Purpose: Pandemic Novel Coronavirus (SARS-CoV-2) has emerger centered from wuhan, China. Structurally homologous spike protein of SARS-CoV-2 receptor is taxonomically homologous with SARS-Cov and SARS associated bat coronavirus. Still now scientists are trying to find out proper vaccine and treatments for this disease. Methods: Systematically we modeled and compared the structure of SARS-CoV-2 spike protein along with Bat Cov, Bat SARS Cov and SARS Cov Urbani. S1 and S2 unit of the coronavirus (SARS-CoV-2) are attached with ACE2 and furin, here we docked 5 Ca+ chelating drugs with these two proteins. Results: Structural comparison with all these spike proteins revealed that less significant but not negligible difference exists among them. Inserted stable nucleotide sequences and corresponding surface exposed peptidal region may be considered as epitope. Docking result with Toxicokinetics and half life of Penicillamine can effectly inhibit the attachment site of spike protein of coronavirus (SARS-CoV-2). Conclusions: Docking summery and the pharmacokinetics with toxicokinetics index recommend that Penicillamine can able to inhibit the infection of SARS-CoV-2.

SARS CoV-2 or COVID-19 pandemic global-outbreak created the most unstable situation of human health-economy. Last two decades different parts of the word experienced smaller or bigger outbreak related to human-coronaviruses. The spike-glycoproteins of the COVID-19 (similar to SARS-CoV) attach to the angiotensin-converting-enzyme (ACE-2) and transit over a stabilized open-state for the viral-internalization to the host-cells and propagate with great efficacy. Higher rate of mutability makes this virus unpredictable/less-sensitive to the protein/nucleic-acid based-drugs. In this emergent situation, drug-induced destabilization of spike-binding to RBD could be a good strategy. In the current study we demonstrated by Bioinformatics (CASTp: Computed-Atlas-of-Surface-Topography, PyMol: molecular-visualization) and Molecular docking (PatchDock) experiments that tea flavonoids catechin-products mainly EGCG or other like theaflavin gallate demonstrated higher Atomic Contact Energy (ACE), surface area and more amino-acid interactions than hydroxychloroquine (HCQ) during binding in the central channel of the spike-protein. Moreover, out of three distinct binding-sites (I, II and III) of spike core when HCQ binds only with site III (farthest from the vCoV-RBD of ACE2 contact), EGCG and TG bind all three sites. As because site I and II is in closer contact with open state location and viral-host contact area so these drugs might have significant effects. Taking into account the toxicity/side-effects by CQ/HCQ, present drugs may be important. Our laboratory is working on tea flavonoids and other phytochemicals in the protection from toxicity, DNA/mitochondrial damage, inflammation etc. The present data might be helpful for further analysis of flavonoids in this emergent pandemic situation.

SARS-CoV2 popularly known as (COVID-19) has presently received worldwide attention. It has been considered a pandemic by the World Health Organisation. Owing to its high transmittance factor the virus has brought about many deaths and spread to all the major countries of the world. Scientists and Researchers worldwide are giving their full efforts to develop a vaccine. In our present study, we have included the comparative analysis of the different spike glycoprotein sequences of the patients suffering from COVID-19 from different countries where this pandemic has occurred. Spike glycoproteins are the structural proteins that bring about the binding of the SARS-CoV-2 viral molecule to the ACE2 receptor of the host following which infection occurs. Through this data, we have shown the different point mutations in the spike glycoproteins that occurred over time in different countries as the disease progressed.

Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has high infectivity in humans, attributed to the strong affinity of its spike (S) protein to human angiotensin-converting enzyme 2 (ACE2). Here, we analyzed the structural similarity of the S protein between SARS-CoV-2 and other SARS-related coronaviruses (CoVs). Methods We performed multiple alignment analysis of nine amino acid sequences of CoV S proteins from NCBI with MAFFT web-based software, followed by phylogeny analysis. Three-dimensional structure modeling was performed by SWISS-MODEL. We calculated the template modeling score between the S protein of SARS-CoV-2 and that of other SARS-related CoVs. Results The S1 domain of the unclassified CoV RaTG13 (the host of which is the intermediate horseshoe bat) was structurally very similar to that of SARS-CoV-2, implying that RaTG13 could be the origin of SARS-CoV-2. In addition, the folding property of the entire S protein was nearly the same between SARS-CoV-2 and RaTG13 after the PRRA amino acid insertion was removed from SARS-CoV-2. Conclusions RaTG13 could have a high binding affinity to ACE2, similar to SARS-CoV-2, and it is therefore highly likely to infect other animals. Therefore, massive research and monitoring of CoVs in animals is necessary to prevent future COVID-19-like disasters.

