Computers and viral diseases. Preliminary bioinformatics studies on the design of a synthetic vaccine and a preventative peptidomimetic antagonist against the SARS-CoV-2 (2019-nCoV, COVID-19) coronavirus

Mutations of SARS-CoV-2 spike protein: Implications on immune evasion and vaccine-induced immunity

Responsible for more than 4.9 million deaths so far, COVID-19, caused by SARS-CoV-2, is instigating devastating effects on the global health care system whose impacts could be longer for the years to come. Acquiring a comprehensive knowledge of host-virus interaction is critical for designing effective vaccines and/or drugs. Understanding the evolution of the virus and the impact of genetic variability on host immune evasion and vaccine efficacy is helpful to design novel strategies to minimize the effects of the emerging variants of concern (VOC). Most vaccines under development and/or in current use target the spike protein owning to its unique function of host receptor binding, relatively conserved nature, potent immunogenicity in inducing neutralizing antibodies, and being a good target of T cell responses. However, emerging SARS-CoV-2 strains are exhibiting variability on the spike protein which could affect the efficacy of vaccines and antibody-based therapies in addition to enhancing viral immune evasion mechanisms. Currently, the degree to which mutations on the spike protein affect immunity and vaccination, and the ability of the current vaccines to confer protection against the emerging variants attracts much attention. This review discusses the implications of SARS-CoV-2 spike protein mutations on immune evasion and vaccine-induced immunity and forward directions which could contribute to future studies focusing on designing effective vaccines and/or immunotherapies to consider viral evolution. Combining vaccines derived from different regions of the spike protein that boost both the humoral and cellular wings of adaptive immunity could be the best options to cope with the emerging VOC.

A novel DeepNet model for the efficient detection of COVID-19 for symptomatic patients

The novel Coronavirus (COVID-19) disease has disrupted human life worldwide and put the entire planet on standby. A resurgence of coronavirus infections has been confirmed in most countries, resulting in a second wave of the deadly virus. The infectious virus has symptoms ranging from an itchy throat to Pneumonia, resulting in the loss of thousands of human lives while globally infecting millions. Detecting the presence of COVID-19 as early as possible is critical, as it helps prevent further spread of disease and helps isolate and provide treatment to the infected patients. Recent radiological imaging findings confirm that lung X-ray and CT scans provide an excellent indication of the progression of COVID-19 infection in acute symptomatic carriers. This investigation aims to rapidly detect COVID-19 progression and non-COVID Pneumonia from lung X-ray images of heavily symptomatic patients. A novel and highly efficient COVID-DeepNet model is presented for the accurate and rapid prediction of COVID-19 infection using state-of-the-art Artificial Intelligence techniques. The proposed model provides a multi-class classification of lung X-ray images into COVID-19, non-COVID Pneumonia, and normal (healthy). The proposed systems’ performance is assessed based on the evaluation metrics such as accuracy, sensitivity, precision, and f1 score. The current research employed a dataset size of 7500 X-ray samples. The high recognition accuracy of 99.67% was observed for the proposed COVID-DeepNet model, and it complies with the most recent state-of-the-art. The proposed COVID-DeepNet model is highly efficient and accurate, and it can assist radiologists and doctors in the early clinical diagnosis of COVID-19 infection for symptomatic patients.

DNA vaccination induced protective immunity against SARS CoV-2 infection in hamsterss

The development of efficient vaccines against COVID-19 is an emergent need for global public health. The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major target for the COVID-19 vaccine. To quickly respond to the outbreak of the SARS-CoV-2 pandemic, a nucleic acid-based vaccine is a novel option, beyond the traditional inactivated virus vaccine or recombinant protein vaccine. Here, we report a DNA vaccine containing the spike gene for delivery via electroporation. The spike genes of SARS-CoV and SARS-CoV-2 were codon optimized for mammalian cell expression and then cloned into mammalian cell expression vectors, called pSARS-S and pSARS2-S, respectively. Spike protein expression was confirmed by immunoblotting after transient expression in HEK293T cells. After immunization, sera were collected for antigen-specific antibody and neutralizing antibody titer analyses. We found that both pSARS-S and pSARS2-S immunization induced similar levels of antibodies against S2 of SARS-CoV-2. In contrast, only pSARS2-S immunization induced antibodies against the receptor-binding domain of SARS-CoV-2. We further found that pSARS2-S immunization, but not pSARS-S immunization, could induce very high titers of neutralizing antibodies against SARS-CoV-2. We further analyzed SARS-CoV-2 S protein-specific T cell responses and found that the immune responses were biased toward Th1. Importantly, pSARS2-S immunization in hamsters could induce protective immunity against SARS-CoV-2 challenge in vivo. These data suggest that DNA vaccination could be a promising approach for protecting against COVID-19.

Exploring the Capability of Indonesia Natural Medicine Secondary Metabolite as Potential Inhibitors of SARS-CoV-2 Proteins to Prevent Virulence of COVID-19: In silico and Bioinformatic Approach

BACKGROUND: SARS-CoV-2 was causing COVID-19 disease resulting in many deaths and being a significant concern in the world today. There is an emergent need to search for possible medications for COVID-19 treatment. The key point to halt SARS-CoV-2 infection through inhibition of the virus-receptor interaction and stimulates the immune system. Utilization of the bioinformatic and in silico molecular docking a number of available medications might be proven to be effective in inhibiting SARS-CoV-2 main drug targets including the SARS-CoV2 spike glycoprotein, the 3CL protease SARS-CoV-2 active target, PD-ACE2, 2019-nCoV PLpro, and NF-kβ. AIM: This present study was conducted to identify the potential target and molecular mechanism of the major compound on Alpinia galanga extract and Citrus sinensis (L.) extract in circumventing COVID-19 using a bioinformatics approach and in silico molecular docking. RESULTS: Direct protein target of all secondary metabolite and the gene list from PubMed “Severe acute respiratory syndrome coronavirus 2” generated 2 genes (CCL2 and VEGFA) as potential therapeutics target genes (PTTG). The molecular docking was conducted by the Protein-Ligand Ant System (PLANTS) software. The results show that hesperidin, naringenin, and galangin have lower docking score for all five-protein target receptor compared with chloroquine and remdesivir. The lower docking score suggests a high affinity to bind the protein. Moreover, these compounds have a strong affinity in their inhibitory capacity for viral infection. CONCLUSION: In general, this study’s findings show that the compound of Alpinia galanga extract dan Citrus sinensis (L.) extract exhibit the best potential as an inhibitor to the development of the SARS-CoV-2 and inhibited cytokine storm through inactivation NF-kβ _pathway.

Global dynamics of SARS-CoV-2 clades and their relation to COVID-19 epidemiology

Expansion of COVID-19 worldwide increases interest in unraveling genomic variations of novel SARS-CoV-2 virus. Metadata of 408,493 SARS-CoV-2 genomes submitted to GISAID database were analyzed with respect to genomic clades and their geographic, age, and gender distributions. Of the currently known SARS-CoV-2 clades, clade GR was the most prevalent worldwide followed by GV then GH. Chronological analysis revealed expansion in SARS-CoV-2 clades carrying D614G mutations with the predominance of the newest clade, GV, in the last three months. D614G clades prevail in countries with more COVID-19 cases. Of them, the clades GH and GR were more frequently recovered from severe or deceased COVID-19 cases. In contrast, G and GV clades showed a significantly higher prevalence among asymptomatic patients or those with mild disease. Metadata analysis showed higher (p < 0.05) prevalence of severe/deceased cases among males than females and predominance of GR clade in female patients. Furthermore, severe disease/death was more prevalent (p < 0.05) in elderly than in adults/children. Higher prevalence of the GV clade in children compared to other age groups was also evident. These findings uniquely provide a statistical evidence on the adaptation-driven evolution of SARS-CoV-2 leading to altered infectivity, virulence, and mortality.

