The COVID-19 dashboard includes data on city/town COVID-19 activity, confirmed and probable cases of COVID-19, confirmed and probable deaths related to COVID-19, and the demographic characteristics of cases and deaths.

The SARS-CoV-2 coronavirus, which causes a respiratory disease called COVID-19, has been declared a pandemic by the World Health Organization (WHO) and is still ongoing. Vaccination is the most important strategy to end the pandemic. Several vaccines have been approved, as evidenced by the ongoing global pandemic, but the pandemic is far from over and no fully effective vaccine is yet available. One of the most critical steps in vaccine development is the selection of appropriate antigens and their proper introduction into the immune system. Therefore, in this study, we developed and evaluated two proposed vaccines composed of single and multiple SARS-CoV-2 polypeptides derived from the spike protein, namely, vaccine A and vaccine B, respectively. The polypeptides were validated by the sera of COVID-19-vaccinated individuals and/or naturally infected COVID-19 patients to shortlist the starting pool of antigens followed by in vivo vaccination to hACE2 transgenic mice. The spike multiple polypeptide vaccine (vaccine B) was more potent to reduce the pathogenesis of organs, resulting in higher protection against the SARS-CoV-2 infection.

Context

Hoping this data will be used to identify new predictions as a new COVID19 data spike was reported at Iran in the city of Tehran. NOTE: The data is mined from WHO.

Content

The data is from the official WHO website that you can also download. I downloaded it here to code it inside Kaggle for easier import of data and developing the code. The data is composed of COVID19 by country, every data that is up to the latest as of December 8, 2020.

Acknowledgements

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

Your data will be in front of the world's largest data science community.

Despite over 13 billion SARS-CoV-2 vaccine doses administered globally, persistent post-vaccination symptoms, termed post-COVID-19 vaccine syndrome (PCVS), resemble post-acute sequelae of COVID-19 (PASC). Symptoms like cardiac, vascular, and neurological issues often emerge shortly after vaccination and persist for months to years, mirroring PASC. We previously showed the S1 subunit of the SARS-CoV-2 spike protein persists in CD16+ monocytes after infection, potentially driving PASC. Approved vaccines (Pfizer, Moderna, Janssen, AstraZeneca) deliver synthetic S1 to elicit immunity, suggesting a shared mechanism. We hypothesized that vaccine-derived S1 persistence in CD16+ monocytes sustains inflammation akin to PASC, contributing to PCVS. We studied 50 individuals with PCVS symptoms lasting over 30 days post-vaccination and 26 asymptomatic controls, using (1) machine learning-based immune profiling to compare cytokine signatures with PASC, (2) flow cytometry to detect S1 in CD16+ monocytes, and (3) LC-MS to confirm S1 across vaccine types. We correlated S1 persistence with symptom duration and inflammation. Prior infection was excluded via clinical history, anti-nucleocapsid antibody tests, and T-detect assays, though definitive tests are lacking. Preliminary findings suggest S1 persistence in CD16+ monocytes and an associated inflammatory profile may contribute to PCVS. Further studies are needed to confirm causality and prevalence. SARS CoV-2 S1 Protein in CD16+ Monocytes in Post-COVID-19 Vaccine Syndrome (PCVS).