New coronavirus (SARS-CoV-2) treatments and vaccines are under development to combat the COVID-19 disease. Several approaches are being used by scientists for investigation including 1) various small molecule approaches targeting RNA polymerase, 3C-like protease, and RNA endonuclease and 2) exploration of antibodies obtained from convalescent plasma from patients who have recovered from COVID-19. The coronavirus genome is highly prone to mutations that lead to genetic drift and escape from immune recognition; thus, it is imperative that sub-strains with different mutations are also accounted for during vaccine development. As the disease has grown to become a pandemic, new B-cell and T-cell epitopes predicted from SARS coronavirus have been reported. Using the epitope information along with variants of the virus, we have found several variants which might cause drifts. Among such variants, 23403A>G variant (p.D614G) in spike protein B-cell epitope is observed frequently in European countries such as the Netherlands, Switzerland and France.

The novel coronavirus (SARS-CoV-2) is a human pathogen recently emerged in China, causing a global pandemic of severe respiratory illness (COVID19). SARS-CoV-2 makes entry into human cells through its spike (S) protein that binds to cell surface receptors. Widespread of SARS-CoV-2 has been attributed to high affinity of S protein to its receptor. A homology model of the receptor binding domain of SARS-CoV-2 S protein (RBD) was built. RBD- receptor docking and published molecular dynamics data were used to map the key RBD-receptor interaction hotspot (RBDhp) on the RBD. Primary virtual screening was carried out against RBDhp using more than 3300 compounds approved by U.S Food and Drug Administration (FDA) and other authorities for human use. Compounds that bind to hpRBD with a binding energy ≤ - 6.5 kcal/mol were subjected to secondary screening using a recently published cryo EM (2.9 Å) structure of RBD. A cardiac glycoside (dgitoxin), two anthracyclines (zorubicin and aclarubicin), a tetracycline derivative (rolitetracycline), a cephalosporin (cefoperazone) and a food dye (E-155) were predicted to be most potent inhibitors of RBD – receptor interaction. An anti-asthmatic drug (zafirlukast) and several other drugs (itrazol, fazadinium, troglitazone, gliquidone, Idarubicin, Oxacillin) were found to be high affinity binders that may have a potential to inhibit RBD – receptor interaction.

We are witnessing the severe third outbreak mediated by coronaviruses affecting global public health with unprecedented economic consequences. A better understanding of its phylogenetics, exploration of sequence features and mutational changes could unveil its genealogy to gain insights into the mechanism of transmission and development of possible interventions. Our comparative genomic analyses of >160 isolates of SARS-CoV-2 reveal phylogenetic kinship with other coronaviruses and emergence of evolutionary divergence in clinical isolates. t-SNE-based clustering revealed different clades but no continent specific clusters. Amino acid substitutions at RBD of spike protein provide possible reasons for rapid transmission. Few proteins specific to SARS-CoV-2 were identified which could have implications as therapeutic targets and diagnostic biomarkers. Virtual screening identified repurposed drugs, known nutraceuticals, for specific interventions. These phylogenetic observations reveal the ancestry and computational studies reveal the emergency measures to interject this emerging pathogen that pose threat to whole of mankind.

SARS-CoV2 (corona virus) has spread globally at an unprecedented rate; so far, increasing SARS-CoV2-infected individuals have been identified. Although the situation in China is improving and is currently under control, the outbreak in other countries and its pandemic management is only beginning to develop. Based on 154 SARS-CoV2 genome sequence analyses, we used receptor–ligand docking to identify one potential point mutation (V354F) on the spike structure which enhances spike binding to ACE2 receptors underlying potential super infection. Importantly, the V354F site on spike S1 had been identified in 5/10 infected French patients living in Paris, who sharing 100% identical SARS-CoV2 genomes. With Covid-19 cases increasing rapidly in France that could lead to a new explosion, we suggest that the French government should identify all potential super spreaders and treat them accordingly. In summary, our study provides on of the measures to avoid the potential second worldwide explosion of SARS-CoV2.