Potential Leads from Liquorice Against SARS-CoV-2 Main Protease using Molecular Docking Simulation Studies

AIM AND OBJECTIVE

At present, the world is facing a global pandemic threat of SARSCoV- 2 or COVID-19 and to date, there are no clinically approved vaccines or antiviral drugs available for the treatment of coronavirus infections. Studies conducted in China recommended the use of liquorice (Glycyrrhiza species), an integral medicinal herb of traditional Chinese medicine, in the deactivation of COVID-19. Therefore, the present investigation was undertaken to identify the leads from the liquorice plant against COVID-19 using molecular docking simulation studies.

MATERIALS AND METHODS

A set of reported bioactive compounds of liquorice were investigated for COVID-19 main protease (M^pro) inhibitory potential. The study was conducted on Autodock vina software using COVID-19 M^pro as a target protein having PDB ID: 6LU7.

RESULTS

Out of the total 20 docked compounds, only six compounds showed the best affinity towards the protein target, which included glycyrrhizic acid, isoliquiritin apioside, glyasperin A, liquiritin, 1-methoxyphaseollidin and hedysarimcoumestan B. From the overall observation, glycyrrhizic acid followed by isoliquiritin apioside demonstrated the best affinity towards M^pro representing the binding energy of -8.6 and -7.9 Kcal/mol, respectively. Nevertheless, the other four compounds were also quite comparable with the later one.

CONCLUSION

From the present investigation, we conclude that the compounds having oxane ring and chromenone ring substituted with hydroxyl 3-methylbut-2-enyl group could be the best alternative for the development of new leads from liquorice plant against COVID-19.

A therapeutic journey of potential drugs against COVID-19

Coronavirus disease (CoVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) scrambles the world by infecting millions of peoples all over the globe. It has caused tremendous morbidity, mortality and greatly impacted the lives and economy worldwide as an outcome of mandatory quarantines or isolations. Despite the worsening trends of COVID-19, no drugs are validated to have significant efficacy in clinical treatment of COVID-19 patients in large-scale studies. Physicians and researchers throughout the world are working to understand the pathophysiology to expose the conceivable handling regimens and to determine the effective vaccines and/or therapeutic agents. Some of them re-purposed drugs for clinical trials which were primarily known to be effective against the RNA viruses including MERS-CoV and SARS-CoV-1. In the absence of a proven efficacy therapy, the current management use therapies based on antivirals, anti-inflammatory drugs, convalescent plasma, anti-parasitic agents in both oral and parenteral formulation, oxygen therapy and heparin support. What is needed at this hour, however, is a definitive drug therapy or vaccine. Different countries are rushing to find this, and various trials are already underway. We aimed to summarized the potential therapeutic strategies as a treatment options for COVID-19 that could be helpful to stop further spread of SARS-CoV-2 by effecting its structural components or modulation of immune response and also discusses the leading drugs/vaccines, which were considered as potential agents for controlling this pandemic.

Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Background

To contain the pandemics caused by SARS-CoV-2, early detection approaches with high accuracy and accessibility are critical. Generating an antigen-capture based detection system would be an ideal strategy complementing the current methods based on nucleic acids and antibody detection. The spike protein is found on the outside of virus particles and appropriate for antigen detection.

Methods

In this study, we utilized bioinformatics approaches to explore the immunodominant fragments on spike protein of SARS-CoV-2.

Results

The S1 subunit of spike protein was identified with higher sequence specificity. Three immunodominant fragments, Spike_56-94, Spike_199-264, and Spike_577-612, located at the S1 subunit were finally selected via bioinformatics analysis. The glycosylation sites and high-frequency mutation sites on spike protein were circumvented in the antigen design. All the identified fragments present qualified antigenicity, hydrophilicity, and surface accessibility. A recombinant antigen with a length of 194 amino acids (aa) consisting of the selected immunodominant fragments as well as a universal Th epitope was finally constructed.

Conclusion

The recombinant peptide encoded by the construct contains multiple immunodominant epitopes, which is expected to stimulate a strong immune response in mice and generate qualified antibodies for SARS-CoV-2 detection.

Tartary Buckwheat in Human Nutrition

Tartary buckwheat (Fagopyrum tataricum Gaertn.) originates in mountain areas of western China, and it is mainly cultivated in China, Bhutan, northern India, Nepal, and central Europe. Tartary buckwheat shows greater cold resistance than common buckwheat, and has traits for drought tolerance. Buckwheat can provide health benefits due to its contents of resistant starch, mineral elements, proteins, and in particular, phenolic substances, which prevent the effects of several chronic human diseases, including hypertension, obesity, cardiovascular diseases, and gallstone formation. The contents of the flavonoids rutin and quercetin are very variable among Tartary buckwheat samples from different origins and parts of the plants. Quercetin is formed after the degradation of rutin by the Tartary buckwheat enzyme rutinosidase, which mainly occurs after grain milling during mixing of the flour with water. High temperature treatments of wet Tartary buckwheat material prevent the conversion of rutin to quercetin.

Biological characteristics and biomarkers of novel SARS-CoV-2 facilitated rapid development and implementation of diagnostic tools and surveillance measures

Existing coronavirus named as a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has speeded its spread across the globe immediately after emergence in China, Wuhan region, at the end of the year 2019. Different techniques, including genome sequencing, structural feature classification by electron microscopy, and chest imaging using computed tomography, are primarily used to diagnose and screen SARS-CoV-2 suspected individuals. Determination of the viral structure, surface proteins, and genome sequence has provided a design blueprint for the diagnostic investigations of novel SARS-CoV-2 virus and rapidly emerging diagnostic technologies, vaccine trials, and cell-entry-inhibiting drugs. Here, we describe recent understandings on the spike glycoprotein (S protein), receptor-binding domain (RBD), and angiotensin-converting enzyme 2 (ACE2) and their receptor complex. This report also aims to review recently established diagnostic technologies and developments in surveillance measures for SARS-CoV-2 as well as the characteristics and performance of emerging techniques. Smartphone apps for contact tracing can help nations to conduct surveillance measures before a vaccine and effective medicines become available. We also describe promising point-of-care (POC) diagnostic technologies that are under consideration by researchers for advancement beyond the proof-of-concept stage. Developing novel diagnostic techniques needs to be facilitated to establish automatic systems, without any personal involvement or arrangement to curb an existing SARS-CoV-2 epidemic crisis, and could also be appropriate for avoiding the emergence of a future epidemic crisis.

Diffusion modeling of COVID-19 under lockdown

Viral immune evasion by sequence variation is a significant barrier to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine design and coronavirus disease-2019 diffusion under lockdown are unpredictable with subsequent waves. Our group has developed a computational model rooted in physics to address this challenge, aiming to predict the fitness landscape of SARS-CoV-2 diffusion using a variant of the bidimensional Ising model (2DIMV) connected seasonally. The 2DIMV works in a closed system composed of limited interaction subjects and conditioned by only temperature changes. Markov chain Monte Carlo method shows that an increase in temperature implicates reduced virus diffusion and increased mobility, leading to increased virus diffusion.

An Overview of Spike Surface Glycoprotein in Severe Acute Respiratory Syndrome-Coronavirus

The novel coronavirus originated in December 2019 in Hubei, China. This contagious disease named as COVID-19 resulted in a massive expansion within 6 months by spreading to more than 213 countries. Despite the availability of antiviral drugs for the treatment of various viral infections, it was concluded by the WHO that there is no medicine to treat novel CoV, SARS-CoV-2. It has been confirmed that SARS-COV-2 is the most highly virulent human coronavirus and occupies the third position following SARS and MERS with the highest mortality rate. The genetic assembly of SARS-CoV-2 is segmented into structural and non-structural proteins, of which two-thirds of the viral genome encodes non-structural proteins and the remaining genome encodes structural proteins. The most predominant structural proteins that make up SARS-CoV-2 include spike surface glycoproteins (S), membrane proteins (M), envelope proteins (E), and nucleocapsid proteins (N). This review will focus on one of the four major structural proteins in the CoV assembly, the spike, which is involved in host cell recognition and the fusion process. The monomer disintegrates into S1 and S2 subunits with the S1 domain necessitating binding of the virus to its host cell receptor and the S2 domain mediating the viral fusion. On viral infection by the host, the S protein is further cleaved by the protease enzyme to two major subdomains S1/S2. Spike is proven to be an interesting target for developing vaccines and in particular, the RBD-single chain dimer has shown initial success. The availability of small molecules and peptidic inhibitors for host cell receptors is briefly discussed. The development of new molecules and therapeutic druggable targets for SARS-CoV-2 is of global importance. Attacking the virus employing multiple targets and strategies is the best way to inhibit the virus. This article will appeal to researchers in understanding the structural and biological aspects of the S protein in the field of drug design and discovery.