SARS-Cov-2 proteins: a comparison with ACE2 protein

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

Coronaviruses (CoVs) [E1] are a diverse group of enveloped, plus-stranded RNAviruses that infect humans and many animal species, in which they can causerespiratory, enteric, hepatic, central nervous system and neurologicaldiseases of varying severity. A CoV contains four structural proteins,including spike (S), envelope (E), membrane (M), and nucleocapsid (N)proteins. Among them, the S protein, which is located on the envelope surfaceof the virion, functions to mediate receptor recognition and membrane fusionand is therefore a key factor determining the virus tropism for a specificspecies. This protein is composed of an N-terminal receptor-binding domain(S1) and a C-terminal trans-membrane fusion domain (S2) .The S2 subunit contains two 4-3 heptad repeats (HRs) of hydrophobic residues,HR1 and HR2, typical of coiled coils, separated by an ~170-aa-long interveningdomain. The S2 subunit is expected to present rearrangement of its HRs to forma stable 6-helix bundle fusion core .HR1 forms a 24-turn alpha-helix, while HR2 adopts a mixed conformation: thecentral part fold into a nine-turn alpha-helix, while the residues on eitherside of the helix adopt an extended conformation. The HR1 region forms a longtrimeric helical coiled-coil structure with peptides from the HR2 regionpacking in an oblique antiparallel manner on the grooves of the HR1 trimer ina mixed extended and helical conformation. Packing of thehelical parts of HR2 on the HR1 trimer grooves and formation of a six-helicalbundle plays an important role in the formation of a stable post-fusionstructure. In contrast to their extended helical conformations in the post-fusion state, the HR1 motifs within S2 form several shorter helices in theirpre-fusion state .The profiles we developed cover the entire CoV S2-HR1 -HR2 regions.

The map shows the 7-day incidence of confirmed cases of COVID-19 in the Austrian districts on a daily basis since the data were available (26 February 2020) and puts them in relation to the political targets.

The type I glycoprotein S of Coronavirus, trimers of which constitute the typical viral spikes, is assembled into virions through noncovalent interactions with the M protein. The spike glycoprotein is translated as a large polypeptide that is subsequently cleaved to S1 ([interpro:IPR002551]) and S2 . The cleavage of S can occur at two distinct sites: S2 or S2' . The spike is present in two very different forms: pre-fusion (the form on mature virions) and post-fusion (the form after membrane fusion has been completed). The spike is cleaved sequentially by host proteases at two sites: first at the S1/S2 boundary (i.e. S1/S2 site) and second within S2 (i.e. S2' site). After the cleavages, S1 dissociates from S2, allowing S2 to transition to the post-fusion structure . Both chimeric S proteins appeared to cause cell fusion when expressed individually, suggesting that they were biologically fully active . The spike is a type I membrane glycoprotein that possesses a conserved transmembrane anchor and an unusual cysteine-rich (cys) domain that bridges the putative junction of the anchor and the cytoplasmic tail .SARS-CoV S is largely uncleaved after biosynthesis. It can be later processed by endosomal cathepsin L, trypsin, thermolysin, and elastase, which are shown to induce syncytia formation and virus entry. Other proteases that are of potential biological relevance in potentiating SARS-CoV S include TMPRSS2, TMPRSS11a, and HAT which are localized on the cell surface and are highly expressed in the human airway . The furin-like S2' cleavage site at KR/SF with P1 and P2 basic residues and a P2' hydrophobic Phe downstream of the IFP is identical between the SARS-CoV-2 and SARS-CoV. One or more furin-like enzymes would cleave the S2' site at KR/SF . Deletion of SARS-CoV-2 furin cleavage site suggests that it may not be required for viral entry but may affect replication kinetics and altered sites have been still seen proteolytically cleaved. Several substitutions within the S2' cleavage domain of SARS-COV-2 have been reported, including P812L/S/T, S813I/G, F817L, I818S/V, but further experimental study of their consequences and the replication properties of the altered viruses are required to understand the role of furin cleavage in SARS-CoV-2 infection and virulence .

SARS-CoV-2 spike antibody seropositivity and factors associated with seropositivity among persons with SARS-CoV-2 spike protein seropositivity among persons who completed at least a COVID-19 primary vaccination series and had no history of diagnosed SARS-CoV-2 infection, Kaiser Permanente Northern California, May 2021—January 2022.

This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 Spike S2 fragment in its postfusion form (PDB id: 6M1V). 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 Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020.

The files 6M1V_SIRAHcg_rawdata_0-5us.tar, and 6M1V_SIRAHcg_rawdata_5-10us.tar, contain all the raw information required to visualize (on VMD 1.9.3), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com.

Additionally, the file 6M1V_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6LU7_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns.

To take a quick look at the trajectory:

1- Untar the file 6M1V_SIRAHcg_10us_prot_skip10ns.tar

2- Open the trajectory on VMD 1.9.3 using the command line:

vmd 6M1V_SIRAHcg_prot.prmtop 6M1V_SIRAHcg_prot.ncrst 6M1V_SIRAHcg_10us_prot_skip10ns.nc -e sirah_vmdtk.tcl

Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc.

