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.
192
datasets available to search
ShareScore release 0.9.0
Dataset results
192 results for “glycosylation”
Diffraction images used to solve the structures published in the article "Structure of human endo-α-1,2-mannosidase (MANEA), an antiviral host-glycosylation target"
<p>Raw diffraction images used for generating the structures published in the article "Structure of human endo-α-1,2-mannosidase (MANEA), an antiviral host-glycosylation target" (available <a href="https://doi.org/10.1073/pnas.2013620117">here</a>). Full single-crystal datasets, including images that were not used in the final analyses, are published. The software used for the processing of each dataset is listed in their respective PDB entries. Datasets 6ZJ1 and 6ZJ5 were cut anisotropically using STARANISO, other datasets were processed isotropically.</p> <p> </p> <p>If you find this useful, please contact me at <a href="mailto:lukasz.sobala@hirszfeld.pl">lukasz.sobala@hirszfeld.pl</a>, I am just interested in how these data are used!</p>
Diffraction images used to solve the structures published in the article "From 1,4-Disaccharide to 1,3-Glycosyl Carbasugar: Synthesis of a Bespoke Inhibitor of Family GH99 Endo-α-mannosidase"
<p>Raw diffraction images used for generating the structures published in the article "From 1,4-Disaccharide to 1,3-Glycosyl Carbasugar: Synthesis of a Bespoke Inhibitor of Family GH99 Endo-α-mannosidase" (available <a href="https://doi.org/10.1021/acs.orglett.8b03260">here</a>). Full single-crystal datasets, including images that were not used in the final analyses, are published. The software used for the processing of each dataset is listed in their respective PDB entries. An additional 720 degree dataset is provided, which has been collected from the same crystal as PDB 6HMH. This dataset has not been used to solve the structure presented in the paper. It works very well as an example of sulfur SAD phasing.</p> <p> </p> <p>If you find this useful, please contact me at <a href="mailto:lukasz.sobala@hirszfeld.pl">lukasz.sobala@hirszfeld.pl</a>, I am just interested in how these data are used!</p>
Kinetic modeling of phosphorylase-catalyzed iterative β-1,4-glycosylation for degree of polymerization-controlled synthesis of soluble cello-oligosaccharides
<p>We provide here the underlying data of the publication "Kinetic modeling of phosphorylase-catalyzed iterative β-1,4-glycosylation for degree of polymerization-controlled synthesis of soluble cello-oligosaccharides". Please find the abstract below.</p> <p><strong>Background: </strong>Cellodextrin phosphorylase (CdP; EC 2.4.1.49) catalyzes the iterative β-1,4-glycosylation of cellobiose using α-D-glucose 1-phosphate as the donor substrate. Cello-oligosaccharides (COS) with a degree of polymerization (DP) of up to 6 are soluble while those of larger DP self-assemble into solid cellulose material. The soluble COS have attracted considerable attention for their use as dietary fibers that offer a selective prebiotic function. An efficient synthesis of soluble COS requires good control over the DP of the products formed. A mathematical model of the iterative enzymatic glycosylation would be important to facilitate target-oriented process development.<br> <strong>Results: </strong>A detailed time-course analysis of the formation of COS products from cellobiose (25 mM, 50 mM) and α-D-glucose 1-phosphate (10–100 mM) was performed using the CdP from <em>Clostridium cellulosi</em>. A mechanism-based, Michaelis–Menten type mathematical model was developed to describe the kinetics of the iterative enzymatic glycosylation of cellobiose. The mechanistic model was combined with an empirical description of the DP-dependent self-assembly of the COS into insoluble cellulose. The hybrid model thus obtained was used for kinetic parameter determination from time-course fits performed with constraints derived from initial rate data. The fitted hybrid model provided excellent description of the experimental dynamics of the COS in the DP range 3–6 and also accounted for the insoluble product formation. The hybrid model was suitable to disentangle the complex relationship between the process conditions used (i.e., substrate concentration, donor/acceptor ratio, reaction time) and the reaction output obtained (i.e., yield and composition of soluble COS). Model application to a window-of-operation analysis for the synthesis of soluble COS was demonstrated on the example of a COS mixture enriched in DP 4.<br> <strong>Conclusions:</strong> The hybrid model of CdP-catalyzed iterative glycosylation is an important engineering tool to study and optimize the biocatalytic synthesis of soluble COS. The kinetic modeling approach used here can be of a general interest to be applied to other iteratively catalyzed enzymatic reactions of synthetic importance.</p>
