domain (Zf-UBD) with addition of ligands</p>
Cannabinoid CB2 Receptor Ligands Datasets
<p>Datasets used in the work titled: "<em>A Multiple Classifier System Identifies Novel Cannabinoid CB2 Receptor Ligands</em>"</p> <ul> <li><strong>CB2 Dataset</strong> contains the dataset used by <a href="https://github.com/drordas/D2-MCS">D2-MCS</a> platform to generate Multi-Classifier Systems.</li> <li><strong>Validation Dataset</strong> is a blinded dataset composed by more than 1.8M compounds. It is used to discover potential candidate compounds.</li> </ul>
Zebrafish behavioral profiling identifies ligands, targets, and neurons related to sedation and paradoxical excitation
<p>Anesthetics are generally associated with sedation, but some anesthetics can also increase brain and motor activity — a phenomenon known as paradoxical excitation. Previous studies have identified GABAA receptors as the primary targets of most anesthetic drugs, but how these compounds produce paradoxical excitation is poorly understood. To identify and understand such compounds, we applied a behavior-based drug profiling approach. Here, we show that a subset of central nervous system depressants cause paradoxical excitation in zebrafish. Using this behavior as a readout, we screened thousands of compounds and identified dozens of hits that caused paradoxical excitation. Many hit compounds modulated human GABAA receptors, while others appeared to modulate different neuronal targets, including the human serotonin-6 receptor. Ligands at these receptors generally decreased neuronal activity, but paradoxically increased activity in the caudal hindbrain. Together, these studies identify ligands, targets, and neurons affecting sedation and paradoxical excitation in vivo in zebrafish.</p>
Growth and Purification of Biotinylated USP5 Constructs & Testing ZnF-UBD Ligands in a Displacement Assay
<p>Expression and purification of biotinylated full length (FL) USP5<sup>1-835</sup> and biotinylated zinc finger ubiquitin-binding domain (ZnF-UBD) USP5<sup>171-290 </sup>constructs for the development of a displacement assay. </p>
Do ZnF-UBD ligands bind full length USP5?
<p>A surface plasmon resonance (SPR) assay was used to determine the binding affinities of USP5 zinc finger ubiquitin-binding domain (ZnF-UBD) ligands to full length (FL) USP5<sup>1-835 </sup></p>
Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors - apo and validation MD
<p>Supplementary data of "Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors" paper.</p> <p>This dataset consists of molecular dynamics simulations trajectories and topology of Cruzain, Cathepsin K and Cathepsin L enzymes in it apo form, together with validation simulations. We ran five replicate 100ns simulations on each complex, with randomized initial velocities.</p>
Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors - ICL and IKR complexes MD
<p>Supplementary data of "Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors" paper.</p> <p>This dataset consists of the molecular dynamics simulations trajectory and topology of Cruzain, Cathepsin K and Cathepsin L enzymes in noncovalent and covalent complexes with selective ligand against Cruzain (ICL* and CCL) and Cathepsin K (IKR and CKR). We ran five replicate 100ns simulations on each complex, with randomized initial velocities.</p> <p> </p> <p> </p>
Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors - ICR and ICK complexes MD
<p>Supplementary data of "Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors" paper.</p> <p>This dataset consists of molecular dynamics simulations trajectory and topology of Cruzain, Cathepsin K and Cathepsin L enzymes in noncovalent and covalent complexes with selective ligand against Cruzain (ICR and CCR) and Cathepsin K (ICK and CCK). We ran five replicate 100ns simulations on each complex, with randomized initial velocities.</p>
Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors - Inputs and Analysis
<p>Supplementary data of "Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors" paper.</p> <p>This dataset consists of the parametrized ligand (covalent and noncovalent form of ICR, ICK, ICL, IKR) and complexes files, sample of input files used for Molecular dynamics simulations and analysis procedures, and the raw data of results. </p>
The dataset used in the article "A point cloud graph neural network for protein-ligand binding site prediction"
Open the record for dataset details and reuse information.
