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Dataset results
471 results for “Protein targets”
Confocal microscopy data associated with "The conserved aphid saliva chemosensory protein effector Mp10 targets plant AMSH deubiquitinases at cellular membranes to suppress pattern-triggered immunity"
<p><strong>Confocal microscopy data as described in "The conserved aphid saliva chemosensory protein effector Mp10 targets plant AMSH deubiquitinases at cellular membranes to suppress pattern-triggered immunity".</strong></p> <p> </p> <p>Data relate to Figure 2 (“Mp10 interacts with AMSH deubiquitinases in yeast and plants”) involving FLIM-FRET imaging data to determine the interaction between eGFP-tagged <em>Myzus persicae </em>Mp10 and mCherry-tagged <em>Nicotiana benthamiana </em>AMSH proteins in plant cells; and Figure 6 (“Mp10 affects the abundance and localisation of cell-surface receptor-like kinases) involving confocal microscopy showing the effect of Mp10-expression on the localisation of the GFP-tagged FLS2 receptor-kinase protein, and it’s colocalization with RFP-tagged markers of the plasma membrane and the tonoplast in plant cells.</p> <p>Constructs encoding fluorescent protein fusions were transformed into <em>Agrobacterium tumefaciens </em>GV3101, and mixed Agrobacterium cultures were infiltrated into mature leaves of <em>N. benthamiana </em>plants to co-express the desired combinations of proteins. All image data was gathered from lower epidermal leaf cells of infiltrated leaves 2-3 days post infiltration.</p> <p> </p> <p><strong>FLIM-FRET assays.</strong></p> <p>eGFP-tagged Mp10, or eGFP-alone, was co-expressed with mCherry-tagged AMSH proteins, or mCherry fused to aquaeorin in <em>N. benthamiana</em> via agroinfiltration as described above. Lower epidermal cells of leaf sections were imaged 2-3 days after infiltration using a Leica Stellaris 8. Images were captured detecting fluorescence from eGFP (WLL laser, ex.488 nm, em 509-534 nm.) mCherry (lWLL aser, ex. 587 nm em 603-625 nm.) and chlorophyll (WLL laser, ex 587 nm. em 687-712 nm.). Regions of cells showing expression of both eGFP- and mCherry- tagged proteins but lacking chlorophyll were selected for FLIM analysis to avoid bleed through of chlorophyll fluorescence into the eGFP chanel. Fluorescence lifetime data of EGFP were collected from these regions in FLIM mode (WLL laser ex. 488nm, em 525-530 nm.), data were collected at 128x128 resolution until 1000 photons per pixel were collected for the most intense regions of the image. Instrument response function was captured using erythrosine on each day of data collection. FLIM data were analysed using Leica LASX FLIM FCS software. Fluorescence lifetime decay curves of free eGFP control samples were modelled as a 2-component exponential function, and all samples from each experimental set were modelled against the fluorescence lifetime from the corresponding control samples to derive values for fluorescent lifetime and %FRET efficiency for each image collected. %FRET efficiency was mapped to the images and phasor plots were generated for regions with the highest and lowest FRET efficiency, showing that the FRET signal was associated with a clockwise shift on the phasor plot consistent with <em>bona-fide </em>FRET. Full experimental metadata for each image set are included within the .lif files.</p> <p> </p> <p><strong>FLS2-GFP localisation experiments.</strong></p> <p>Confocal microscopy analysis was performed on a Leica TCS SP8X confocal DM6 microscope with a 63x water-immersion objective, using Leica Application Suite X (LAS X) software (3.5.7.23225). eGFP and chlorophyll signals were excited by a 488 nm Argon laser with emission, respectively, at 495–545 nm and 690-710 nm. RFP signal was excited by a 590 nm white light laser (WLL) with emission at 605–650 nm. Full experimental metadata for each image set are included within the .lif files.</p> <p> </p> <p>Leica Image Files (.lif) that contain multiple images including metadata associated with image acquisition and processing.</p> <p> </p> <p>FLIM030823.lif</p> <p>FLIM130724.lif</p> <p>FLIM140623.lif</p> <p>FLIM160623.lif</p> <p>FLIM240523.lif</p> <p>FLIM250523.lif</p> <p>Files include FLIM-FRET data as shown in Figure 2 parts D-L.</p> <p>FLIM-data-files.xlsx includes a description of the individual image filenames, and the combinations of fluorophore imaged in each.</p> <p> </p> <p>Fig6cSlFLS2-gfp_Mp10-RFP.lif</p> <p>Fig6c-SlFLS2-GFP_EV-RFP.lif</p> <p>Correspond to Figure 6 C showing co-expression of RFP-tagged Mp10 (or free RFP control) co-expressed with GFP-tagged FLS2</p> <p> </p> <p>20230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP-3-3-1x.lif</p> <p>20230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP-3-3-3x.lif</p> <p>20230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP-4-2-3x.lif</p> <p>0230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP4-2-1x.lif</p> <p>Correspond to Figure 6 D showing co-expression of FLAG-tagged Mp10 (or free FLAG control) co-expressed with GFP-tagged FLS2 together with RFP-tagged plasma membrane marker Remorin</p> <p> </p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-14-5-1x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-14-5-3x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-16-1-1x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-16-1a-3x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-16-1b-1x.lif</p> <p>Correspond to Figure 6 E showing co-expression of FLAG-tagged Mp10 (or free FLAG control) co-expressed with GFP-tagged FLS2 together with RFP-tagged tonoplast marker SUC4.