Potential therapeutic agents to COVID-19: An update review on antiviral therapy, immunotherapy, and cell therapy

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, in December 2020 and coronavirus disease 19 (COVID-19) was later announced as pandemic by the World Health Organization (WHO). Since then, several studies have been conducted on the prevention and treatment of COVID-19 by potential vaccines and drugs. Although, the governments and global population have been attracted by some vaccine production projects, the presence of SARS-CoV-2-specific antiviral drugs would be an urge necessity in parallel with the efficient preventive vaccines. Various nonspecific drugs produced previously against other bacterial, viral, and parasite infections were recently evaluated for treating patients with COVID-19. In addition to therapeutic properties of these anti-COVID-19 compounds, some adverse effects were observed in different human organs as well. Not only several attentions were paid to antiviral therapy and treatment of COVID-19, but also nanomedicine, immunotherapy, and cell therapy were conducted against this viral infection. In this review study, we planned to introduce the present and potential future treatment strategies against COVID-19 and define the advantages and disadvantages of each treatment strategy.

Comparison of the SARS-CoV-2 (2019-nCoV) M protein with its counterparts of SARS-CoV and MERS-CoV species

Coronaviruses M proteins are well-represented in the major protein component of the viral envelope. During the viral assembly, they play an important role by association with all other viral structural proteins. Despite their crucial functions, very little information regarding the structures and functions of M proteins is available. Here we utilize bioinformatic tools from available sequences and 3D structures of SARS-CoV, SARS-CoV2, and MERS-CoV M proteins in order to predict potential B-cell epitopes and assessing antibody binding affinity. Such study aims to aid finding more effective vaccines and recognize neutralizing antibodies. we found some rather exciting differences between SARS-COV-2, SARS-Cov and MERS-CoV M proteins. Two SARS-CoV-2 peptides with significant antigen presentation scores for human cell surface proteins have been identified. The results reveal that N-terminal domains of M proteins of SARS-CoV and SARS-CoV2 are translocated (outside) whereas it is inside (cytoplasmic side) in MERS-CoV.

Functional and Structural Characterization of SARS-Cov-2 Spike Protein: An In Silico Study

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the global outbreak of coronavirus disease 2019 (Covid-19), which has been considered as a pandemic by WHO. SARS-CoV-2 encodes four major structural proteins, among which spike protein has always been a main target for new vaccine studies. This in silico study aimed to investigate some physicochemical, functional, immunological, and structural features of spike protein using several bioinformatics tools.

METHOD

We retrieved all SARS-CoV-2 spike protein sequences from different countries registered in NCBI GenBank. CLC Sequence Viewer was employed to translate and align the sequences, and several programs were utilized to predict B-cell epitopes. Modification sites such as phosphorylation, glycosylation, and disulfide bonds were defined. Secondary and tertiary structures of all sequences were further computed.

RESULTS

Some mutations were determined, where only one (D614G) had a high prevalence. The mutations did not impact the B-cell and physicochemical properties of the spike protein. Seven disulfide bonds were specified and also predicted in several N-link glycosylation and phosphorylation sites. The results also indicated that spike protein is a non-allergen.

CONCLUSION

In summary, our findings provided a deep understanding of spike protein, which can be valuable for future studies on SARS-CoV-2 infections and design of new vaccines.

Berries anthocyanins as potential SARS-CoV–2 inhibitors targeting the viral attachment and replication; molecular docking simulation

The viral respiratory disease, severe acute respiratory syndrome (SARS), has turned into a global health concern. Till now, there is no drug or vaccine has yet been specifically approved for SARS-CoV-2. One of the urgent solutions against the recent COVID-19 disease is the use of dietary molecules, which can be found abundantly in functional food. In the current study, we have conducted a molecular docking approach for eighteen dietary molecules belong to the subclass of anthocyanins, as potential inhibitors of the main protease and spike glycoprotein of SARS-CoV-2. Both selected targets, playing a vital role in attachment and replication of the virus. The results indicated that cyanidin-3-arabinoside exhibited the lowest binding energy and located onto the pocket through a sufficient number of hydrogen bonds with the main protease virus. However, pelargonidin-3-glucoside and pelargonidin 3-rhamnoside display significant binding energy with the spike glycoprotein of SARS-CoV-2. All compounds mentioned above shown high drug-likeness and fulfils the Lipinski’s rule of five, as well as confer favorable toxicity parameters, in addition to ADME values. Considering the obtained results, regular consumption of berry fruits, which are rich in anthocyanin compounds, should be supportive to inhibit viral infectious by reducing of propagation and pathogenicity of SARS-CoV–2.

Spike S2 Subunit: The Dark Horse in the Race for Prophylactic and Therapeutic Interventions against SARS-CoV-2

In the midst of the unceasing COVID-19 pandemic, the identification of immunogenic epitopes in the SARS-CoV-2 spike (S) glycoprotein plays a vital role in the advancement and development of intervention strategies. S is expressed on the exterior of the SARS-CoV-2 virion and contains two subunits, namely the N-terminal S1 and C-terminal S2. It is the key element for mediating viral entry as well as a crucial antigenic determinant capable of stimulating protective immune response through elicitation of anti-SARS-CoV-2 antibodies and activation of CD4+ and CD8+ cells in COVID-19 patients. Given that S2 is highly conserved in comparison to the S1, here, we provide a review of the latest findings on the SARS-CoV-2 S2 subunit and further discuss its potential as an attractive and promising target for the development of prophylactic vaccines and therapeutic agents against COVID-19.

Whole proteome screening and identification of potential epitopes of SARS-CoV-2 for vaccine design-an immunoinformatic, molecular docking and molecular dynamics simulation accelerated robust strategy

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the most cryptic pandemic outbreak of the 21st century, has gripped more than 1.8 million people to death and infected almost eighty six million. As it is a new variant of SARS, there is no approved drug or vaccine available against this virus. This study aims to predict some promising cytotoxic T lymphocyte epitopes in the SARS-CoV-2 proteome utilizing immunoinformatic approaches. Firstly, we identified 21 epitopes from 7 different proteins of SARS-CoV-2 inducing immune response and checked for allergenicity and conservancy. Based on these factors, we selected the top three epitopes, namely KAYNVTQAF, ATSRTLSYY, and LTALRLCAY showing functional interactions with the maximum number of MHC alleles and no allergenicity. Secondly, the 3D model of selected epitopes and HLA-A*29:02 were built and Molecular Docking simulation was performed. Most interestingly, the best two epitopes predicted by docking are part of two different structural proteins of SARS-CoV-2, namely Membrane Glycoprotein (ATSRTLSYY) and Nucleocapsid Phosphoprotein (KAYNVTQAF), which are generally target of choice for vaccine designing. Upon Molecular Docking, interactions between selected epitopes and HLA-A*29:02 were further validated by 50 ns Molecular Dynamics (MD) simulation. Analysis of RMSD, Rg, SASA, number of hydrogen bonds, RMSF, MM-PBSA, PCA, and DCCM from MD suggested that ATSRTLSYY is the most stable and promising epitope than KAYNVTQAF epitope. Moreover, we also identified B-cell epitopes for each of the antigenic proteins of SARS CoV-2. Findings of our work will be a good resource for wet lab experiments and will lessen the timeline for vaccine construction.Communicated by Ramaswamy H. Sarma.