Glycosylated models for: The diversity of the glycan shield of sarbecoviruses closely related to SARS-CoV-2
<p>Glycosylated models (as PDB files) of the sarbecovirus spike proteins used in the study: The diversity of the glycan shield of sarbecoviruses closely related to SARS-CoV-2.</p>
A Simple Strategy to Eliminate Glycation Bias in the Relative Quantification of Protein N-glycosylation
<p><strong>Contents</strong></p> <p>Supplementary files for “A Simple Strategy to Eliminate Glycation Bias in the Relative Quantification of Protein <em>N</em>-glycosylation” by Esser-Skala et al (2020):</p> <ul> <li> <p><em>cafog_raw_data.tar.gz</em>: Raw data for denosumab and NISTmAb.</p> </li> <li> <p><em>cafog_source_code.zip</em>: Supplementary file 1 from the manuscript. This ZIP archive contains the source code of CAFOG.</p> </li> <li> <p><em>data.zip</em>: Supplementary file 2 from the manuscript. Files in this ZIP archive allow to reproduce all results presented in the manuscript.</p> </li> </ul> <p> </p> <p><strong>Changelog</strong></p> <ul> <li>1.1.0 – 2023-05-25 <ul> <li>added supplementary files 1 and 2 mentioned in the manuscript, since those were not published along with the manuscript</li> </ul> </li> <li>1.0.0 – 2020-01-30 <ul> <li>initial release</li> </ul> </li> </ul>
Supplementary Material for "Route Efficiency Assessment and Review of the Synthesis of β-Nucleosides via N-Glycosylation of Nucleobases"
<p>This is the external Supplementary Material for our publication "Route Efficiency Assessment and Review of the Synthesis of β-Nucleosides via <em>N</em>-Glycosylation of Nucleobases", which has been released as a preprint on <em>ChemRxiv </em>(https://doi.org/10.26434/chemrxiv.12753413.v1). The files in this record are additionally available from <em>ChemRxiv</em>.</p>
Interactions of netrin-1 through its glycosylation sites immobilize DCC receptors by favoring its constitutive clustering
Open the record for dataset details and reuse information.
(VIDEOS) Glycosylation as a key for enhancing drug recognition into spike glycoprotein of SARS-CoV-2.
<ul> <li>S1_movie_1. Movie of MD1 trajectory showing the Interaction of ligand TCMDC-124223 (roto-translate phenomenon) on RBD in absence of glycosylations within 50ns of simulation.</li> <li>S2_movie_2. Movie of MD4 trajectory showing the Interaction of ligand TCMDC-133766 (induced fit phenomenon) on the cryptic pocket of NTD in presence of glycosylations within 50ns of simulation.</li> <li>S3_movie_3. Movie of MD2 trajectory showing the Interaction of ligand TCMDC-124223 on RBD in presence of glycosylations within 50ns of simulation.</li> <li>S4_movie_4. Movie of MD3 trajectory showing the Interaction of ligand TCMDC-133766 on the cryptic pocket of NTD in absence of glycosylations within 50ns of simulation.</li> <li>S1_movie_1_v2. Movie of MD1 trajectory showing the Interaction of ligand TCMDC-124223 (roto-translate phenomenon) on RBD in absence of glycosylations within 300ns of simulation.</li> <li>S2_movie_2_v2. Movie of MD4 trajectory showing the Interaction of ligand TCMDC-133766 (induced fit phenomenon) on the cryptic pocket of NTD in presence of glycosylations within 300ns of simulation.</li> <li>S3_movie_3_v2. Movie of MD2 trajectory showing the Interaction of ligand TCMDC-124223 on RBD in presence of glycosylations within 300ns of simulation.</li> <li>S4_movie_4_v2. Movie of MD3 trajectory showing the Interaction of ligand TCMDC-133766 on the cryptic pocket of NTD in absence of glycosylations within 300ns of simulation.</li> </ul>
Three‐level hybrid modeling for systematic optimization of biocatalytic synthesis: α‐glucosyl glycerol production by enzymatic trans‐glycosylation from sucrose