</p> <p> </p> <p>We are grateful to the John Innes Centre (JIC) Bioimaging Platform for training and technical support</p> <p>This work was funded by UK Research and Innovation (UKRI) Biotechnology and Biological Sciences Research Council (BBSRC) grants to SAH (BB/V008544/1 and BB/N009169/1), Additional Support was provided by the BBSRC Institute Strategy Programmes (BBS/E/J/000PR9797 and BBS/E/JI/230001B) awarded to the John Innes Centre (JIC). The JIC is grant-aided by the John Innes Foundation.</p> <p> </p>
Data for "Machine Learning Scoring Functions for Drug Discovery from Experimental and Computer-generated Protein-Ligand Structures: Towards Per-target Scoring Functions"
<p>Data used in "<em>Machine Learning Scoring Functions for Drug Discovery from Experimental and Computer-generated Protein-Ligand Structures: Towards Per-target Scoring Functions</em>"<br> by F. Pellicani, D. Dal Ben, A. Perali, S. Pilati</p> <p>If you use these data or the python script for your research or other activities, please cite the corresponding journal article.</p> <p> </p> <p>====================</p> <p>Uncompressing the zipped file <em>DataSFUnicam.zip</em> provies the following files and folders:</p> <p><br> <strong>DataSFUnicam/</strong></p> <p> </p> <p> ExperimentalDataPDBFiles/<br> <em>This folder contains 2408 .pdb files of experimental complex structures. The files are named with a univocal code corresponding to the protein-ligand complex.</em></p> <p> </p> <p> ExperimentalDataXLSXFile.xlsx<br> <em>This Excel file reports the experimental protein-ligand chemical information. In the sheet named “Foglio1”, the first column contains the univocal code of the protein-ligand complex, the second column contains the experimentally measured pK_d.</em></p> <p> </p> <p> SyntheticDataPDBFiles/<br> <em>This folder contains the .pdb files of the synthetic complex structures. The .pdb files are grouped in 17 folders according to just as many target proteins. The folders are named after the corresponding protein. Each folder contains the .pdb files for the best position of each protein-ligand pair according to the MOE docking score. The files are named with a univocal code.</em></p> <p> </p> <p> SyntheticDataXLSXFiles/<br> <em> The folder contains 17 Excel files with the chemical information of the synthetic protein-ligand complexes. The files are named after the corresponding target protein. In the sheet named “Foglio1” of each .xlsx file, the first column contains a univocal code of the protein-ligand complex in each conformation, the second column contains an auxiliary numerical code corresponding to the protein-ligand pair, the third column contains the experimentally measured pK_i, and the fourth column contains the docking score provided by the MOE software.</em></p> <p>====================</p> <p>USER GUIDE FOR THE PYTHON SCRIPT</p> <p>Download and uncompress the zipped file "<em>SFUnicam.zip</em>" with a command like "<em>unzip SFUnicam.zip</em>". </p> <p>The following file structure is created:</p> <p><em>SFUnicam/</em></p> <p> <em>ComplexToBePredictedFolder/4ey5_30.pdb <br> MaxAssMatrix.npy<br> my_model<br> devStndSynt.npy<br> mediaSynt.npy<br> UnicamSF13prot.py<br> README.txt</em><br> <br> The subfolder "<em>ComplexToBePredictedFolder/</em>" contains the example PDB file "<em>4ey5_30.pdb</em>".</p> <p>-) To execute the script "<em>UnicamSF13prot.py</em>", Python 3 should be installed with the following libraries and sublibraries:<br> <em>Keras:<br> Regularizers<br> Sequential (keras.models)<br> Conv1D, Dense, MaxPooling1D, GlobalMaxPooling1D, GlobalAveragePooling1D, AveragePooling1D (keras.layers)<br> Adam (keras.optimizers)<br> Numpy</em><br> <em>Tensorflow</em></p> <p>Operation:<br> -) Copy the .pdb file related to the protein-ligand complex whose affinity is to be predicted in the subfolder “<em>ComplexToBePredictedFolder/</em>”.<br> -) Make sure the following files are in the same folder where the python script is:<br> <em>MaxAssMatrix.npy<br> mediaSynt.npy<br> devStndSynt.npy<br> my_model</em><br> -) Run the code using Python 3 with a command like "<em>python3.x UnicamSF13prot.py</em>".<br> -) Enter the name of the protein-ligand PDB file whose affinity is to be predicted (excluding the extension ".pdb").<br> -) Read the predicted affinity from screen.<br> </p> <p> </p>
Dietary Protein and Monocyte/Macrophage Mammalian Target of Rapamycin (mTOR) Signaling
ClinicalTrials.gov study NCT03946774. IPD Sharing: NO. Countries: 1. Publications: 0.