A machine learning model reveals expansive downregulation of ligand-receptor interactions enhancing lymphocyte infiltration in melanoma with developed resistance to Immune Checkpoint Blockade
<p>Data repository containing the data to reproduce the results and findings that are published in:</p> <p>Sahni, S., Wang, B., Wu, D. <em>et al.</em> A machine learning model reveals expansive downregulation of ligand-receptor interactions that enhance lymphocyte infiltration in melanoma with developed resistance to immune checkpoint blockade. <em>Nat Commun</em> <strong>15</strong>, 8867 (2024). https://doi.org/10.1038/s41467-024-52555-4</p>
Data Set "Protein-Ligand Interaction Energies from Quantum-Chemical Fragmentation Methods: Upgrading the MFCC-Scheme with Many-Body Contributions"
<p>This data set accompanies the publication "Protein-Ligand Interaction Energies from Quantum-Chemical Fragmentation Methods: Upgrading the MFCC-Scheme with Many-Body Contributions" by Johannes Vornweg and Christoph R. Jacob (TU Braunschweig, Germany) </p> <p>It contains the following files:</p> <p><br>Directory 1_structures:</p> <p> PDB files of all structures used for the test calculations. <br> The PDB files correspond to the protonated structures obtained <br> as described in the main text.</p> <p><br>Directory 02_figure_scripts:</p> <p> Jupyter Notebook for generating all plots included in the manuscript, <br> including raw numerical data.</p> <p><br>Directory 03_input_scripts:</p> <p> - min_congrad.mdp: input file for partial optimization of protonated <br> protein--ligand complexes with Gromacs</p> <p> PyADF input scripts:</p> <p> - sp_single.pyadf: single-point calculations of separate protein and ligand<br> - sp_complex.pyadf: single-point calculation of protein-ligand complex<br> - mfccmbe3.pyadf: MFCC and MFCC-MBE(2) calculations of P-L interaction energy</p> <p> These scripts can be used with PyADF v1.5 (DOI: 10.5281/zenodo.13236550)</p>
Gating residues govern ligand-unbinding kinetics from the buried cavity in HIF2a PAS-B
<p>Representative Pathways for each pathway class for HIF-2a PAS-B unbinding. Trajectories are with water.</p>
Ligand Many-Body Expansion as a General Approach for Accelerating Transition Metal Complex Discovery
<p>Dataset of transition metal complex structures in .xyz file format, computed and predicted energies in comma delimited format, model information in JSON format, and the Mathematica script for uncertainty analysis for associated manuscript.</p>
Growing Malaria Parasites at a Critical Shaking Speed Mimicking Physiological Flow Reveals New Phenotypes for Invasion Ligands, Supporting Information
<p>This repository contains the dataset and analysis scripts associated with the upcoming publication titled <em>Growing malaria parasites at a critical shaking speed that mimics physiological flow conditions reveals new phenotypes for EBA and RH invasion ligands.</em> The repository includes a comprehensive collection of data and scripts used to generate all the plots, along with videos showing how the red blood cells behave in culture media for different shaking speeds in the different shaking vessels. The growth assay data used for this experiment was collected in four batches, labelled GA1 to 4:</p> <ul> <li><strong>GA1</strong>: compares the different knockout lines. </li> <li><strong>GA2</strong>: compares different hematocrits. </li> <li><strong>GA3</strong>: compares different growth vessels.</li> <li><strong>GA4</strong>: contains more repeats of lines from GA1.</li> </ul> <p>This repository offers all necessary resources to replicate the findings, including the complete codebase, raw data, and graphical representations of results. Researchers are encouraged to explore the included notebooks and datasets for detailed insights. Movies S1 to S4 show a top and side view of each type of plate/plask used on an orbital shaker as the shaking speed is increased.</p>
Targeting Plasmodium falciparum chondroitin sulfate a ligand: A highly conserved malaria antigen with potential for pregnancy-associated malaria vaccine development
