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2,489 results for “Sars-CoV-2”
Figure 1 from: Senapati S, Dash J, Sethi M, Chakraborty S (2020) Bioengineered probiotics to control SARS-CoV-2 infection. Research Ideas and Outcomes 6: e54802. https://doi.org/10.3897/rio.6.e54802
<p>Figure 1 Bioengineered probiotics to control SARS-CoV-2 infection. (a) Pathogenesis of SARS-CoV-2 depends on interaction between S protein of virus and angiotensin-converting enzyme 2 (ACE2) expressed on the surface of host cells. (b (1)) Engineered probiotics with expression of cell bound ACE2, sequesters the virus by making it bind to the ACE2 receptor on its surface thus inhibiting the viral entry into gut epithelial cells. (b (2)) The secreted form of ACE2 (sACE2) produced by probiotics confiscates the virus by binding to S proteins and masking their binding sites for gut epithelial ACE2. (c) The sACE2 could also have systemic effects due to its absorption into circulation and inhibiting the virus binding at distant organs like lungs.</p>
Figure 4 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 4 Docking energies and interface score charts. A shows the Rosetta Dock results, binding energies from PDBEPISA server in B shows good results for ΔG. Developability of this antibody shows all green flags in C.
Figure 3 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 3 Docking interface between the modified 80R antibody and the RBD of the SARS-CoV-2 spike protein. The model shows the structural interface with the 80R antibody above and the RBD below. The seven substitutions in 80R are shown in magenta and RBD residues are shown in cyan. Notice how the substitutions in 80R allow new aromatic-aromatic interactions that improve binding to the RBD and are not present in wild type 80R. E484 is shown pointing towards the beta strand of 80R and a glycine substitution was therefore introduced to avoid clashes.
Figure 6 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 6 m396 mutations docking results. A shows Rosetta Dock funnels for the original partners SARS-CoV and m396, SARS-CoV-2 and m396 and the SARS-CoV-2 and mutated m396. Notice how the binding is improved to the level of the original partners. B shows the ΔG energies again notice the improvement of binding when the mutations are introduced. Finally, C shows the developability flags with only one warning that is not that far from green flag.
Figure 5 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 5 Docking interface between the modified m396 antibody and SARS-CoV-2 spike protein RBD. In magenta is m396 mutant and in cyan SARS-CoV-2 RBD. These five mutations introduce many electrostatic interactions between the partners therefore stabilizing very much the binding.
Figure 2 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 2 Structural analysis of SARS-CoV spike glycoprotein. In A the SARS-CoV spike protein (PDB ID: 6ACG) is shown bound to ACE2 (brown) and 80R antibody (cyan), superimposed on the same binding site. In B the spike protein is shown bound only to the 80R antibody (PDB ID: 2GHW), with the structural model of the RBD of the SARS-CoV-2 spike protein (magenta) containing the missing loops. This homology model served as the basis for the docking experiments. In C it is shown a spike colored by subunit and showing the glycans. There are only two possible glycans in RBD region at 331 and 343 and neither of these sites affect the 80R binding.
Figure 1 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 1 Structural model of SARS-CoV-2 infection. This structural model was built with UCSF Chimera using high-performance computers (Bridges Large and Frontera). The model shows 16 viruses, with the spike proteins shown in green (PDB ID: 6VSB) and an actual lipid bilayer membrane, with ACE2 dimers shown in magenta. All these structures are at atomic resolution. The length of the membrane is approximately 1 micrometer.
Data for manuscript "Estimate of airborne transmission of SARS-CoV-2 using real time tracking of healthcare workers."
