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2,489 results for “Sars-CoV-2”
Structure prediction from SARS-CoV-2 accessory proteins ORF-7B
<p>Structure prediction made with Collabfold for SARS-CoV-2 accessory protein ORF-7B.</p> <p>The archive contains both the structure and the logs from the prediction.</p>
PanDDA files from a ligand screen against the NSP3 macrodomain of SARS-CoV-2 - ligands from linking with FRESCO
<p>This deposition contains the X-ray diffraction data used to run PanDDA in the ligand screen against the NSP3 macrodomain of SARS-CoV-2 described in McCorkindale et al. 2022 (https://doi.org/10.1101/2022.11.21.517375).</p> <p>mac1_pandda.zip contains the structure factor intensities, PanDDA input/ouput and refined models/maps. A description of the files can be found in the README file. </p> <p>mac1_ligand-bound_states.zip contains the ligand-bound states extracted from the multi-state PDB files. </p>
SARS-CoV-2 genomes dataset (TargetCall-D2)
<p>Detailed description:</p> <p>The fast5 files in this dataset is generated from ONT machine.</p> <p>This dataset includes the 4000 fast5 samples sampled from datasets released in https://www.caddecentre.org</p> <p> </p>
Antibody accessibility determines location of spike surface mutations in SARS-CoV-2 variants
<p>Scripts and Data to reproduce plots in</p> <p>Sören von Bülow, Mateusz Sikora, Florian E.C. Blanc, Roberto Covino, Gerhard Hummer, "Antibody accessibility determines location of spike surface mutations in SARS-CoV-2 variants", PLoS Computational Biology 202X</p>
Performance Evaluation of SARS-CoV-2 Viral Transport Medium Produced by Bangladesh Reference Institute for Chemical Measurements
<p>Supplementary Table S1: Stability study design of BRiCM VTM<br> Supplementary Table S2: Stability study result of BRiCM VTM</p>
Dimerization the ACE-2 with Different RBD Mounts: A Dynamic Simulation Perspective on SARS-Cov-2 Infecting Details
<p>The system construction and dynamic simulation data of paper "Dimerization the ACE-2 with Different RBD Mounts: A Dynamic Simulation Perspective on SARS-Cov-2 Infecting Details"(manuscript, ci-2023-00041c) are prepared.</p>
Screening for nucleoside inhibitors of the SARS-CoV-2 RdRP
<p>This report describes the most relevant results of screening compounds with a nucleoside analogue structure from the Janssen Pharmaceutica compound collection for potential activity against SARS-CoV-2 in a cell-based assay and nucleoside triphosphates in a radioactive filtering binding RdRP assay.</p>
AGC archives of human and SARS-CoV-2 genomes
<p><a href="https://github.com/refresh-bio/agc">AGC</a> is a tool to compress a collection of similar genomes. This Zenodo record provides pre-built AGC-3.0 archives of several datasets:</p> <ul> <li>File "HPRC-yr1.agc" contains <a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_009914755.3/">CHM13</a> and 94 haploid human assemblies <a href="https://github.com/human-pangenomics/HPP_Year1_Data_Freeze_v1.0">released by HPRC</a> in 2021. The telomere-to-telomere CHM13 v2 plus chrY from GRCh38 is used as the reference genome.</li> <li>File "sars-cov-2_ncbi-620k.agc" contains 619,750 complete SARS-CoV-2 genomes with <a href="https://www.ncbi.nlm.nih.gov/nuccore/NC_045512.2">NC_045512.2</a> as the reference. It was created with AGC command line "agc create -cb10000 -s3000". SARS-CoV-2 genomes were downloaded <a href="https://www.ncbi.nlm.nih.gov/datasets/coronavirus/genomes/">from NCBI</a> at the end of year 2021. The original FASTA is provided as "sars-cov-2_ncbi-620k.fa.xz".</li> </ul>
Uncover a microbiota signature of upper respiratory tract in patients with SARS-CoV-2+
