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641 results for “Protein interaction”
The dataset used in "A max-margin model for predicting residue-base contacts in protein-RNA interactions"
<p>The dataset used in "A max-margin model for predicting residue-base contacts in protein-RNA interactions"</p>
Identification of protein-protein interaction bridges for multiple sclerosis
<p>Supplementary data for thesis "Identification of protein-protein interaction bridges for multiple sclerosis"</p>
Structural characterization of the protein-material interfacial interactions by using lysine reactivity profiling-mass spectrometry
<p>The exploration of interfacial molecular interactions of protein-material integrations and how material modulate the protein structure and activity are essential to the safety evaluation of biomedical micro/nanomaterials, toxicity estimation and design of nano-drugs, and catalytic activity improvement of bio-inorganic functional hybrids. However, characterizing the interfacial molecular details of protein-micro/nanomaterial hybrids remains a great challenge. Herein, we introduce the protocol of lysine reactivity profiling-mass spectrometry (LRP-MS) strategy for probing the interfacial molecular structures between proteins and micro/nanomaterials. LRP-MS utilizes lysine residues as the endogenous probes to characterize the protein localization orientation, interaction sequence regions, binding sites, and modulated protein structures in the protein-material hybrids, which cannot be achieved by traditional spectroscopy methods. We describe the optimized heavy and light two-step isotope dimethyl labeling strategy for protein-material hybrids under their native and denaturing conditions in sequence. The comparative quantification results of lysine reactivity (referred as NLE) are only dependent on the native microenvironments of lysine local structures. We also highlight other critical steps including protein digestion, elution from materials, data processing, and interfacial structure analysis. The two-step isotope labeling steps need about 5 h, and the whole protocol including digestion, liquid chromatography-tandem mass spectrometry, data processing, and structure analysis needs about 3-5 days.</p>
CTCF protein-protein interactions
<p>A collection of all the interactions between CTCF and other proteins. Data from the literature, as well as the STRING database and the Integrated Interactions Database, were analyzed and merged.</p>
Supporting data for "Recalibration of protein interactions in Martini 3"
<p>Coarse-grained molecular dynamics simulations from "Recalibration of protein interactions in Martini 3". Simulations were run with the Martini 3.0 force field, as well as several modified versions of Martini 3.0 in which the well-depth, ε, in the Lennard-Jones potential between all protein and water beads was rescaled by a factor <em>λ</em><sub>PW</sub>, ε in the Lennard-Jones potential between all protein beads was rescaled by a factor <em>λ</em><sub>PP</sub>, or ε in the Lennard-Jones potential between all protein backbone and water beads was rescaled by a factor <em>λ</em><sub>PW-BB</sub>. The simulation files are organized into one tar file for each rescaling approach. The simulation files are in xtc format, and are accompanied by a structure in gro format that can be used for system topology. There is also a tar file containing the atomistic starting structures used to set up the simulations (in pdb format).</p>
Changing protein-DNA interactions promote ORC binding site exchange during replication origin licensing
<p><strong>Changing protein-DNA interactions promote ORC binding site exchange during replication origin licensing.</strong></p> <p>Zhang, Annie, Massachusetts Institute of Technology, ORCID: 0000-0003-3939-2585</p> <p>DOI: 10.5281/zenodo.7814499</p> <p>Primary publication DOI: <a href="https://doi.org/10.1073/pnas.2305556120">https://doi.org/10.1073/pnas.2305556120</a></p> <p> </p> <p><strong>Folder Structure</strong></p> <p> </p> <p>Source data are organized based on the parent figures from the main text (Figs 1-6). Source data from supplementary figures associated are placed within the associated parent figure folder. All figures, their associated parent figures, and the experiment names from which these figures are derived are summarized in the 'Summary.xlsx' file.