<p>These are the data sets for a manuscript to calculate the transmissability of SARS CoV-2 via the airborne route. These data have the duration of exposure of healthcare workers to SARS CoV-2 and the code used to analyze to estimate q, and the comparison to other pathogens.</p>
SARS-CoV-2 Origins and Evolution: Insights from Coronaviruses Recombination and Phylogenetic Analysis
<p>It is imperative in the midst of a global epidemic to investigate the origins of the infectious agent especially when it has reached parts of the world with either ailing economies or pre-existing political turmoil consistent with non-functional health systems. To explore the possibility of cross species infection, genomic recombination and the emergence of novel coronaviruses in the near future we carried out recombination and phylogenetic analysis to determine the spatio-temporal evolution and origins of the current SARS-CoV-2 virus. Using two robust recombination tools, RDPv4.100 and SimPlot3.5.1 analysis, our findings prove that SARS-CoV-2 is a recombinant of pangolin and bat RaTG13 sequences as been previously shown elsewhere. We also report one novel recombination event between two SARS-CoV-2 sequences (<em>SARS-CoV-2 sequence, MT188341</em>, <em>SARS-CoV-2 sequence, </em><em>MT293183).</em> Bearing in mind that the prerequisite for recombination is the occurrence of two viral sequences in the same reservoir, biological niche or host at the same time we postulate either co-infection with the two viral sequences, or superinfection. The possibility of recombination between the SARS-CoV-2 sequences poses the likelihood of the emergence of new more or less virulent “strains” of the virus. The future of science lies in our ability to be able to use computational based methods to predict the genetic sequences of infectious agents of the next epidemics. Addition of more SARS-CoV-2 sequences has a bearing on our understanding of the origin, evolution and clinical outcome prediction of given viral genomes. More SARS-CoV-2 sequences are needed to elucidate our understanding of this family of viruses.</p>
Supplementary Structural Models (SARS-CoV-2 Spike-RBD:ACE2 complex and TMPRSS2) - SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals
<p>Structural Models (PDB) of SARS-CoV-2 Spike RBD bound to ACE2 receptors of 215 animals.</p> <p>Structural model of Human TMPRSS2.</p> <p>Modelled using the FunMod pipeline and referenced in the preprint</p> <p><a href="https://www.biorxiv.org/content/10.1101/2020.05.01.072371v5">SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals</a></p> <p> </p>
Data sets v.1.1 for Perspective: SARS-CoV-2 may regulate cellular responses through depletion of specific host miRNAs
<p>The list of potential (bioinformatic predictions) interactions of human miRNA with 7 coronavirus genomes that include 3 pathogenic and 4 non-pathogenic coronaviruses. (<strong>Data Set 1</strong>). <em>The HCoVs' RNA genomes of pathogenic strains were SARS-CoV-2 (NC_045512.2), SARS-CoV (NC_004718.3), MERS-CoV (NC_019843.3). </em>The non-pathogenic strains were HCoV-OC43 (KU131570.1), HCoV-229E (NC_002645.1), HCoV-HKU1 (KF686346.1), and HCoV-NL63 (NC_005831.2). These coronaviruses were tested against the set of 896 confident mature human miRNA sequences that were obtained from the miRBbase v2.21 using the RNA22 v2 microRNA target discovery tool web-server. In order to reduce the false discovery rate of the MTS predictions, the most strict parameters were applied to the default computation workflow using a specificity of 92% versus a sensitivity of 22%.</p> <p><strong>Data set 2.</strong> The potential targets of miRNA that could be bound to either the pathogenic, the non-pathogenic or both groups of HCoVs. Predicted base on miRDIP database (with only top 1% of the most probable targets considered),</p> <p><strong>Data set 3. </strong> Pre-miRNA sequences in the <em>SARS-CoV-2</em> RNA sequence that could potentially enter the human RNAi pathway, base on miRNAFold webserver.</p>
Electron microscopy of SARS-CoV-2 particles - Dataset 02
<p>The dataset contains 128 transmission electron microscopy images of ultrathin (60-70 nm) plastic sections through extracellular SARS-CoV-2 particles in Vero cell cultures. Images were recorded with 1376 x 1032 pixel dimensions at 0.64 nm pixel size (12 bit) and stored in 16 bit TIF format. For visualization of the images, use an image viewer capable of reading 16 bit images (e.g. IrfanView). Image files are size calibrated and can be opened with the correct size calibration using ImageJ or Fiji using the Bioformats importer. The image files are accompanied by a PDF document which describes the methods which were used for generation of the images. The dataset was produced as dataset 02 for a comparative morphometric analysis of SARS-CoV and SARS-CoV-2. Further datasets which were used for the analysis are available in this repository (see dataset description document).</p> <p>Related publication: Laue M, Kauter A, Hoffmann T, Möller L, Michel J, Nitsche A. Morphometry of SARS-CoV and SARS-CoV-2 particles in ultrathin plastic sections of infected Vero cell cultures. Sci Rep. 2021 Feb 10;11(1):3515. doi: 10.1038/s41598-021-82852-7. PMID: 33568700; PMCID: PMC7876034.</p>