<p>The dataset represents the details of sera samples collected from participants recruited for a longitudinal study. The sera was used for ELISA <em>in vitro</em> assays. The immunoreactivity of PfCSA-L antigen was assessed with the utilization of the gravidity status of the study participants. The antigen is used by the <em>plasmodium falciparum</em> parasite to adhere to the placenta during pregnancy and causes challenges both to the mother and her fetus.</p> <h5>Variables</h5> <ul> <li> <p>Sample_ID - This is the coded details of the study participant.</p> </li> <li> <p>Mean*od <em>_1st_visit, Mean</em>od <em>_2nd_visit, and Mean</em>od *_3rd_visit - These represent the mean reactivity values for antibody (IgG) to PfCSA-L antigen for antenatal visits 1,2 and 3 respectively.</p> </li> <li> <p>Gravida - Refers to the total number of confirmed pregnancies a female has had, regardless of the outcome of the pregnancy.</p> </li> <li> <p>PCR_Results - these are molecular diagnostic results for <em>Plasmodium falciparum</em> to assess whether the study participants were positive or negative for this species. positive = 1 and negative = 0</p> </li> <li> <p>Gestation..weeks - Refers to how far along the pregnancy is, from the first day of the woman's last menstrual cycle to the delivery</p> </li> <li> <p>Newborn outcome - Describes the health status of the childlren when they were born</p> </li> <li> <p>Gravida_class - Describes the different classes of gravida, such that primigravida means single pregnancy, secundigravida-second pregnancy, and tertigravida-third pregnancy</p> </li> <li> <p>Age - Describes the age of the participants recruited for the study</p> </li> <li> <p>HB_level - Describes the amount of hemoglobin in whole blood expressed in grams per deciliter (g/dl) during<br>enrolment</p> </li> <li> <p>Type of delivery - A spontaneous vaginal delivery (SVD) describes when a pregnant female goes into labor without the use of drugs or techniques to induce labor, and delivers her baby in the normal manner, without forceps, vacuum extraction, or a cesarean section (cs)</p> </li> <li> <p>N/A - Missing values for different variables</p> </li> </ul>
Design of facilitated dissociation enables control over cytokine signaling duration - SMT raw data - unstimulated - calibration beads - long term tracking - labelled ligand
<p>This dataset contains the raw data for the Single-molecule tracking data of the manuscript: "Design of facilitated dissociation enables control over cytokine signaling duration". Presicely, it contains the calibration beads for all imaging experiments, the long term tracking experiments, the experiments with labelled ligand and the unstimulated probes</p>
ligands_top500_data
<p>4jq7蛋白的一千个重组分子在对接后的top500候选化合物(基于kinfraglib九百万分子)</p>
Targeting protein-ligand neosurfaces with a generalizable deep learning tool
<p>Molecular recognition events between proteins drive biological processes in living systems. However, higher levels of mechanistic regulation have emerged, where protein-protein interactions are conditioned to small molecules. Despite recent advances, computational tools for the design of novel chemically-induced protein interactions have remained a challenging task for the field. Here, we present a computational strategy for the design of proteins that target neosurfaces, i.e. surfaces arising from protein-ligand complexes. To do so, we leveraged a geometric deep learning approach based on learned molecular surface representations and experimentally validated binders against three drug-bound protein complexes: Bcl2:Venetoclax, DB3:Progesterone and PDF1:Actinonin. All binders demonstrated high affinities and accurate specificities assessed by mutational and structural characterization. Remarkably, surface fingerprints previously trained only on proteins can be applied to neosurfaces emerging from small molecules, serving as a powerful demonstration of generalizability that is uncommon in other deep learning approaches. We anticipate that the designed chemically-induced protein interactions hold the potential to expand the sensing repertoire and the assembly of new synthetic pathways in engineered cells for innovative drug-controlled cell-based therapies</p>
Molecular Dynamics Trajectories for GPR6 without Ligand (ApoNoLig)
<p>Molecular Dynamics Data for 10.1126/scisignal.ado8741 for publication at Science Signalling</p> <p>Barekatain M., Johansson L.C., Lam J.H. et al Structural Insights into the High Basal Activity and Inverse Agonism of the Orphan Receptor GPR6 Implicated in Parkinson's Disease, Sci Signal. 2024 Dec 3;17(865):eado8741. doi: 10.1126/scisignal.ado8741. Epub 2024 Dec 3.</p> <p>This folder contains the PDB format file ("Topology") and the XTC format file (Trajectories). The timestep in this strided trajectory is 0.1 ns per frame. Periodic boundary condition (pbc) can be restored using VMD's standard pbc commands.</p> <p>Please cite us if you find this data useful!</p>
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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.