A Novel Method for a COVID-19 Classification of Countries Based on an Intelligent Fuzzy Fractal Approach

We outline in this article a hybrid intelligent fuzzy fractal approach for classification of countries based on a mixture of fractal theoretical concepts and fuzzy logic mathematical constructs. The mathematical definition of the fractal dimension provides a way to estimate the complexity of the non-linear dynamic behavior exhibited by the time series of the countries. Fuzzy logic offers a way to represent and handle the inherent uncertainty of the classification problem. The hybrid intelligent approach is composed of a fuzzy system formed by a set of fuzzy rules that uses the fractal dimensions of the data as inputs and produce as a final output the classification of countries. The hybrid approach calculations are based on the COVID-19 data of confirmed and death cases. The main contribution is the proposed hybrid approach composed of the fractal dimension definition and fuzzy logic concepts for achieving an accurate classification of countries based on the complexity of the COVID-19 time series data. Publicly available datasets of 11 countries have been the basis to construct the fuzzy system and 15 different countries were considered in the validation of the proposed classification approach. Simulation results show that a classification accuracy over 93% can be achieved, which can be considered good for this complex problem.

Pattern of genomic variation in SARS-CoV-2 (COVID-19) suggests restricted nonrandom changes: Analysis using Shewhart control charts

SARS-CoV-2 is a member of the Coronavirus family which recently originated from the Wuhan province of China and spread very rapidly through the world infecting more than 4 million people. In the past, other Coronaviruses have also been found to cause human infection, but not as widespread as COVID-19. Since Coronavirus sequences constantly change due to mutation and recombination, it is important to understand the pattern of changes and likely path the virus can take in the future. In this study, we have used the Shewhart control chart to identify and analyze hypervariable (hotspots) and hypovariable (coldspots) regions of the virus. Our analysis shows that SARS-CoV-2 has changed in a few regions of the genome. Analysis of SARS-CoV-1 and MERS sequences suggests that over time, mutations start accumulating in different regions and most likely SARS-CoV-2 may also follow a similar path. The results suggest a possible emergence of modified viruses over some time.

Recent biotechnological advances as potential intervention strategies against COVID-19

The emerging SARS-CoV-2 viral disease (COVID-19) has caused a global health alert due to its high rate of infection and mortality in individuals with chronic cardiovascular comorbidities, in addition to generating complex clinical conditions. This has forced the scientific community to explore different strategies that allow combating this viral infection as well as treating life-threatening systemic effect of the infection on the individual. In this work, we have reviewed the most recent scientific evidence to provide a comprehensive panorama regarding the biotechnological strategies that have been proposed to combat this new viral infection. We have focused our analysis on vaccine production, nanotechnology applications, repurposing of know drugs for unrelated pathologies, and the search for bioactive molecules obtained from natural products. The goals include safely use as potential prophylactic or therapeutic treatments, based on in silico and in vivo studies, including clinical trials around the world for the correct and timely diagnosis of the infection. This review aims to highlight the development of new ideas that can decrease the time lines for research output and improve research quality while at the same time, keeping in mind the efficacy and safety aspects of these potential biotechnological strategies.

A Revisit to the Research Updates of Drugs, Vaccines, and Bioinformatics Approaches in Combating COVID-19 Pandemic

A new strain of coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for the coronavirus disease 2019 (COVID-19) pandemic was first detected in the city of Wuhan in Hubei province, China in late December 2019. To date, more than 1 million deaths and nearly 57 million confirmed cases have been recorded across 220 countries due to COVID-19, which is the greatest threat to global public health in our time. Although SARS-CoV-2 is genetically similar to other coronaviruses, i.e., SARS and Middle East respiratory syndrome coronavirus (MERS-CoV), no confirmed therapeutics are yet available against COVID-19, and governments, scientists, and pharmaceutical companies worldwide are working together in search for effective drugs and vaccines. Repurposing of relevant therapies, developing vaccines, and using bioinformatics to identify potential drug targets are strongly in focus to combat COVID-19. This review deals with the pathogenesis of COVID-19 and its clinical symptoms in humans including the most recent updates on candidate drugs and vaccines. Potential drugs (remdesivir, hydroxychloroquine, azithromycin, dexamethasone) and vaccines [mRNA-1273; measles, mumps and rubella (MMR), bacille Calmette-Guérin (BCG)] in human clinical trials are discussed with their composition, dosage, mode of action, and possible release dates according to the trial register of US National Library of Medicines (clinicaltrials.gov), European Union (clinicaltrialsregister.eu), and Chinese Clinical Trial Registry (chictr.org.cn) website. Moreover, recent reports on in silico approaches like molecular docking, molecular dynamics simulations, network-based identification, and homology modeling are included, toward repurposing strategies for the use of already approved drugs against newly emerged pathogens. Limitations of effectiveness, side effects, and safety issues of each approach are also highlighted. This review should be useful for the researchers working to find out an effective strategy for defeating SARS-CoV-2.

Supplementation with vitamin D in the COVID-19 pandemic?

The coronavirus disease 2019 (COVID-19) pandemic was declared a public health emergency of international concern by the World Health Organization. COVID-19 has high transmissibility and could result in acute lung injury in a fraction of patients. By counterbalancing the activity of the renin-angiotensin system, angiotensin-converting enzyme 2, which is the fusion receptor of the virus, plays a protective role against the development of complications of this viral infection. Vitamin D can induce the expression of angiotensin-converting enzyme 2 and regulate the immune system through different mechanisms. Epidemiologic studies of the relationship between vitamin D and various respiratory infections were reviewed and, here, the postulated mechanisms and clinical data supporting the protective role of vitamin D against COVID-19-mediated complications are discussed.

Structural Comparison of the SARS CoV 2 Spike Protein Relative to Other Human-Infecting Coronaviruses

Coronaviruses (CoV) are enveloped positive-stranded RNA viruses and, historically, there are seven known human-infecting CoVs with varying degrees of virulence. CoV attachment to the host is the first step of viral pathogenesis and mainly relies on the spike glycoprotein located on the viral surface. Among the human-infecting CoVs, only the infection of SARS CoV 2 (SARS2) among humans resulted to a pandemic which would suggest that the protein structural conformation of SARS2 spike protein is distinct as compared to other human-infecting CoVs. Surprisingly, the possible differences and similarities in the protein structural conformation between the various human-infecting CoV spike proteins have not been fully elucidated. In this study, we utilized a computational approach to generate models and analyze the seven human-infecting CoV spike proteins, namely: HCoV 229E, HCoV OC43, HCoV NL63, HCoV HKU1, SARS CoV, MERS CoV, and SARS2. Model quality assessment of all CoV models generated, structural superimposition of the whole protein model and selected S1 domains (S1-CTD and S1-NTD), and structural comparison based on RMSD values, Tm scores, and contact mapping were all performed. We found that the structural orientation of S1-CTD is a potential structural feature associated to both the CoV phylogenetic cluster and lineage. Moreover, we observed that spike models in the same phylogenetic cluster or lineage could potentially have similar protein structure. Additionally, we established that there are potentially three distinct S1-CTD orientation (Pattern I, Pattern II, Pattern III) among the human-infecting CoVs. Furthermore, we postulate that human-infecting CoVs in the same phylogenetic cluster may have similar S1-CTD and S1-NTD structural orientation. Taken together, we propose that the SARS2 spike S1-CTD follows a Pattern III orientation which has a higher degree of similarity with SARS1 and some degree of similarity with both OC43 and HKU1 which coincidentally are in the same phylogenetic cluster and lineage, whereas, the SARS2 spike S1-NTD has some degree of similarity among human-infecting CoVs that are either in the same phylogenetic cluster or lineage.

Identification of novel inhibitors of angiotensin-converting enzyme 2 (ACE-2) receptor from Urtica dioica to combat coronavirus disease 2019 (COVID-19)

Abstract

The pandemic outbreak of coronavirus (SARS-CoV-2) is rapidly spreading across the globe, so the development of anti-SARS-CoV-2 agents is urgently needed. Angiotensin-converting enzyme 2 (ACE-2), a human receptor that facilitates entry of SARS-CoV-2, serves as a prominent target for drug discovery. In the present study, we have applied the bioinformatics approach for screening of a series of bioactive chemical compounds from Himalayan stinging nettle (Urtica dioica) as potent inhibitors of ACE-2 receptor (PDB ID: 1R4L). The molecular docking was applied to dock a set of representative compounds within the active site region of target receptor protein using 0.8 version of the PyRx virtual screen tool and analyzed by using discovery studio visualizer. Based on the highest binding affinity, 23 compounds were shortlisted as a lead molecule using molecular docking analysis. Among them, β-sitosterol was found with the highest binding affinity − 12.2 kcal/mol and stable interactions with the amino acid residues present on the active site of the ACE-2 receptor. Similarly, luteoxanthin and violaxanthin followed by rutin also displayed stronger binding efficiency. We propose these compounds as potential lead candidates for the development of target-specific therapeutic drugs against COVID-19.