</p> <p> </p> <p><strong>File Formats</strong></p> <p><strong> </strong></p> <p>1. Integrated trace files are saved as .dat files.</p> <p> </p> <p>- These trace files are obtained by integrating the fluorescence intensity contained within each DNA spot, or Area of Interest (AOI), over the range of the experimental time frame. They can be read and viewed in Matlab or the Matlab program imscroll, which is publicly available: <a href="https://github.com/gelles-brandeis/CoSMoS_Analysis">https://github.com/gelles-brandeis/CoSMoS_Analysis</a>.</p> <p> </p> <p>- Naming of files:</p> <p>The experiment name is specified at the beginning of the file name.</p> <p>The excitation and emission fields are specified using the following abbreviations.</p> <p>Gex: Green excited (Donor excited)</p> <p>Rex: Red excited (Acceptor excited)</p> <p>GexRex: Green and red excited (Donor and acceptor excited)</p> <p>Gem: Green emission (Donor emission)</p> <p>Rem: Red emission (Acceptor emission)</p> <p> </p> <p> </p> <p>To read the .dat integrated trace files in Matlab the user may type: </p> <p>>>[fn fp] = uigetfile</p> <p>% use the dialog box to mouse click on the appropriate *.dat file, then type:</p> <p>>>eval(['load ' [fp fn] ' -mat'])</p> <p>% This loads an aoifits structure array into the Matlab command environment</p> <p> </p> <p>The integrated trace data is stored in the aoifits.data matrix. A description of the columns is in the aoifits.dataDescription.</p> <p> </p> <p>The first five columns within aoifits.data are the most relevant to view fluorescence emission intensities at individual AOIs over time.</p> <p>Column 1: aoinumber</p> <p>Column 2: framenumber</p> <p>Column 3: amplitude (of fluorescence emission)</p> <p>Column 4: xcenter of the aoi</p> <p>Column 5: ycenter of the aoi</p> <p> </p> <p> </p> <p>2. Time Intervals are stored as excel spreadsheet (.xlsx) files.</p> <p> </p> <p>These files contain the AOI numbers used for analysis and frame numbers that correspond to specific events, such as protein arrival and departure events.</p> <p> </p> <p> </p> <p>3. For experiments with <em>E</em><sub>FRET</sub> analysis performed, <em>E</em><sub>FRET</sub> values are stored as .mat matrix files.</p> <p> </p> <p>Column 1: Time in seconds after protein colocalization with DNA</p> <p>Column 2: <em>E</em><sub>FRET </sub>values</p> <p>Column 3: AOI number</p> <p>Column 4: Frame number</p>
Localization files for "Imaging proteins sensitive to direct fusions using transient peptide-peptide interactions"
<p>Localization csv files for super-resolution images taken and analysed for "Imaging proteins sensitive to direct fusions using transient peptide-peptide interactions". Single localizations were processed using the Peak Fit function of the Fiji (Java 8 2017 release) GDSC SMLM plugin, using a signal strength threshold of 30, a minimum photon threshold of 100, and a precision threshold of 15-30 nm (precision threshold used is indicated in the file name). </p>
Polycystin–1 interacting protein–1 (CU062 ) interacts with the ectodomain of polycystin–1 (PC1)
<p>Videos for Polycystin–1 interacting protein–1 (CU062 ) interacts with the ectodomain of polycystin–1 (PC1) --CELLS</p>
Fig. 2 in Detection of candidate proteins in the indican biosynthetic pathway of Persicaria tinctoria (Polygonum tinctorium) using protein-protein interactions and transcriptome analyses
Fig. 2. Analysis of the protein–protein interaction using co-immunoprecipitation. Cytosolic (a) and microsomal fractions (b) were incubated with an anti-PtIGS antibody bound to the AminoLink Plus Coupling Resin. After elution with an acidic buffer, proteins were separated by SDS-PAGE using a 12.5% acrylamide gel for (a) and 10% for (b). After the samples corresponding to (a) 0.205 and (b) 0.057 g wet weight leaves were analyzed, total proteins were visualized with silver staining. As the control, PtIGS in the samples corresponding to 0.041 and 0.057 g wet weight leaves was also detected with western blotting using the anti-PtIGS antibody. C1–C6 and M1–M10 show the regions that were cut from gels and subjected to MS/MS analysis. The symbols "+" and "-" represent the use of AminoLink Plus Coupling Resins bound with anti-PtIGS antibody and without antibody, respectively.