This dataset is part of the SIRAH-CoV2 initiative.

For further details, please contact Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).

The dataset contains a total of 40 snapshots of the four trajectories (10 snapshots each system = two per replica x 5 replicas/system):

1. SARS-CoV-2002 spike protein without ACE2
2. SARS-CoV-2 spike protein without ACE2
3. SARS-CoV-2002 spike protein with ACE2
4. SARS-CoV-2 spike protein with ACE2

Molecular dynamics simulation trajectories (320ns each) have been performed using the Amber ff14SB force field running with the Amber18 package at the the NSF-funded (OAC-1826915, OAC-1828163) ELSA high performance computing cluster at The College of New Jersey. Under the following simulation methodology:

All-atom simulations were carried out with Amber18 (ambermd.org), and system components (protein, ions, water) were modeled with the included FF14SB and TIP3P parameter sets. Energy minimization used CPU pmemd, while later simulation stages used GPU pmemd. CoV2 and CoV1 systems with one RBD up (with/without ACE2) were solvated in 12 angstrom water shells. Cysteine residues identified in the initial models as having a disulfide bond (DB) were bonded using tLeap. All simulations used 0.150 M NaCl. Hydrogen mass repartitioning was applied only to the protein to enable a 4 fs timestep (https://pubs.acs.org/doi/abs/10.1021/ct5010406). The SHAKE algorithm was applied to hydrogens, and a real-space cutoff of 8 angstroms was used. Periodic boundary conditions were applied and PME was used for long-range electrostatics. Minimization was by steepest descent (2000 steps) followed by conjugate gradient (3000 steps). Heating used two stages: (1) NVT heating from 0 K to 100 K (50 ps), and (2) NPT heating from 100 K to 300 K (100 ps). Restraints of 10 kcal mol^-1 angstrom^-2 were applied during minimization and heating to C-alpha atoms. During 6 ns of equilibration at 300 K C-alpha restraints were gradually reduced from 10 kcal mol^-1 angstrom^-2 to 0.1 kcal mol^-1 angstrom^-2. Finally, restraints were released and 320 ns unrestrained production simulations were carried out for CoV2 and CoV1 systems. Production simulations began from the final equilibrated snapshots, and five copies of each system were simulated. As unrestrained systems can freely rotate we monitored simulations for any close contacts and found that in one copy of the CoV1 simulation without ACE2 and one RBD up that a few contacts close to 8 angstrom occur near the end of the 320 ns between the RBD and a different subdomain of the spike complex in a periodic image. However this did not influence analyzed structural properties which is verified by comparing results across simulations. The Monte Carlo barostat was used to maintain pressure (1 atm), and the Langevin thermostat was used to maintain 300 K temperature (collision frequency 1 ps^-1), as implemented in Amber18. In aggregate, nearly 7 microseconds of simulation of systems ranging from 396,147 to 879,100 atoms was carried out for this work.
For further details on the trajectories, please contact Joseph Baker (bakerj@tcnj.edu).

Regarding the contact map analysis scripts (contactMaps_Analysis.tar.gz), they contain the following workflow:

contactmap --> source files from contact_map executable
process_nc.sh --> convert raw data from all-atom simulation to numbered PDB files and get the contact maps
frequency.lua --> read a set of PDB files and output the frequency count for each contact
consensus.fasta --> align sequence of Covid19 and SARS from Chimera
consensus.lua --> read data previously generated and compute the frequency per residue, among other things.
consensus.sh --> input information to consensus.lua
consensus.gp --> gnuplot script to plot figures

This dataset and the code is part of tripartite collaboration between:

• The Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland (supported by the National Science Centre, Poland, under grant No. 2017/26/D/NZ1/0046)
• Department of Chemistry, The College of New Jersey, New Jersey, United States (supported by National Science Foundation under grant numbers OAC-1826915 and OAC-1828163).
• Jozef Stefan Institute, Ljubljana, Slovenia (supported by the Slovenian Research Agency (Funding No. P1-0055)).