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s11030-020-10159-2) contains supplementary material, which is available to authorized users.

Product of natural evolution (SARS, MERS, and SARS-CoV-2); deadly diseases, from SARS to SARS-CoV-2

SARS-CoV-2, the virus causing COVID-19, is a single-stranded RNA virus belonging to the order Nidovirales, family Coronaviridae, and subfamily Coronavirinae. SARS-CoV-2 entry to cellsis initiated by the binding of the viral spike protein (S) to its cellular receptor. The roles of S protein in receptor binding and membrane fusion makes it a prominent target for vaccine development. SARS-CoV-2 genome sequence analysis has shown that this virus belongs to the beta-coronavirus genus, which includes Bat SARS-like coronavirus, SARS-CoV and MERS-CoV. A vaccine should induce a balanced immune response to elicit protective immunity. In this review, we compare and contrast these three important CoV diseases and how they inform on vaccine development.

In silico validation of potent phytochemical orientin as inhibitor of SARS-CoV-2 spike and host cell receptor GRP78 binding

The present wellbeing worry to the whole world is the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also called COVID-19. This global health crisis first appeared in Wuhan, China around December 2019 and due to its extremely contagious nature it had spread to almost 187 countries. Still now no effective method of treatment or vaccine is developed for controlling the disease. Therefore, the sole obliging strategy is to take precautionary measures by repurposing drugs from the pre-existing library of therapeutically potent molecules. In this situation of pandemic this repurposing technique may save the labour-intensive and tiresome process of new drug development. Orientin is a natural flavonoid with several beneficial effects. This phytochemical can be isolated from different plants like tulsi or holy basil, black bamboo, passion flowers etc. It's antiviral, anti-inflammation, vasodilatation, cardioprotective, radioprotective, neuroprotective, anticarcinogenic and antinociceptive effects are already established. In this research, it is intriguing to find out whether this molecule can interfere the interaction of SARS-CoV-2 spike glycoprotein and their host receptor GRP78. Our in silico docking and molecular dynamics simulation results indicate the binding of Orientin in the overlapping residues of GRP78 binding region of SARS-CoV-2 spike model and SARS-CoV-2 spike model binding region of GRP78 substrate-binding domain. Therefore, the results included in this research work provide a strong possibility of using Orientin as a promising precautionary or therapeutic measure for COVID-19.

Patents Related to Pathogenic Human Coronaviruses

BACKGROUND

Coronaviruses have caused outbreaks of respiratory disease since the beginning of the 21st century, representing a significant threat to public health. Together, the severe acute respiratory syndrome coronavirus (SARS-CoV), the respiratory syndrome coronavirus (MERS-CoV), and, more recently, the novel coronavirus (SARS-CoV-2) have caused a large number of deaths around the world. Thus, investments in research and the development of strategies aimed at diagnosing, treating, and preventing these infections are urgently needed.

OBJECTIVE

The objective of this study was to analyze the patents that address pathogenic coronaviruses in Google Patents databases in the last year (2019-2020).

METHODS

The search strategy was carried out in April 2020, based on the keywords "SARS", "SARS-CoV", "MERS", "MERS-CoV", "SARS-CoV-2" and "COVID-19. Out of the patents examined, 25 were selected for a short description in this study.

RESULTS

A total of 191 patents were analyzed, 149 of which were related to SARS-CoV, and 29 and 12 were related to MERS-CoV and SARS- CoV2, respectively. The patents addressed the issues of diagnosis, therapeutic agents, prevention and control, along with other applications.

CONCLUSION

Several promising strategies have been documented in intellectual property databases favoring the need for further studies on the pathogenesis and optimization of the diagnosis and therapeutic treatment for these emerging infections.

Recent trends on omics and bioinformatics approaches to study SARS-CoV-2: A bibliometric analysis and mini-review

BACKGROUND

The successful sequencing of SARS-CoV-2 cleared the way for the use of omics technologies and integrative biology research for combating the COVID-19 pandemic. Currently, many research groups have slowed down their respective projects to concentrate efforts in the study of the biology of SARS-CoV-2. In this bibliometric analysis and mini-review, we aimed to describe how computational methods or omics approaches were used during the first months of the COVID-19 pandemic.

METHODS

We analyzed bibliometric data from Scopus, BioRxiv, and MedRxiv (dated June 19th, 2020) using quantitative and knowledge mapping approaches. We complemented our analysis with a manual process of carefully reading the selected articles to identify either the omics or bioinformatic tools used and their purpose.

RESULTS

From a total of 184 articles, we found that metagenomics and transcriptomics were the main sources of data to perform phylogenetic analysis aimed at corroborating zoonotic transmission, identifying the animal origin and taxonomic allocation of SARS-CoV-2. Protein sequence analysis, immunoinformatics and molecular docking were used to give insights about SARS-CoV-2 targets for drug and vaccine development. Most of the publications were from China and USA. However, China, Italy and India covered the top 10 most cited papers on this topic.

CONCLUSION

We found an abundance of publications using omics and bioinformatics approaches to establish the taxonomy and animal origin of SARS-CoV-2. We encourage the growing community of researchers to explore other lesser-known aspects of COVID-19 such as virus-host interactions and host response.

Next-generation computational tools and resources for coronavirus research: From detection to vaccine discovery

The COVID-19 pandemic has affected 215 countries and territories around the world with 60,187,347 coronavirus cases and 17,125,719 currently infected patients confirmed as of the November 25, 2020. Currently, many countries are working on developing new vaccines and therapeutic drugs for this novel virus strain, and a few of them are in different phases of clinical trials. The advancement in high-throughput sequence technologies, along with the application of bioinformatics, offers invaluable knowledge on genomic characterization and molecular pathogenesis of coronaviruses. Recent multi-disciplinary studies using bioinformatics methods like sequence-similarity, phylogenomic, and computational structural biology have provided an in-depth understanding of the molecular and biochemical basis of infection, atomic-level recognition of the viral-host receptor interaction, functional annotation of important viral proteins, and evolutionary divergence across different strains. Additionally, various modern immunoinformatic approaches are also being used to target the most promiscuous antigenic epitopes from the SARS-CoV-2 proteome for accelerating the vaccine development process. In this review, we summarize various important computational tools and databases available for systematic sequence-structural study on coronaviruses. The features of these public resources have been comprehensively discussed, which may help experimental biologists with predictive insights useful for ongoing research efforts to find therapeutics against the infectious COVID-19 disease.

Computational guided identification of potential leads from Acacia pennata (L.) Willd. as inhibitors for cellular entry and viral replication of SARS-CoV-2

BACKGROUND

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) started in 2019 and is still an on-going pandemic. SARS-CoV-2 uses a human protease called furin to aid in cellular entry and its main protease (M^pro) to achieve viral replication. By targeting these proteins, scientists are trying to identify phytoconstituents of medicinal plants as potential therapeutics for COVID-19. Therefore, our study was aimed to identify promising leads as potential inhibitors of SARS-CoV-2 M^pro and furin using the phytocompounds reported to be isolated from Acacia pennata (L.) Willd.