<p>This is the repository containing the code used to obtain the results shown in <a href="https://doi.org/10.1038/s41598-023-43040-x"><i><strong>Bellato M, Cappellato M, Longhin F, Del Vecchio C, Brancaccio G, Cattelan AM, Brun P, Salaris C, Castagliuolo I, Di Camillo B. "Uncover a microbiota signature of upper respiratory tract in patients with SARS-CoV-2+" Sci Rep 13, 16867 (2023)</strong></i></a>.</p><p>We characterized through 16S rDNA-seq the microbiota in the upper airways of 192 subjects with a positive nasopharyngeal swab for SARS-CoV-2 to identify a microbial signature predictive of disease progression. Patients were divided in groups based on the presence of symptoms, the level of pneumonia, and whether or not they needed oxygen therapy or intubation. </p><p>In the GitLab repository <a href="https://gitlab.com/sysbiobig/microbiomecovid/-/tree/v1.0">here</a> there are all the scripts used to perform the preprocessing step and the downstream analysis. The GitLab repository (version 1.0) contains also the Docker image <strong>microbiomecovid:1.0.0</strong> that can be used to reproduce the results shown in the paper (see the instruction <a href="https://gitlab.com/sysbiobig/microbiomecovid/-/tree/v1.0#reproduce-the-results-%EF%B8%8F">here</a>).</p><p>Here in Zenodo you can find the <strong>microbiomecovid_data.zip </strong>file containing two folders that need to be unzipped and put in the <i>microbiomecovid</i> local repository, downloaded from GitLab.</p><p>In particular, the <i><strong>original_data</strong></i> folder contains:</p><ul><li><i><strong>Raw_data</strong></i><strong>: </strong>a folder with two FASTQ files for each sample, i.e., forward (R1) and reverse (R2) reads.</li><li><strong>Metadata.xlsx: </strong>the table containing information on the - anonymized - subjects involved in the study.</li><li><strong>QC Report.pdf: </strong>The report provided by the sequencing center.</li></ul><p>Additionally, in the <i><strong>output</strong></i><strong> </strong>folder, the following items can be found:</p><ul><li><i><strong>Preprocessing</strong></i><strong>: </strong>a folder containing all the output file from step1 to step7, namely:<ul><li>create input data for QIIME2;</li><li>import data in QIIME2;</li><li>remove primers;</li><li>denoising and imputation;</li><li>taxonomy classification;</li><li>phylogenetic tree reconstruction;</li><li>collapse at specific taxonomic level and normalize data.</li></ul></li><li><i><strong>Analysis</strong></i><strong>: </strong>a folder containing all the output files form step8 to step10 namely:<ul><li>alpha and beta diversity results;</li><li><i><strong>DA_output</strong></i><strong>:</strong> a folder containing the differential abundance analysis performed for each taxonomic level and for each covariate;</li><li><i><strong>Network_output:</strong></i> a folder containing the sparCC and Cytoscape networks and results.</li></ul></li></ul><p>For more info about all the bioinformatic pipeline see the <a href="https://gitlab.com/sysbiobig/microbiomecovid/-/tree/v1.0#pipeline">GitLab repository</a><strong>.</strong></p><p>Remember to set the path as <i>ABSOLUTE_PATH_MICROBIOMECOVID.</i></p>
Sars-Cov-2 training dataset
<p>Training dataset SARS-Cov-2 amplicons Artic v3</p>
Data and Code for "Behavioral factors and SARS-CoV-2 transmission heterogeneity within a household cohort in Costa Rica"
<p>Data and Code for "Behavioral factors and SARS-CoV-2 transmission heterogeneity within a household cohort in Costa Rica"</p>
Movies and data to accompany "Single-virus fusion measurements reveal multiple mechanistically equivalent pathways for SARS-CoV-2 entry"
<p>Movies and data to accompany "Single-virus fusion measurements reveal multiple mechanistically equivalent pathways for SARS-CoV-2 entry".</p> <p>AVI files contain movies of video micrographs</p> <p>TIFF files contain primary micrographs for representative experiments</p> <p>XLS file contains analyzed data with individual fusion waiting times (as well as locations of fusion events)</p>
The relationship between the clinical course of SARS-CoV-2 infection with ACE2 and TMPRSS2 expression and polymorphisms
<p>Background<br> The viral S protein and host ACE2 and TMPRSS2 genetic variations may act as a barrier to viral<br> infection or determine susceptibility to COVID-19 infection.<br> Objectives<br> We investigated the relationship between the expression patterns and polymorphisms of the ACE2<br> and TMPRSS2 receptor genes associated with COVID-19 and the clinical course of COVID-19<br> infection.<br> Material and methods<br> We studied 147 COVID-19 patients (41 asymptomatic, 53 symptomatic and 53 treated in intensive<br> care unit (ICU) cases) and 33 healthy controls. ACE2 and TMPRSS2 expressions were determined<br> using the One-Run RT Q-PCR kit. Genotypic distributions of Single Nucleotide Polymorphisms (SNP)<br> of ACE2 and TMPRSS2 were obtained by RT-PCR.