Protein Turnover in Preterm Infants - Feeding of Target Fortified Breast Milk With Different Macronutrient Composition to Improve Growth
ClinicalTrials.gov study NCT04854226. IPD Sharing: NO. Countries: 1. Publications: 0.
The Function of PET Molecular Imaging Targeting Fibroblast Activation Protein in the Hepatobiliary Malignancies
ClinicalTrials.gov study NCT05264688. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Heat Shock Proteins: a Pathogenic Driver and Potential Therapeutic Target in Acute Pancreatitis
ClinicalTrials.gov study NCT03634787. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
A Phase I/II Study of the Tumor-targeting Human L19-IL2 Monoclonal Antibody-cytokine Fusion Protein in Combination With Rituximab in Relapsed or Refractory Diffuse Large B-cell Lymphoma (DLBCL)
ClinicalTrials.gov study NCT02957019. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Phase I/II Dose Escalation Study of the Tumor-targeting Human L19-IL2 Monoclonal Antibody-cytokine Fusion Protein in Combination With Dacarbazine for Patients With Metastatic Melanoma
ClinicalTrials.gov study NCT02076646. IPD Sharing: Not stated. Countries: 2. Publications: 0.
Targeting 18kDa Translocator Protein (TSPO) to Improve Brain Endothelial Cell Function in Cerebral Small Vessel Disease
ClinicalTrials.gov study NCT06643013. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Meeting Protein Targets in Critically Ill Patients
ClinicalTrials.gov study NCT03319836. IPD Sharing: NO. Countries: 1. Publications: 0.
Safety and Immunogenicity of HDT-301 Targeting a SARS-CoV-2 Variant Spike Protein
ClinicalTrials.gov study NCT05132907. IPD Sharing: NO. Countries: 1. Publications: 0.
A Clinical Study Evaluating the Safety, Tolerability, Preliminary Efficacy and Immunogenicity of a Tumor Vaccine Injection Targeting Stressinducible Proteins MICA/B in Combination With the AG Regimen
ClinicalTrials.gov study NCT07231094. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Targeting Leukemic Stem Cell Expressing the IL-1RAP Protein in Chronic Myelogenous Leukemia (CML)
ClinicalTrials.gov study NCT02842320. IPD Sharing: NO. Countries: 1. Publications: 0.
DC Vaccines Targeting HPV16/18 E6/E7 Protein to Regress CINI/CIN2
ClinicalTrials.gov study NCT03870113. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study of the Tumor-targeting Human F16IL2 Monoclonal Antibody-cytokine Fusion Protein in Combination With Very Low-dose Cytarabine in Patients With AML Relapse After Allogeneic Hematopoietic Stem Ce
ClinicalTrials.gov study NCT02957032. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Development of a New Family of HIV Latency Regulators (LRAs) Targeting the Tat Viral Protein
ClinicalTrials.gov study NCT06441123. IPD Sharing: NO. Countries: 1. Publications: 0.
Sarcopenia Prevention With a Targeted Exercise and Protein Supplementation Program
ClinicalTrials.gov study NCT03417531. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Safety and Efficacy Study of HCB101, Fc-fusion Protein Targeting SIRPα-CD47 Pathway, in Solid or Hematological Tumors
ClinicalTrials.gov study NCT05892718. IPD Sharing: Not stated. Countries: 3. Publications: 0.
Validation of the 18 kiloDalton Translocator Protein (TSPO) as a Novel Neuroimmunodulatory Target
ClinicalTrials.gov study NCT03850301. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Reaching Protein Target With SmofKabiven® Extra Nitrogen vs Olimel N9E During the Early Phase of Acute Critical Illness
ClinicalTrials.gov study NCT03992716. IPD Sharing: NO. Countries: 3. Publications: 0.
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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.