RESULTS

A total of 29 phytocompounds were reported to be isolated from A. pennata. Molecular docking simulation studies revealed 9 phytocompounds as having the top 5 binding affinities towards SARS-CoV-2 M^pro and furin. Among these phytocompounds, quercetin-3-O-α-L-rhamnopyranoside (C_18), kaempferol 3-O-α-L-rhamnopyranosyl-(1 → 4)-β-D-glucopyranoside (C_4), and isovitexin (C_5) have the highest drug score. However, C_18 and C_4 were not selected for further studies due to bioavailability issues and low synthetic accessibility. Based on binding affinity, molecular properties, drug-likeness, toxicity parameters, ligand interactions, bioavailability, synthetic accessibility, structure-activity relationship, and comparative analysis of our experimental findings with other studies, C_5 was identified as the most promising phytocompound. C_5 interacted with the active site residues of SARS-CoV-2 M^pro (GLU166, ARG188, GLN189) and furin (ASN295, ARG298, HIS364, THR365). Many phytocompounds that interacted with these amino acid residues were reported by other studies as potential inhibitors of SARS-CoV-2 M^pro and furin. The oxygen atom at position 18, the -OH group at position 19, and the 6-C-glucoside were identified as the pharmacophores in isovitexin (also known as apigenin-6-C-glucoside). Other in-silico studies reported apigenin as a potential inhibitor of SARS-CoV-2 M^pro and apigenin-o-7-glucuronide was reported to show stable conformation during MD simulations with SARS-CoV-2 M^pro.

CONCLUSION

The present study found isovitexin as the most promising phytocompound to potentially inhibit the cellular entry and viral replication of SARS-CoV-2. We also conclude that compounds having oxygen atom at position 18 (C-ring), -OH group at position 19 (A-ring), and 6-C-glucoside attached to the A-ring at position 3 on a C₆-C₃-C₆ flavonoid scaffold could offer the best alternative to develop new leads against SARS-CoV-2.

Molecular Docking and Fragment-Based QSAR Modeling for In Silico Screening of Approved Drugs and Candidate Compounds Against COVID-19

Background: Coronavirus disease 2019 (COVID-19) as a serious global health crisis leads to high mortality and morbidity. However, currently, there are no effective vaccines and treatments for COVID-19. Main protease (Mpro) and angiotensin-converting enzyme 2 (ACE2) are the best therapeutic targets of COVID-19. Objectives: The main purpose of this study is to investigate the most appropriate drug and candidate compound for proper interaction with Mpro and ACE2 to inhibit the activity of COVID-19. Methods: In this study, repurposing of approved drugs and screening of candidate compounds using molecular docking and fragment-based QSAR method were performed to discover the potential inhibitors of Mpro and ACE2. QSAR and docking calculations were performed based on the prediction of the inhibitory activities of 5-hydroxy indanone derivatives. Based on the results, an optimal structure was proposed to inhibit the activity of COVID-19. Results: Among 2629 DrugBank approved drugs, 118 were selected considering the LibDock score and absolute energy for possible drug-Mpro interactions. Furthermore, the top 40 drugs were selected based on screening the results for possible drug- Mpro interactions with AutoDock Vina. Conclusion: Finally, evaluation of the top 40 selected drugs for possible drug-ACE2 interactions with AutoDock Vina indicated that deslanoside (DB01078) can interact effectively with both Mpro and ACE2. However, prior to conducting clinical trials, further experimental validation is needed.

Blocking Effect of Demethylzeylasteral on the Interaction between Human ACE2 Protein and SARS-CoV-2 RBD Protein Discovered Using SPR Technology

The novel coronavirus disease (2019-nCoV) has been affecting global health since the end of 2019, and there is no sign that the epidemic is abating. Targeting the interaction between the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and the human angiotensin-converting enzyme 2 (ACE2) receptor is a promising therapeutic strategy. In this study, surface plasmon resonance (SPR) was used as the primary method to screen a library of 960 compounds. A compound 02B05 (demethylzeylasteral, CAS number: 107316-88-1) that had high affinities for S-RBD and ACE2 was discovered, and binding affinities (K_D, μM) of 02B05-ACE2 and 02B05-S-RBD were 1.736 and 1.039 μM, respectively. The results of a competition experiment showed that 02B05 could effectively block the binding of S-RBD to ACE2 protein. Furthermore, pseudovirus infection assay revealed that 02B05 could inhibit entry of SARS-CoV-2 pseudovirus into 293T cells to a certain extent at nontoxic concentration. The compoundobtained in this study serve as references for the design of drugs which have potential in the treatment of COVID-19 and can thus accelerate the process of developing effective drugs to treat SARS-CoV-2 infections.

Anomaly Identification during Polymerase Chain Reaction for Detecting SARS-CoV-2 Using Artificial Intelligence Trained from Simulated Data

Real-time reverse transcription (RT) PCR is the gold standard for detecting Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), owing to its sensitivity and specificity, thereby meeting the demand for the rising number of cases. The scarcity of trained molecular biologists for analyzing PCR results makes data verification a challenge. Artificial intelligence (AI) was designed to ease verification, by detecting atypical profiles in PCR curves caused by contamination or artifacts. Four classes of simulated real-time RT-PCR curves were generated, namely, positive, early, no, and abnormal amplifications. Machine learning (ML) models were generated and tested using small amounts of data from each class. The best model was used for classifying the big data obtained by the Virology Laboratory of Simon Bolivar University from real-time RT-PCR curves for SARS-CoV-2, and the model was retrained and implemented in a software that correlated patient data with test and AI diagnoses. The best strategy for AI included a binary classification model, which was generated from simulated data, where data analyzed by the first model were classified as either positive or negative and abnormal. To differentiate between negative and abnormal, the data were reevaluated using the second model. In the first model, the data required preanalysis through a combination of prepossessing. The early amplification class was eliminated from the models because the numbers of cases in big data was negligible. ML models can be created from simulated data using minimum available information. During analysis, changes or variations can be incorporated by generating simulated data, avoiding the incorporation of large amounts of experimental data encompassing all possible changes. For diagnosing SARS-CoV-2, this type of AI is critical for optimizing PCR tests because it enables rapid diagnosis and reduces false positives. Our method can also be used for other types of molecular analyses.

A domain-based vaccine construct against SARS-CoV-2, the causative agent of COVID-19 pandemic: development of self-amplifying mRNA and peptide vaccines

Introduction: Coronavirus disease 2019 (COVID-19) is undoubtedly the most challenging pandemic in the current century with more than 293,241 deaths worldwide since its emergence in late 2019 (updated May 13, 2020). COVID-19 is caused by a novel emerged coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Today, the world needs crucially to develop a prophylactic vaccine scheme for such emerged and emerging infectious pathogens. Methods: In this study, we have targeted spike (S) glycoprotein, as an important surface antigen to identify its B- and T-cell immunodominant regions. We have conducted a multi-method B-cell epitope (BCE) prediction approach using different predictor algorithms to discover the most potential BCEs. Besides, we sought among a pool of MHC class I and II-associated peptide binders provided by the IEDB server through the strict cut-off values. To design a broad-coverage vaccine, we carried out a population coverage analysis for a set of candidate T-cell epitopes and based on the HLA allele frequency in the top most-affected countries by COVID-19 (update 02 April 2020). Results: The final determined B- and T-cell epitopes were mapped on the S glycoprotein sequence, and three potential hub regions covering the largest number of overlapping epitopes were identified for the vaccine designing (I531-N711; T717-C877; and V883-E973). Here, we have designed two domain-based constructs to be produced and delivered through the recombinant protein- and gene-based approaches, including (i) an adjuvanted domain-based protein vaccine construct (DPVC), and (ii) a self-amplifying mRNA vaccine (SAMV) construct. The safety, stability, and immunogenicity of the DPVC were validated using the integrated sequential (i.e. allergenicity, autoimmunity, and physicochemical features) and structural (i.e. molecular docking between the vaccine and human Toll-like receptors (TLRs) 4 and 5) analysis. The stability of the docked complexes was evaluated using the molecular dynamics (MD) simulations. Conclusion: These rigorous in silico validations supported the potential of the DPVC and SAMV to promote both innate and specific immune responses in preclinical studies.