<br> Results<br> The expressions of ACE2 and TMPRSS2 were different between SARS-CoV-2 positive and negative<br> groups. ACE2 rs714205GG genotype and G-allele showed significant differences in the SARS-CoV-2<br> positive asymptomatic group. A significant correlation was found between TMPRSS2 rs8134378GA,<br> rs2070788GA, rs7364083GA and rs9974589AC genotypes and SARS-CoV-2 positivity. The<br> rs1978124 C-allele and rs8134378 A-allele were significant in the SARS-CoV-2 positive symptomatic<br> group. TMPRSS2 rs2070788GA was different in all patient groups from the control group. There was a<br> difference between SARS-CoV-2 positive and negative groups for the CTTA haplotype formed by<br> ACE2 variants. The AGCAG and AGAAG haplotypes formed by TMPRSS2 variants were more<br> common in the asymptomatic patient group than in other patient groups.<br> Conclusions<br> Identifying the relationship between host genetic variants and COVID-19 susceptibility will contribute to<br> further studies that will enable new vaccines and potential therapeutic approaches to be applicable.</p>
Safety and immunogenicity of heterologous booster immunization with Ad5-nCoV after three-dose priming with inactivated SARS-CoV-2 vaccine in Chinese adults: a randomized, double-blind, parallel-controlled trial
<p>Data on safety and immunity of heterologous booster (fourth dose) after three-dose priming with inactivated SARS-CoV-2 vaccine are limited in Chinese adults. Here, we evaluate the safety and immunogenicity of immunization with Ad5-nCoV in a randomized, double-blind, parallel-controlled phase 4 clinical trial in Zhejiang, China (NCT05373030). Participants aged 18-80 years (100 participants per group) who have administered three doses of inactivated SARS-CoV-2 vaccine ≥ 6-month earlier were enrolled and randomized at 1:1 into two groups, then administered intramuscular Ad5-nCoV or different inactivated SARS-CoV-2 vaccine (CoronaVac or Covilo) respectively. All observed adverse reactions were predictable and manageable. Ad5-nCoV elicited significantly higher RBD-specific IgG levels, with a GMC of 2924.0 on day 14 post-booster, 7.8-fold that of the inactivated vaccine. Pseudovirus-neutralizing antibodies to Omicron BA.4/5 showed a similar pattern, with GMT of 228.9 in the Ad5-nCoV group and 65.5 in the inactivated vaccine group. The Ad5-nCoV booster-maintained a high antibody levels on day 90, with seroconversion of 71.4%, while the inactivated vaccine group was 5.2%, closed to pre-booster levels. In summary, a fourth Ad5-nCoV vaccination following three-dose inactivated SARS-CoV-2 vaccination is immunogenic, tolerable, and more efficient than inactivated SARS-CoV-2 vaccine. Ad5-nCoV elicits a stronger humoral response against Omicron BA.4/5 and maintains antibody levels for longer than homologous boosting.</p>
The ribosome-inactivating proteins MAP30 and Momordin inhibit SARS-CoV-2
<p>These data are related to a manuscript submitted to PLOS ONE. The recombinant proteins MAP30 and Momordin, prepared at the National Institute of Arthritis and Musculoskeletal and Skin Diseases, were analyzed for SARS-CoV-2 inhibition using A549-NLRV human lung cell assays performed at Southern Research during the Covid-19 pandemic. All viral inhibition and cell viability values reported can be derived from the raw data provided here. Some data are replicates. File dates correspond to those originally provided by and preserved at Southern Research, Birmingham AL.</p>
Codes and datasets for: Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control
<p>Codes and datasets to reproduce the main figures of the article titled: "Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control".</p>
CD4+ and CD8+ T cell responses to peptides covering SARS-CoV-2 Spike in response to mRNA vaccination in persons recovered from SARS-CoV-2 infection