The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the world health organization declared it pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. In this urgency situation, development of SARS-CoV-2 based vaccines is immediately required. Immunoinformatic and molecular modelling are generally used time-efficient methods to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines is proved to be a promising immunization strategy against viruses and pathogens, which induce more comprehensive protective immunity. The current study demonstrated a comprehensive in-silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in-silico cloning in a known pET28a vector system also estimated the possibility of MVC expression in E. Coli. Despite this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can present to be a better prophylactic solution against COVID-19.

A novel coronavirus (2019-nCoV) that is initially found to trigger human severe respiratory illness in Wuhan City of China, 2019, has been recognized as a public health emergency of international concern. In the past two months, this deadly agent has caused 77,785 cases with 2,666 deaths via rapid person-to-person transmission and reached at least 25 countries. However, its evolutionary origin is poorly understood. Here we show integrative evidence that 2019-nCoV is a possible progenitor for SARS-CoV with bat origin. Our finding underscores the importance of tracing origin in the efficient monitoring, and effectively preventing the interspecies transmission of such emerging/re-emerging coronaviruses.

In previous work, a quantum mathematical formalism associated an element of experience with a single sensory neuron, as a local reduction of a global mental state. In contrast to the binary objective states of neuronal polarisation/depolarisation, neuronal experience was modeled as a continuous variable, the instantaneous value of which could only be estimated statistically from an ensemble of evoked responses to stereotyped stimulus presentation. In the present work, the quantum operations formalism of energy dissipation through amplitude damping is adopted to explain how smooth evolution of conscious experience might arise from discrete spikes and discontinuous synaptic transmission between neurons.

Pneumonia caused by a new coronavirus SARS-CoV-2 has caused serious harm to people's lives and health in Wuhan, China. By February 26, 2020, over 80,000 people were infected and 2,814 died from the infection. The initial route of infection is the binding of the spike protein (S protein) of the virus to the angiotensin-converting enzyme 2 (ACE2). From bioinformatics analysis, we found that the S protein of SARS-CoV-2 produced an evolutionary mutation of K403R compared with the S protein of SARS-CoV, forming an adjacent RGD motif at the interaction surface. As the RGD motif is considered as a ligand for many cell surface integrins, we proposed that the binding of S protein of SARS-CoV-2 with integrins may facilitate the infection process of the virus. Therefore, high-throughput virtual screening was performed by choosing the key residues of S protein interface of SARS-CoV-2 and the adjacent RGD motif as potential binding site, to search for the potential agents targeting interaction of S protein of SARS-CoV-2 with both ACE2 and integrins as potential therapeutic drugs. Various libraries including the FDA-approved drugs etc. were screened, and Nadide, Losartan, 9'''-Methyllithospermate B and Leonurine etc. were identified as representative potential drugs candidate for COVID-19.

The spike protein of SARS coronavirus (SARS-CoV) attaches the virus to its cellular receptor, angiotensin-converting enzyme 2 (ACE2), which is mediated by the receptor binding domain (RBD) of the spike protein. Recently, an analysis based on decade-long structural studies of SARS was reported to illustrate with atomic-level details receptor recognition by the novel coronavirus from Wuhan, i.e., 2019-nCoV. Here, this article reports a comprehensive set of structural electrostatic analysis of all SARS-CoV spike protein RBD-related structures as of February 13, 2020, aiming at identifying the electrostatic hot spots for SARS-CoV spike protein to be complexed with ACE2 and its neutralizing antibodies. First, this article identified a structural action mechanism of the F26G19 antibody (of SARS-CoV spike protein), where its Asp56 residue binds to the Arg426 of the SARS-CoV spike protein RBD against the formation of the interfacial Arg426-Glu329 salt bridges between ACE2 and the SARS-CoV spike protein RBD. Second, a hypothesis is reported that a pair of electrostatic clips exist at the interface between ACE2 and the SARS-CoV spike protein RBD, including both Arg426-Glu329 and His445-Glu23-Lys447 salt bridges. Last, this article reports a structurally identified interfacial Glu35-Arg479 salt bridge which helps stabilize the complex structure of ACE2 and the SARS-CoV spike protein RBD. Overall, the structurally identified electrostatic hot spots reported here may be useful for the design of SARS-CoV-neutralizing antibodies in future.