The dataset of spike Covid proteins was obtained from GISAID. Each protein in the dataset is represented as a sequence of amino acids (AAs).

The coronavirus disease 2019 (COVID-19) pandemic is caused by a novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spike protein (S) of SARS-CoV-2 is a major target for diagnosis and vaccine development because of its essential role in viral infection and host immunity. Currently, time-dependent responses of humoral immune system against various S protein epitopes are poorly understood. In this study, enzyme-linked immunosorbent assay (ELISA), peptide microarray, and antibody binding epitope mapping (AbMap) techniques were used to systematically analyze the dynamic changes of humoral immune responses against the S protein in a small cohort of moderate COVID-19 patients who were hospitalized for approximately two months after symptom onset. Recombinant truncated S proteins, target S peptides, and random peptides were used as antigens in the analyses. The assays demonstrated the dynamic IgM- and IgG recognition and reactivity against various S protein epitopes with patient-dependent patterns. Comprehensive analysis of epitope distribution along the spike gene sequence and spatial structure of the homotrimer S protein demonstrated that most IgM- and IgG-reactive peptides were clustered into similar genomic regions and were located at accessible domains. Seven S peptides were generally recognized by IgG antibodies derived from serum samples of all COVID-19 patients. The dynamic immune recognition signals from these seven S peptides were comparable to those of the entire S protein or truncated S1 protein. This suggested that the humoral immune system recognized few conserved S protein epitopes in most COVID-19 patients during the entire duration of humoral immune response after symptom onset. Furthermore, in this cohort, individual patients demonstrated stable immune recognition to certain S protein epitopes throughout their hospitalization period. Therefore, the dynamic characteristics of humoral immune responses to S protein have provided valuable information for accurate diagnosis and immunotherapy of COVID-19 patients.

Molecular dynamics trajectory data of the SARS-CoV-2 (COVID-19) spike protein. The spike protein is a major target for vaccine development.

Datasets include: - 2 x 0.2 µs trajectories of WT prefusion spike protein with site-specific glycans in GROMACS format - 2 x 0.2 µs trajectories of D614G prefusion spike protein with site-specific glycans in GROMACS format - CHARMM-GUI generated GROMACS topologies - GROMACS tpr and checkpoint files for continuing the simulations - Video renderings (protein chains in gray, cyan, and magenta; glycans in yellow)

The prefusion spike protein structure used is based on 6VSB (single RBD in the up conformation) with site-specific glycans, see https://www.biorxiv.org/content/10.1101/2020.04.07.030445v1.full.

Simulation details: CHARMM36m force field with CHARMM modified TIP3P water model, and 0.15 M NaCl. Equilibration and production (310 K, NPT) were performed with CHARMM-GUI files.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease-19 (COVID-19). The spike protein (S) of SARS-CoV-2 plays a crucial role in mediating viral infectivity; hence, in an extensive effort to curb the pandemic, many urgently approved vaccines rely on the expression of the S protein, aiming to induce a humoral and cellular response to protect against the infection. Given the very limited information about the effects of intracellular expression of the S protein in host cells, we aimed to characterize the early cellular transcriptomic changes induced by expression of the S protein in THP-1-derived macrophage-like cells. Results showed that a wide variety of genes were differentially expressed, products of which are mainly involved in cell adhesion, homeostasis, and most notably, antiviral and immune responses, depicted by significant downregulation of protocadherins and type I alpha interferons (IFNAs). While initially, the levels of IFNAs were higher in the medium of S protein expressing cells, the downregulation observed on the transcriptomic level might have been reflected by no further increase of IFNA cytokines beyond the 5 h time-point, compared to the mock control. Our study highlights the intrinsic pathogenic role of the S protein and sheds some light on the potential drawbacks of its utilization in the context of vaccination strategies.