<p>These files contain intracellular cytokine staining flow cytometry data for CD4+ and CD8+ T cells after exposure of serial PBMC to SARS-CoV-2 spike peptides or control antigens. PBMC are from subjects recovered from SARS-CoV-2 infection that subsequently received mRNA vaccination. The data were analyzed and exported from FlowJo version 10 as individual gated events and related Boolean subsets for four functional markers: CD40L, IFN-g, IL-2, and TNF-a. Counts and frequencies are both included.</p> <p> </p> <p><strong>Procedure for obtaining data:</strong></p> <p>Cryopreserved peripheral blood mononuclear cells (PBMC) were thawed and rested overnight. PBMC (1 x 10<sup>6</sup> per well) were stimulated with a SARS-CoV-2 spike overlapping peptide pool (JPT, 1 μg/mL each peptide; 0.4% final DMSO concentration), 0.4% DMSO as a negative control, or PHA-P (Remel; 1.6 μg/mL final concentration) as a positive control, in the presence of anti-CD28 and anti-CD49d (BD Biosciences) antibodies at 37°C for 6 hours. Brefeldin A (Sigma) was added after 2 hours. Cells were stained with Live/Dead Near IR dye (Invitrogen), treated with FACS lyse (BD Biosciences) and frozen at -80<sup>o</sup>C. For staining, the cells were thawed, washed, and permeabilized with Permeabilizing solution 2 (BD Biosciences) then stained with fluorochrome labeled monoclonal antibodies to anti-human CD3 mAb (clone UCHT) conjugated with PE-Texas Red (ECD; Beckman Coulter), anti-human CD4 mAb (clone SK3) conjugated with BV510 (Biolegend), anti-human CD8 mAb (clone SK1) conjugated with PerCP-Cy5.5 (BD Biosciences), and the activation markers anti-human CD40L mAb (clone TRAP1) conjugated with BV421 (BD Biosciences), anti-human IFNγ mAb (clone 4S.B3) conjugated with PE (BD Biosciences), anti-human IL2 mAb (clone MQ1-17H12) conjugated with APC (BD Biosciences), and anti-human TNFα mAb (clone MAb11) conjugated with FITC (BD Biosciences). Events were recorded with BD Fortessa and analyzed with FlowJo (v10 for Mac; BD). </p>
Longitudinal Assessment of TCR Repertoires in Recipients of Inactivated SARS-CoV-2 Vaccines: An Artificial Intelligence-Guided Study
<p>T cells play a crucial role in mitigating disease severity during SARS-CoV-2 infection and in shaping long-term immune memory. However, the precise molecular immune response involving T-cell receptor (TCR) repertoire changes following full vaccination, and evaluating vaccine efficacy through TCR analysis, remains incompletely understood. In this study, we conducted a 10-month longitudinal investigation of individuals who received SARS-CoV-2 inactivated vaccines and developed a vaccine efficacy evaluation model. Through the advanced large language artificial intelligence method, we identified vaccine-specific TCR clones, 3 V genes, 20 V-J combinations, and 3 epitopes, and traced their longitudinal development. The vaccine-specific TCR clones expanded to peak levels after the second vaccine dose and remained detectable in most subjects at 10 months. Utilizing vaccine-specific TCRs as novel markers, we constructed a vaccine efficacy evaluation model that predicts antibody levels with a mean AUC of 0.96, highlighting the relationship between vaccine-specific TCRs and antibodies. Our findings reveal the longitudinal patterns of vaccine-specific TCR clones and the potential of the efficacy evaluation model built upon them.</p>
Positive selection screen in yeast for inhibitors of SARS-CoV-2 Main Protease. Dataset from docking studies.
<p>Best docked poses from XP docking and covalent docking (Glide; Schrödinger 2021-2) towards the SARS-CoV-2 MPro protein (PDB ID 7CB7). List of ligands is also included. </p>
Fig. 5. pro-ISG15 in Natural biflavones are potent inhibitors against SARS-CoV-2 papain-like protease
Fig. 5. pro-ISG15 cleavage assays for the biflavones. (A) Initial screening of all nine biflavones for the inhibitory activities against PLpro-mediated deISGylation at a 20 μM concentration. (B–D) Active biflavones were further evaluated at serially diluted concentrations of 20, 10, 5 and 2.5 μM. (E) Inhibition rates for all 9 biflavones against PLpro-mediated deISGylation at 20 μM. (F) Inhibition rates for C–C-type biflavones (2–4) at concentrations of 20, 10, 5 and 2.5 μM. (G) Inhibition rates for C–O–C-type biflavones (7–9) at concentrations of 20, 10, 5 and 2.5 μM. w/o inb. = without inhibitors.
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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.