<p>We provide here the underlying data of the publication "Three‐level hybrid modeling for systematic optimization of biocatalytic synthesis: α‐glucosyl glycerol production by enzymatic trans‐glycosylation from sucrose". Please find the abstract below.</p> <p>Mechanism-based kinetic models are rigorous tools to analyze enzymatic reactions, but their extension to actual conditions of the biocatalytic synthesis can be difficult. Here, we demonstrate (mechanistic-empirical) hybrid modeling for systematic optimization of the sucrose phosphorylase-catalyzed glycosylation of glycerol from sucrose, to synthesize the cosmetic ingredient α-glucosyl glycerol (GG). The empirical model part was developed to capture nonspecific effects of high sucrose concentrations (up to 1.5 M) on microscopic steps of the enzymatic trans-glycosylation mechanism. Based on verified predictions of the enzyme performance under initial rate conditions (Level 1), the hybrid model was expanded by microscopic terms of the reverse reaction to account for the full-time course of GG synthesis (Level 2). Lastly (Level 3), the application of the hybrid model for comprehensive window-of-operation analysis and constrained optimization of the GG production (~250 g/L) was demonstrated. Using two candidate sucrose phosphorylases (from <em>Leuconostoc mesenteroides</em> and <em>Bifidobacterium adolescentis</em>), we reveal the hybrid model as a powerful tool of “process decision making” to guide rational selection of the best-suited enzyme catalyst. Our study exemplifies a closing of the gap between enzyme kinetic models considered for mechanistic research and applicable in technologically relevant reaction conditions; and it highlights the important benefit thus realizable for biocatalytic process development.</p>
SIRAH-CoV2 initiative: Glycosylated RBD
<p>This dataset contains the trajectories of 10 microseconds-long coarse-grained molecular dynamics simulations of SARS-CoV2 Spike´s RBD glycosylated at Asn331 and Asn343. The initial coordinates correspond to amino acids 327 to 532 taken from the PDB structure 6VSB. Missing loops and glycosylation trees were added with CHARMM-GUI (http://www.charmm-gui.org).</p> <p>There are two different sets of simulations corresponding to Core Complex and High Mannose. Simulations were performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00006">Machado et al. JCTC 2019</a>, adding 150 mM NaCl according to <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00953">Machado & Pantano JCTC 2020</a>. Glycan parameters are available upon request.</p> <p>The files RBD-Man9_SIRAHcg_rawdata_0-6us.tar and RBD-Man9_SIRAHcg_rawdata_6-10us.tar, contain all the raw information required to visualize (on VMD), analyze, and backmap the simulations of High Mannose glycosylated RBD. Analogous information for Core-complex glycosylations is contained in files RBD-Core-complex_SIRAHcg_rawdata_0-6us.tar and RBD-Core-complex_SIRAHcg_rawdata_6-10us.tar</p> <p>Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using <a href="https://academic.oup.com/bioinformatics/article/32/10/1568/1743152">SirahTools</a> can be found at www.sirahff.com.</p> <p>Additionally, files with names ending in SIRAHcg_10us_glycoprot.tar contain only the protein coordinates, while file names ending with SIRAHcg_10us_glycoprot_skip10ns.tar contains one frame every 10ns.</p> <p>To take a quick look at a trajectory:</p> <p>1- Untar the file RBD-Core-complex_SIRAHcg_10us_prot_skip10ns.tar</p> <p>2- Open the trajectory on VMD 1.9.3 using the command line:</p> <p>vmd glyco-RBD_SIRAHcg_glycoprot.prmtop glyco-RBD_SIRAHcg_glycoprot.ncrst glyco-RBD_SIRAHcg_glycoprot_10us_skip10ns.nc -e sirah_vmdtk.tcl</p> <p>Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. </p> <p>This dataset is part of the SIRAH-CoV2 initiative.</p> <p>For further details, please contact Pablo Garay (pgaray@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).</p>
SIRAH-CoV2 initiative: RBD triple glycosylated at Asn331, 343, and 481 from PDB structure 6XEY
<p>This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of a Spike's RBD from SARS-CoV2 glycosylated at Asn331, 343, and 481 with Man9 glycosylation trees. The initial coordinates correspond to amino acids 327 to 532 taken from the PDB structure 6XEY. Missing loops and glycosylation trees were added with CHARMM-GUI (http://www.charmm-gui.org). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00006">Machado et al. JCTC 2019</a>, adding 150 mM NaCl according to <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00953">Machado & Pantano JCTC 2020</a>. Glycan parameters correspond to those reported by <a href="https://www.biorxiv.org/content/10.1101/2020.12.18.423446v1">Garay et al</a>.</p> <p>The files 6XEY-RBD-3Man9_SIRAHcg_0-4us.tar, 6XEY-RBD-3Man9_SIRAHcg_4-8us.tar, and 6XEY-RBD-3Man9_SIRAHcg_8-10us.tar, contain all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using <a href="https://academic.oup.com/bioinformatics/article/32/10/1568/1743152">SirahTools</a> can be found at www.sirahff.com.