Electron Tomograms of SARS-CoV and SARS-CoV-2 particles in Vero cell culture
<p>The tomograms are supplemental data of a manuscript on the morphometry of SARS-CoV and SARS-CoV-2 particles in cell culture which is available as a preprint on BioRxiv.</p>
Genomic Evidence for a Case of Reinfection with SARS-CoV-2
<p>Tillett, Richard and Sevinsky, Joel and Hartley, Paul and Kerwin, Heather and Crawford, Natalie and Gorzalski, Andrew and Laverdure, Christopher and Verma, Subhash and Rossetto, Cyprian and Jackson, David and Farrell, Megan and Van Hooser, Stephanie and Pandori, Mark, Genomic Evidence for a Case of Reinfection with SARS-CoV-2 (August 25, 2020). Available at SSRN: <a href="https://ssrn.com/abstract=3680955">https://ssrn.com/abstract=3680955</a> or <a href="https://dx.doi.org/10.2139/ssrn.3680955">http://dx.doi.org/10.2139/ssrn.3680955</a></p>
SARS-CoV-2 spike binding to ACE2-B0AT1 complex
<p>Cryo-EM maps and models of SARS-CoV-2 spike (EMD:21457) and ACE2-B0AT1 (EMD:30039) are illustrated. Membranes are shown around the B0AT1 and approximated around the spike, which is lacking the trans-membrane domain. The binding of the spike to the ACE2 receptor is shown based on the model RBD built into the ACE2-B0AT1 map. The appears to attain a sharp angle wrt. the membrane surface to allow this binding.</p>
Supervised molecular dynamics for exploring the druggability of the SARS-CoV-2 spike protein (Topology and .xtc files)
<p>ABSTRACT. The recent outbreak of the respiratory syndrome-related coronavirus (SARS-CoV-2) is stimulating an unprecedented scientific campaign to alleviate the burden of the coronavirus disease (COVID-19). One line of research has focused on targeting SARS-CoV-2 proteins fundamental for its replication by repurposing drugs approved for other diseases. The first interaction between the virus and the host cell is mediated by the spike protein on the virus surface and the human angiotensin-converting enzyme (ACE2). Small molecules able to bind the receptor-binding domain (RBD) of the spike protein and disrupt the binding to ACE2 would offer an important tool for slowing, or even preventing, the infection. Here, we screened 2421 approved small molecules<em> in </em>silico and validated the docking outcomes through extensive molecular dynamics simulations. Out of six drugs characterized as putative RBD binders, the cephalosporin antibiotic cefsulodin was further assessed for its effect on the binding between the RBD and ACE2, suggesting the importance of considering the dynamic formation of the heterodimer when judging any potential candidate.</p>
SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities
<p>Brazil has one of the fastest-growing COVID-19 epidemics worldwide. Non-pharmaceutical interventions (NPIs) have been adopted on a municipal level, with asynchronous actions taken across 5,568 municipalities and the Federal District. This paper addresses this complexity reporting on a novel dataset with survey responses from 4,027 mayors, 72.4% of the total municipalities in the country. This dataset responds to the urgency to track and share findings on fragmented policies to tackle health crises like the COVID-19 pandemic. Quantifying NPIs can allow for understanding the effectiveness of interventions in reducing transmission. We offer temporal details for a range of measures aimed at reducing social distancing as well as when local governments started to relax those measures.</p>
3D model of the human ACE2 receptor bound to the SARS-CoV-2 Spike RBD
<p>3D structure model of the receptor-binding domain of SARS-CoV-2 (top) bound to the human ACE2 receptor (bottom). The two highlighted aminoacids - ACE2 D30 (red) and RBD K417 (blue) - are part of a set of interactions that is conserved in animal species susceptible to infection by the virus but are absent from immune species.</p>
Code and data sharing for manuscript titled "Transmission heterogeneities, kinetics, and controllability of SARS-CoV-2"
<p>Code and data sharing for manuscript titled "Transmission heterogeneities, kinetics, and controllability of SARS-CoV-2".</p>
Supplementary material 3 from: Padilla-Sanchez V (2021) SARS-CoV-2 Structural Analysis of Receptor Binding Domain New Variants from United Kingdom and South Africa. Research Ideas and Outcomes 7: e62936. https://doi.org/10.3897/rio.7.e62936
United Kingdom variant interactions
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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.