Fig. 1 in Detection of candidate proteins in the indican biosynthetic pathway of Persicaria tinctoria (Polygonum tinctorium) using protein-protein interactions and transcriptome analyses
Fig. 1. Chemical crosslinking assay in vitro and in vivo. Cytosolic (a) and microsomal (b) fractions and the protoplasts (c) were treated with chemical crosslinkers (BS3 and DSS, respectively). Treated samples were then subjected to SDS-PAGE using a 10% acrylamide gel for (a) and (b) and 7.5% for (c). Proteins that reacted against the anti-PtIGS antibody were detected by western blotting. "I" indicates PtIGS monomer. "II" denotes molecules larger than the monomer.
Fig. 5 in Detection of candidate proteins in the indican biosynthetic pathway of Persicaria tinctoria (Polygonum tinctorium) using protein-protein interactions and transcriptome analyses
Fig. 5. The validation of the expression amount of candidates, which might relate to the indican biosynthesis pathway, by qRT-PCR. a, Indican synthase (PtIGS) and the degradation enzyme (PtBGL); b, indole synthesis-related proteins; c, proteins that might relate to the indole oxidation; d, UDP-glucose biosynthesis enzymes and transport proteins that might relate to the indican biosynthesis pathway. Each error bar shows the standard error. The detailed values of (a) and (b) are indicated in Supplementary Table 4S. Those values of (c) and (d) are showed in Tables 4 and 5, respectively.
OPTICS: an interactive online platform for photosensory and bio-functional proteins in optogenetic systems
<p>The cutting-edge technology of optogenetics opens to new ideas for control of cellular bio-functional proteins (CPs) using optogenetic tools (OTs) in spatial and temporal. Over the past decade, hundreds of optogenetic systems (OSs) have been constructed for various applications from living cells to freely moving organisms. In this work, a new database named OPTICS (an interactive online platform for photosensory and bio-functional proteins in optogenetic systems) was thus introduced. Our OPTICS is unique in (i) systematically describing diverse OSs from the perspective of photoreceptor-based classification and mechanism of action; (ii) featuring the detailed biophysical properties and functional data of OSs; (iii) providing the interaction between OT and CP of each OS refers to distinct applications in research, diagnosis, and therapy; and (iv) enabling light response property-based search against all OSs in the database. Since the information of OSs is essential for design of optogenetic controls, the comprehensive data provided in OPTICS lay a solid foundation for the future development of novel OSs. The OPTICS is freely accessible at <a href="https://idrblab.org/optics/">https://idrblab.org/optics/</a>.</p>
Role of Piwi-protein Interacting RNA, miRNA-194 and Amino Acids in Patients With Prostate Cancer
ClinicalTrials.gov study NCT04835454. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Modelling the Interaction Between Rationally-designed Synthetic Model Viral Protein Immunogens
ClinicalTrials.gov study NCT03816137. IPD Sharing: YES. Countries: 1. Publications: 1.
Drug-drug Interaction Study Using Rosuvastatin as a Breast Cancer Resistant Protein (Efflux Transporter), Organic Anion-transporting Polypeptide (OATP)1B1, and OATP1B3 (Uptake Transporters) Probe Subs
ClinicalTrials.gov study NCT02671097. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Interactive Effects of an Isocaloric High-protein Diet and Resistance Exercise in Untrained Overweight Young Men
ClinicalTrials.gov study NCT01714700. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: The geometric framework for nutrition reveals interactions between protein and carbohydrate during larval growth in honey bees
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Data from: Epistatic interaction of the melanocortin 1 receptor and agouti signaling protein genes modulates wool color in the Brazilian Creole sheep
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Electrostatic interactions contribute to the control of intramolecular thiol–disulfide isomerization in a protein
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Data from: Positive selection within a diatom species acts on putative protein interactions and transcriptional regulation
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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.