</p> <p>Additionally, the file 6XEY-RBD-3Man9_SIRAHcg_glycoprot_10us.tar contains only the protein coordinates, while 6XEY-RBD-3Man9_SIRAHcg_glycoprot_skip10ns.tar contains one frame every 10ns.</p> <p>To take a quick look at the trajectory:</p> <p>1- Untar the file 6XEY-RBD-3Man9_SIRAHcg_glycoprot_skip10ns.tar</p> <p>2- Open the trajectory on VMD using the command line:</p> <p>vmd 6XEY-RBD-3Man9_SIRAHcg_glycoprot.prmtop 6XEY-RBD-3Man9_SIRAHcg_glycoprot.ncrst 6XEY-RBD-3Man9_SIRAHcg_10us_skip10ns.nc -e sirah_vmdtk.tcl</p> <p>Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. </p> <p>This dataset is part of the SIRAH-CoV2 initiative.</p> <p>For further details, please contact Pablo Garay (pgaray@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).</p>
MD simulations from "#GotGlycans: Role of N343 Glycosylation on the SARS-CoV-2 S RBD Structure and Co-Receptor Binding Across Variants of Concern
<p>This folder contains all the MD simulations (saved in frames of 1 ns in PDB format) analysed and discussed in the paper titled "#GotGlycans: Role of N343 Glycosylation on the SARS-CoV-2 S RBD Structure and Co-Receptor Binding Across Variants of Concern" DOI https://doi.org/10.1101/2023.12.05.570076. The naming reflects the specific variant and the presence ('g' or 'gly') or absence ('ng' or 'nogly') of glycosylation at N343 and N331 sites in the SARS-CoV-2 S RBD. Gaussian accelerated MD simulations are indicated with 'gamd', all others represent conventional (deteriministic) sampling. For all details please refer to the original manuscript.</p>
Supplementary information for: Macrophage- and CD4+ T cell-derived SIV differ in glycosylation, infectivity, and neutralization sensitivity
<p>The human immunodeficiency virus (HIV) envelope protein (Env) mediates viral entry into host cells and is the primary target for the humoral immune response. Env is extensively glycosylated, and these glycans shield underlying epitopes from neutralizing antibodies. The glycosylation of Env is influenced by the type of host cell in which the virus is produced. Thus, HIV is distinctly glycosylated by CD4<sup>+</sup> T cells, the major target cells, and macrophages. However, the specific differences in glycosylation between viruses produced in these cell types have not been explored at the molecular level. Moreover, it remains unclear whether the production of HIV in CD4<sup>+</sup> T cells or macrophages affects the efficiency of viral spread and resistance to neutralization. To address these questions, we employed the simian immunodeficiency virus (SIV) model. Glycan analysis implied higher relative levels of oligomannose-type <em>N</em>-glycans in SIV from CD4<sup>+</sup> T cells (T-SIV) compared to SIV from macrophages (M-SIV), and the complex-type <em>N</em>-glycans profiles seem to differ between the two viruses. Notably, M-SIV demonstrated greater infectivity than T-SIV, even when accounting for Env incorporation, suggesting that host cell-dependent factors influence infectivity. Further, M-SIV was more efficiently disseminated by HIV-binding cellular lectins. We also evaluated the influence of cell type-dependent differences on SIV's vulnerability to carbohydrate-binding agents (CBAs) and neutralizing antibodies. T-SIV demonstrated greater susceptibility to mannose-specific CBAs, possibly due to its elevated expression of oligomannose-type <em>N</em>-glycans. In contrast, M-SIV exhibited higher susceptibility to neutralizing sera in comparison to T-SIV. These findings underscore the importance of host cell-dependent attributes of SIV, such as glycosylation, in shaping both infectivity and the potential effectiveness of intervention strategies.</p>
Dataset for "Formal Single Atom Editing of the Glycosylated Natural Product Fidaxomicin Improves Acid Stability and Retains Antibiotic Activity"
<p>ZIP File:</p> <p>Characterisation data (such as e.g. NMR, IR, MS spectra)</p> <p>NMR raw data, .mnova files</p> <p>DP4+ data (final conformer coordinate files, result tables)</p> <p>DFT simulation data (coordinate files, results table)</p> <p>PDF file:</p> <p>Supporting information for</p> <p>Formal Single Atom Editing of the Glycosylated Natural Product Fidaxomicin Improves Acid Stability and Retains Antibiotic Activity</p>
N-glycosylation acts as a switch for FGFR1 trafficking between the plasma membrane and nuclear envelope - yet unpublished supplementary data regarding Fig. 1C