The type I glycoprotein S of Coronavirus, trimers of which constitute the typical viral spikes, is assembled into virions through noncovalent interactions with the M protein. The spike glycoprotein is translated as a large polypeptide that is subsequently cleaved to S1 and S2 [interpro:IPR002552] . Both chimeric S proteins appeared to cause cell fusion when expressed individually, suggesting that they were biologically fully active . The spike is a type I membrane glycoprotein that possesses a conserved transmembrane anchor and an unusual cysteine-rich (cys) domain that bridges the putative junction of the anchor and the cytoplasmic tail .

This dataset contains an updated trajectory of a four microseconds-long coarse-grained molecular dynamics simulation of the hexameric complex between SARS-CoV2 Spike´s RBD, ACE2, and B0AT1 (PDB id: 6M17). It substitutes the previous one on the same system, which was performed in the absence of disulfide bridges.

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 Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. Zinc ions were parameterized as reported in Klein et al. 2020.

The files 6M17_SIRAHcg_rawdata_0-1.tar, 6M17_SIRAHcg_rawdata_1-2.tar, 6M17_SIRAHcg_rawdata_2-3.tar, and 6M17_SIRAHcg_rawdata_3-4.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 SirahTools can be found at www.sirahff.com.

Additionally, the file 6M17_SIRAHcg_4us_prot.tar contains only the protein coordinates, while 6M17_SIRAHcg_4us_prot_skip10ns.tar contains one frame every 10ns.

To take a quick look at the trajectory:

1- Untar the file 6M17_SIRAHcg_4us_prot_skip10ns.tar

2- Open the trajectory on VMD 1.9.3 using the command line:

vmd 6M17_SIRAHcg_prot.prmtop 6M17_SIRAHcg_prot.ncrst 6M17_SIRAHcg_4usprot_skip.nc -e sirah_vmdtk.tcl

Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc.

This dataset is part of the SIRAH-CoV2 initiative.

For further details, please contact Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).

PDBs were generated using molecular dynamics. See DESRES_README.txt for more details on molecular dynamics simulation. PDBs were converted to volumetric data using EMAN2. The image stack contains 100 000 projection images each of the 10 states (see PDBs), at an SNR of 1/10 in the following order: state00 (closed) state01 (closed) state02 (closed) state10 (intermediate) state11 (intermediate) state12 (intermediate) state13 (intermediate) state20 (open) state21 (open) state22 (open) Projections were made using relion_project. White gaussian noise with standard deviation 1.0 CTF multiplied signal High signal-to-noise ratio Image size 96x96x96 MRC-files used for the projections not included, but can be generated using the PDB files. Final RELION reconstruction resolution is 5.33334 Angstrom (Nyqvist is at 5.33334). Command line for RELION reconstruction: relion_refine_mpi --o refine3d/run --auto_refine --split_random_halves --i rot_trans_ctf_noise/stack.star --ref pdb2mrc/state21.mrc --ini_high 20 --dont_combine_weights_via_disc --preread_images --pool 30 --pad 2 --ctf --particle_diameter 130 --flatten_solvent --zero_mask --oversampling 1 --healpix_order 2 --auto_local_healpix_order 4 --offset_range 5 --offset_step 2 --low_resol_join_halves 40 --norm --scale --j 2 --gpu --fristiter_cc --grad This dataset is generated as a testbed for cryo-EM heterogeneity analysis.

The Spike (S) protein of the SARS-CoV-2 virus is critical for its ability to attach and fuse into the host cells, leading to infection, and transmission. In this review, we have initially performed a meta-analysis of keywords associated with the S protein to frame the outline of important research findings and directions related to it. Based on this outline, we have reviewed the structure, uniqueness, and origin of the S protein of SARS-CoV-2. Furthermore, the interactions of the Spike protein with host and its implications in COVID-19 pathogenesis, as well as drug and vaccine development, are discussed. We have also summarized the recent advances in detection methods using S protein-based RT-PCR, ELISA, point‐of‐care lateral flow immunoassay, and graphene-based field-effect transistor (FET) biosensors. Finally, we have also discussed the emerging Spike mutants and the efficacy of the Spike-based vaccines against those strains. Overall, we have covered most of the recent advances on the SARS-CoV-2 Spike protein and its possible implications in countering this virus.