Update on treatment and preventive interventions against COVID-19: an overview of potential pharmacological agents and vaccines

The outbreak of coronavirus disease 2019 (COVID-19) triggered by the new member of the coronaviridae family, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has created an unprecedented challenge for global health. In addition to mild to moderate clinical manifestations such as fever, cough, and fatigue, severe cases often developed lethal complications including acute respiratory distress syndrome (ARDS) and acute lung injury. Given the alarming rate of infection and increasing trend of mortality, the development of underlying therapeutic and preventive treatment, as well as the verification of its effectiveness, are the top priorities. Current research mainly referred to and evaluated the application of the empirical treatment based on two precedents, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), including antiviral drugs targeting different stages of virus replication, immunotherapy modulating the overactivated inflammation response, and other therapies such as herbal medicine and mesenchymal stem cells. Besides, the ongoing development of inventing prophylactic interventions such as various vaccines by companies and institutions worldwide is crucial to decline morbidity and mortality. This review mainly focused on promising candidates for the treatment of COVID-19 and collected recently updated evidence relevant to its feasibility in clinical practice in the near future.

The fourth industrial revolution and the coronavirus: a new era catalyzed by a virus☆

The global pandemic caused by the new coronavirus, COVID 19, has disrupted the lives of most people on the planet. The magnitude of such disruption can only be compared to those caused by World War II. Experts suggest that in order to better evaluate this situation, it should be divided into two waves. The first wave being associated with health issues and the second one with economic issues. This article suggests that this global pandemic is fostering yet a third wave, which in the long run can be much more impactful in our lives than the first two. This third wave consists on accelerating the implantation process of the fourth industrial revolution. This article is divided into sections with the physical, digital and biological spheres of the fourth industrial revolution, as well as the dimensions of sustainability and other important considerations, in order to better demonstrate the emergence of a new era catalyzed by a virus.

"Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images"

Coronavirus disease 2019 (COVID-19) is a novel harmful respiratory disease that has rapidly spread worldwide. At the end of 2019, COVID-19 emerged as a previously unknown respiratory disease in Wuhan, Hubei Province, China. The world health organization (WHO) declared the coronavirus outbreak a pandemic in the second week of March 2020. Simultaneous deep learning detection and classification of COVID-19 based on the full resolution of digital X-ray images is the key to efficiently assisting patients by enabling physicians to reach a fast and accurate diagnosis decision. In this paper, a simultaneous deep learning computer-aided diagnosis (CAD) system based on the YOLO predictor is proposed that can detect and diagnose COVID-19, differentiating it from eight other respiratory diseases: atelectasis, infiltration, pneumothorax, masses, effusion, pneumonia, cardiomegaly, and nodules. The proposed CAD system was assessed via five-fold tests for the multi-class prediction problem using two different databases of chest X-ray images: COVID-19 and ChestX-ray8. The proposed CAD system was trained with an annotated training set of 50,490 chest X-ray images. The regions on the entire X-ray images with lesions suspected of being due to COVID-19 were simultaneously detected and classified end-to-end via the proposed CAD predictor, achieving overall detection and classification accuracies of 96.31% and 97.40%, respectively. Most test images from patients with confirmed COVID-19 and other respiratory diseases were correctly predicted, achieving average intersection over union (IoU) greater than 90%. Applying deep learning regularizers of data balancing and augmentation improved the COVID-19 diagnostic performance by 6.64% and 12.17% in terms of the overall accuracy and the F1-score, respectively. It is feasible to achieve a diagnosis based on individual chest X-ray images with the proposed CAD system within 0.0093 s. Thus, the CAD system presented in this paper can make a prediction at the rate of 108 frames/s (FPS), which is close to real-time. The proposed deep learning CAD system can reliably differentiate COVID-19 from other respiratory diseases. The proposed deep learning model seems to be a reliable tool that can be used to practically assist health care systems, patients, and physicians.

Breeding Buckwheat for Increased Levels of Rutin, Quercetin and Other Bioactive Compounds with Potential Antiviral Effects

Common buckwheat (Fagopyrum esculentum Moench) and Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn.) are sources of many bioactive compounds, such as rutin, quercetin, emodin, fagopyrin and other (poly)phenolics. In damaged or milled grain under wet conditions, most of the rutin in common and Tartary buckwheat is degraded to quercetin by rutin-degrading enzymes (e.g., rutinosidase). From Tartary buckwheat varieties with low rutinosidase activity it is possible to prepare foods with high levels of rutin, with the preserved initial levels in the grain. The quercetin from rutin degradation in Tartary buckwheat grain is responsible in part for inhibition of α-glucosidase in the intestine, which helps to maintain normal glucose levels in the blood. Rutin and emodin have the potential for antiviral effects. Grain embryos are rich in rutin, so breeding buckwheat with the aim of producing larger embryos may be a promising strategy to increase the levels of rutin in common and Tartary buckwheat grain, and hence to improve its nutritional value.

Techniques assisting peptide vaccine and peptidomimetic design. Sidechain exposure in the SARS-CoV-2 spike glycoprotein

The aim of the present study is to discuss the design of peptide vaccines and peptidomimetics against SARS-COV-2, to develop and apply a method of protein structure analysis that is particularly appropriate to applying and discussing such design, and also to use that method to summarize some important features of the SARS-COV-2 spike protein sequence. A tool for assessing sidechain exposure in the SARS-CoV-2 spike glycoprotein is described. It extends to assessing accessibility of sidechains by considering several different three-dimensional structure determinations of SARS-CoV-2 and SARS-CoV-1 spike protein. The method is designed to be insensitive to a distance limit for counting neighboring atoms and the results are in good agreement with the physical chemical properties and exposure trends of the 20 naturally occurring sidechains. The spike protein sequence is analyzed with comment regarding exposable character. It includes studies of complexes with antibody elements and ACE2. These indicate changes in exposure at sites remote to those at which the antibody binds. They are of interest concerning design of synthetic peptide vaccines, and for peptidomimetics as a basis of drug discovery. The method was also developed in order to provide linear (one-dimensional) information that can be used along with other bioinformatics data of this kind in data mining and machine learning, potentially as genomic data regarding protein polymorphisms to be combined with more traditional clinical data.

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Bioinformatics studies are carried out on SARS-CoV-2 spike, studying solvent exposure.

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The methods are particularly suited for synthetic vaccines and d-amino acid peptidomimetics.

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Methods of generating d-amino acid peptidomimetics are described and reviewed.

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The effect of antibody binding in stabilizing loop conformation and exposing remote sites is noted.

Investigating the potential antiviral activity drugs against SARS-CoV-2 by molecular docking simulation

Recently, scary viral pneumonia is known as (COVID-19) has swept the whole world. The new virus strain designated as SARS-CoV-2 belonging to the coronavirus family. Although the current medical research directed towards the development of a novel therapeutic agent, no anti-viral drug approved until now. On the medical scale, the development of an approved drug is a time-consuming process, so research is directed towards screening of ligands and drugs multimodal structure-based-design and then docked to the main viral protease to investigate the active binding sites. The bioinformatic approaches used to evaluate the competence of a comprehensive range of ligands and drugs before their clinical implementation. In this study, a computational approach through molecular docking simulation is conducted for screening the antiviral activity of drugs, natural sources, and inhibitory compounds against the SARS-CoV-2 genome. The main virus protease was collected from a Protein Data Bank (PDB# 6YB7) and docked with a sequence of 19 approved antiviral drugs, 10 natural inhibitory ligands against COVID-19 downloaded from PubChem, in addition to 10 natural sources optimized for Escherichia coli BL21 (DE3) to identify the antiviral activity of these candidates against COVID-19. The docking results were promised and indicated that the reported ligands can firmly bind to the SARS-CoV-2 main protease and leads to inhibition of its infectious impact.

Evaluation of acridinedione analogs as potential SARS-CoV-2 main protease inhibitors and their comparison with repurposed anti-viral drugs

Background

The main protease (Mpro) of SARS-CoV-2 is involved in the processing of vital polypeptides required for viral genome replication and transcription and is one of the best-characterized targets to inhibit the progression of SARS-CoV-2 in infected individuals.

Methods

We screened a set of novel classes of acridinediones molecules to efficiently bind and inhibit the activity of the SARS-CoV-2 by targeting the Mpro. The repurposed FDA-approved antivirals were taken as standard molecules for this study. Long term (1.1 μs) MD simulations were performed to analyze the conformational space of the binding pocket of Mpro bound to the selected molecules.