<p>Fibroblast growth factor receptor 1 (FGFR1) is a heavily N-glycosylated cell surface receptor tyrosine kinase that transmits signals across the plasma membrane, in response to fibroblast growth factors (FGFs). Balanced FGF/FGFR1 signaling is crucial for the development and homeostasis of the human body, and aberrant FGFR1 is frequently observed in various cancers. In addition to its predominant localization to the plasma membrane, FGFR1 has also been detected inside cells, mainly in the nuclear lumen, where it modulates gene expression. However, the exact mechanism of FGFR1 nuclear transport is still unknown. In this study, we generated a glycosylation-free mutant of FGFR1, FGFR1.GF, and demonstrated that it is localized primarily to the nuclear envelope. We show that reintroducing N-glycans into the D3 domain cannot redirect FGFR1 to the plasma membrane or exclude the receptor from the nuclear envelope. Reestablishment of D2 domain N-glycans largely inhibits FGFR1 accumulation in the nuclear envelope, but the receptor continues to accumulate inside the cell, mainly in the ER. Only the simultaneous presence of N-glycans of the D2 and D3 domains of FGFR1 promotes efficient transport of FGFR1 to the plasma membrane. We demonstrate that while disturbed FGFR1 folding results in partial FGFR1 accumulation in the ER, impaired FGFR1 secretion drives FGFR1 trafficking to the nuclear envelope. Intracellular FGFR1.GF displays a high level of autoactivation, suggesting the presence of nuclear FGFR1 signaling, which is independent of FGF. Using mass spectrometry and proximity ligation assay, we identified novel binding partners of the nuclear envelope-localized FGFR1, providing insights into its cellular functions. Collectively, our data define N-glycosylation of FGFR1 as an important regulator of FGFR1 kinase activity and, most importantly, as a switchable signal for FGFR1 trafficking between the nuclear envelope and plasma membrane, which, due to spatial restrictions, shapes FGFR1 interactome and cellular function.</p> <p> </p> <p>These data are raw data of Fig. 1C generated by Aleksandra Chorążewska. These data are not present in supplementary data od publication</p>
Congenital disorder of glycosylation caused by starting site-specific variant in syntaxin-5
<p>The SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein syntaxin-5 (Stx5) is essential for Golgi transport. In humans, the <em>STX5</em> mRNA encodes two protein isoforms, Stx5 Long (Stx5L) from the first starting methionine and Stx5 Short (Stx5S) from an alternative starting methionine at position 55. In this study, we identified a novel human disorder caused by a single missense substitution in the second starting methionine (p.M55V), resulting in complete loss of the short isoform. Patients suffer from an early fatal multisystem disease, including severe liver disease, skeletal abnormalities and abnormal glycosylation. Primary human dermal fibroblasts isolated from these patients showed defective glycosylation, altered Golgi morphology as measured by electron microscopy and mislocalization of glycosyltransferases. Measurements of anterograde trafficking, based on biotin-synchronizable forms of Stx5 (the RUSH system), and of cognate binding SNAREs, based on Förster resonance energy transfer (FRET), revealed that the short isoform of Stx5 is essential for intra-Golgi transport. This is the first time a mutation in an alternative starting codon is linked to human disease, demonstrating that the site of translation initiation is an important new layer of regulating protein trafficking.</p>
DATA for Exploration of O-GlcNAc-transferase (OGT) glycosylation sites reveals a target sequence compositional bias
<p>Mass spectrometry data for identification of glycosylation sites in CBP ID3 and EWS LCRn</p> <p>Perl based implementation of glycosylation Site Predictor OGTcomPred</p>
Supplementary information for: Macrophage- and CD4+ T cell-derived SIV differ in glycosylation, infectivity, and neutralization sensitivity
Open the record for dataset details and reuse information.
Data from: Mannose glycosylation is an integral step for human NIS localization and function in breast cancer cells
Open the record for dataset details and reuse information.
A single-cell atlas of Drosophila trachea reveals glycosylation-mediated Notch signaling in cell fate specification
<p>Processed data files for the following article:</p><p>Li Y, Lu T, Dong P, Chen J, Zhao Q, Wang Y, Xiao T, Wu H, Zhao Q and Huang H. A single-cell atlas of Drosophila trachea reveals glycosylation-mediated Notch signaling in cell fate specification.</p><p>Please also refer to code at https://github.com/Tianfeng-Lu/single-cell-atlas-of-fly-trachea</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.