The recent outbreak of the new virus in Wuhan city, China from the sea food market has led to the identification of a new strain called the corona virus and named as novel corona virus (2019-nCoV) belonging to Coronaviridae family. This has created major havoc and concern due to the mortality of 250 persons and affecting more than 10,000 people. This virus causes sudden fever, pneumonia and also kidney failure. In this study a computational approach is proposed for drug and vaccine design. The spike protein sequences were collected from a protein database and analysed with various bioinformatics tools to identify suitable natural inhibitors for the N-terminal receptor binding domain of spike protein. Also, it is attempted to identify suitable vaccine candidates by identifying B-Cell and T-cell epitopes. In the drug design, the tanshinone Iia and methyl Tanshinonate were identified as natural inhibitors based on the docking score. In the vaccine design, B-cell epitope VLLPLVSSQCVNLTTRTQLPPAYTN was found to have the highest antigenicity. FVFLVLLPL of MHC class-I allele and FVFLVLLPL of MHC class-II allele were identified as best peptides based on a number of alleles and antigencity scores. The present study identifies natural inhibitors and putative antigenic epitopes which may be useful as effective drug and vaccine candidates for the eradication of novel corona virus.

Although most biological processes are characterized by a strong temporal asymmetry, several popular mathematical models neglect this issue. Maximum entropy methods provide a principled way of addressing time irreversibility, which leverages powerful results and ideas from the3literature of non-equilibrium statistical mechanics. This article provides a comprehensive overview of these issues, with a focus in the case of spike train statistics. We provide a detailed account of the5mathematical foundations and work out examples to illustrate the key concepts and results from non-equilibrium statistical mechanics

Spike shape and morphometric characteristics are among the key characteristics of cultivated cereals associated with their productivity. Identification of the genes controlling these traits requires morphometric data harvesting and analysis for numerous plants, which is automatable using technologies of digital image analysis. A method for wheat spike morphometry utilizing 2D image analysis is proposed. Digital images are acquired in two variants: a spike on a table (one projection) or fixed with a clip (four projections). The method identifies spike and awns in the image and estimates their quantitative characteristics (area in image, length, width, circularity, etc.). Models of sections, quadrilaterals, and radial model are proposed for describing spike shape. Parameters of these models are used to predict spike shape type (spelt, normal, or compact) by machine learning. The mean error in spike density prediction for the images in one projection is 4.61 (~18%) versus 3.33 (~13%) for the parameters obtained using four projections. F1 measure in automated spike classification into three types is 0.78 using logistic regression (one projection) and 0.85 using random forest method (four projections). The proposed method is implemented in Java; examples of images and user guide are available at http://wheatdb.org/werecognizer.

Base on the sequence of S genes, which encode spike proteins, we previously identified three different types (North American, S INDEL and S large-DEL types) of porcine epidemic diarrhea virus (PEDV) that have re-emerged in Japan since 2013. Base on experimental infections with the North American and S large-DEL types, we also hypothesized that PEDV virulence may be linked to the S1 subunit of the S protein. To test this hypothesis, we have now assayed in gnotobiotic piglets various recombinant PEDVs generated by reverse genetics. Piglets inoculated with CV777 maintained in National Institute of Animal Health, along with piglets infected with a recombinant form of the same virus, developed subclinical to mild diarrhea. In contrast, severe watery diarrhea, dehydration, weight loss, astasia, and high mortality were observed in piglets inoculated with recombinant strains in which the S gene was partially or fully replaced with corresponding sequences from the highly virulent Japanese PEDV isolate OKN-1/JPN/2013. Indeed, symptoms resembled those in piglets inoculated with the OKN-1/JPN/2013, and were especially pronounced in younger piglets. Collectively, the data demonstrate that the S1 subunit of the S protein is an important determinant of PEDV virulence, and advance development of new vaccine candidate.

We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. We review large deviations techniques useful in this context to describe properties of accuracy and convergence in terms of sampling size. We use these results to study the statistical fluctuation of correlations, distinguishability and irreversibility of maximum entropy Markov chains. We illustrate these applications using simple examples where the large deviation rate function is explicitly obtained for maximum entropy models of relevance in this field.

Experimental recordings of the collective activity of interacting spiking neurons exhibit random behavior and memory effects, thus the stochastic process modeling the spiking activity is expected to show some degree of time irreversibility. We use the thermodynamic formalism to build a framework, in the context of spike train statistics, to quantify the degree of irreversibility of any parametric maximum entropy measure under arbitrary constraints, and provide an explicit formula for the information entropy production of the inferred Markov maximum entropy process. We provide examples to illustrate our results and discuss the importance of time irreversibility for modeling the spike train statistics.