Results

The molecules DSPD-2 and DSPD-6 showed more favorable MM-PBSA interaction energies and were seated more deeply inside the binding pocket of Mpro than the topmost antiviral drug (Saquinavir). Moreover, DSPD-5 also exhibited comparable binding energy to Saquinavir. The analysis of per residue contribution energy and SASA studies indicated that the molecules showed efficient binding by targeting the S1 subsite of the Mpro binding pocket.

Conclusion

The DSPD-2, DSPD-6, and DSPD-5 could be developed as potential inhibitors of SARS-CoV-2. Moreover, we suggest that targeting molecules to bind effectively to the S1 subsite could potentially increase the binding of molecules to the SARS-CoV-2 Mpro.

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A robust computational strategy applied to identify the potential lead for COVID-19.

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Repurposed FDA approved antiviral drugs were compared with a set of acridinedione analogs against Mpro of SARS-CoV-2.

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The acridinedione analogs have acceptable ADMET values and low toxicity profile.

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In-house synthesized acridinedione analogs showed good amount of interaction with Mpro of SARS-CoV-2.

Current status of COVID-19 pandemic; characteristics, diagnosis, prevention, and treatment

Humans have always been encountered to big infectious diseases outbreak throughout the history. In December 2019, novel coronavirus (COVID-19) was first noticed as an agent causing insidious pneumonia in Wuhan, China. COVID-19 was spread rapidly from Wuhan to the rest of the world. Until late June 2020, it infected more than 10,000,000 people and caused more than 500,000 deaths in almost all of countries in the world, creating a global crisis worse than all previous epidemics and pandemics. In the current review, we gathered and summarized the results of various studies on characteristics, diagnosis, treatment, and prevention of this pandemic crisis.

Designing a novel mRNA vaccine against SARS-CoV-2: An immunoinformatics approach

SARS-CoV-2 is the deadly virus behind COVID-19, the disease that went on to ravage the world and caused the biggest pandemic 21st century has witnessed so far. On the face of ongoing death and destruction, the urgent need for the discovery of a vaccine against the virus is paramount. This study resorted to the emerging discipline of immunoinformatics in order to design a multi-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2. Various immunoinformatics tools were utilized to predict T and B lymphocyte epitopes. The epitopes were channeled through a filtering pipeline comprised of antigenicity, toxicity, allergenicity, and cytokine inducibility evaluation with the goal of selecting epitopes capable of generating both T and B cell-mediated immune responses. Molecular docking simulation between the epitopes and their corresponding MHC molecules was carried out. 13 epitopes, a highly immunogenic adjuvant, elements for proper sub-cellular trafficking, a secretion booster, and appropriate linkers were combined for constructing the vaccine. The vaccine was found to be antigenic, almost neutral at physiological pH, non-toxic, non-allergenic, capable of generating a robust immune response and had a decent worldwide population coverage. Based on these parameters, this design can be considered a promising choice for a vaccine against SARS-CoV-2.

Forecasting of COVID-19 time series for countries in the world based on a hybrid approach combining the fractal dimension and fuzzy logic

We describe in this paper a hybrid intelligent approach for forecasting COVID-19 time series combining fractal theory and fuzzy logic. The mathematical concept of the fractal dimension is used to measure the complexity of the dynamics in the time series of the countries in the world. Fuzzy Logic is used to represent the uncertainty in the process of making a forecast. The hybrid approach consists on a fuzzy model formed by a set of fuzzy rules that use as input values the linear and nonlinear fractal dimensions of the time series and as outputs the forecast for the countries based on the COVID-19 time series of confirmed cases and deaths. The main contribution is the proposed hybrid approach combining the fractal dimension and fuzzy logic for enabling an efficient and accurate forecasting of COVID-19 time series. Publicly available data sets of 10 countries in the world have been used to build the fuzzy model with time series in a fixed period. After that, other periods of time were used to verify the effectiveness of the proposed approach for the forecasted values of the 10 countries. Forecasting windows of 10 and 30 days ahead were used to test the proposed approach. Forecasting average accuracy is 98%, which can be considered good considering the complexity of the COVID problem. The proposed approach can help people in charge of decision making to fight the pandemic can use the information of a short window to decide immediate actions and also the longer window (like 30 days) can be beneficial in long term decisions.

Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19

Coronavirus disease 2019 (COVID-19) has caused thousands of deaths worldwide and has become an urgent public health concern. The extraordinary interhuman transmission of this disease has urged scientists to examine the various facets of its pathogenic agent, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, based on publicly available genomic data, we analyzed the codon usage co-adaptation profiles of SARS-CoV-2 and other respiratory coronaviruses (CoVs) with their human host, identified CoV-responsive human genes and their functional roles on the basis of both the relative synonymous codon usage (RSCU)-based correlation of viral genes with human genes and differential gene expression analysis, and predicted potential drugs for COVID-19 treatment based on these genes. The relatively high codon adaptation index (CAI) values (>0.70) signposted the gene expressivity efficiency of CoVs in human. The ENc-GC3 plot indicated that SARS-CoV-2 genome was under strict selection pressure while SARS-CoV and MERS-CoV were under selection and mutational pressures. The RSCU-based correlation analysis indicated that the viral genomes shared similar codons with a panoply of human genes. The merging of RSCU-based correlation data and SARS-CoV-2-responsive differentially expressed genes allowed the identification of human genes potentially affected by SARS-CoV-2 infection. Functional enrichment analysis indicated that these genes were enriched in biological processes and pathways related to host response to viral infection and immune response. Using the drug-gene interaction database, we screened a list of drugs that could target these genes as potential COVID-19 therapeutics. Our findings not only will contribute in vaccine development but also provide a useful set of drugs that could guide practitioners in strategical monitoring of COVID-19. We recommend practitioners to scrupulously screen this list of predicted drugs in order to authenticate those qualified for treating COVID-19 symptoms.

A Body Tracking-Based Low-Cost Solution for Monitoring Workers' Hygiene Best Practices during Pandemics

Since its beginning at the end of 2019, the pandemic spread of the severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2) caused more than one million deaths in only nine months. The threat of emerging and re-emerging infectious diseases exists as an imminent threat to human health. It is essential to implement adequate hygiene best practices to break the contagion chain and enhance society preparedness for such critical scenarios and understand the relevance of each disease transmission route. As the unconscious hand-face contact gesture constitutes a potential pathway of contagion, in this paper, the authors present a prototype system based on low-cost depth sensors able to monitor in real-time the attitude towards such a habit. The system records people's behavior to enhance their awareness by providing real-time warnings, providing for statistical reports for designing proper hygiene solutions, and better understanding the role of such route of contagion. A preliminary validation study measured an overall accuracy of 91%. A Cohen's Kappa equal to 0.876 supports rejecting the hypothesis that such accuracy is accidental. Low-cost body tracking technologies can effectively support monitoring compliance with hygiene best practices and training people in real-time. By collecting data and analyzing them with respect to people categories and contagion statistics, it could be possible to understand the importance of this contagion pathway and identify for which people category such a behavioral attitude constitutes a significant risk.

Structure-Based Design of Novel Peptidomimetics Targeting the SARS-CoV-2 Spike Protein

Purpose

SARS-CoV-2 is a SARS-like novel coronavirus strain first identified in December 2019 in Wuhan, China. The virus has since spread globally, resulting in the current ongoing coronavirus disease 19 (COVID-19) pandemic. SARS-CoV-2 spike protein is a critical factor in the COVID-19 pathogenesis via interactions with the host cell angiotensin-converting enzyme 2 (ACE2) PD domain. Worldwide, numerous efforts are being made to combat COVID19. In the current study, we identified potential peptidomimetics against the SARS-CoV-2 spike protein.

Methods

We utilized the information from ACE2-SARS-CoV-2 binary interactions, and based on crucial interacting interface residues, novel peptidomimetics were designed.

Results

Top scoring peptidomimetics were found to bind at the ACE2 binding site of the receptor-binding domain (RBD) of SARS-CoV-2 spike protein.

Conclusions

The current studies could pave the way for further investigations of these novel and potent compounds against the SARS-CoV-2.

Drug Discovery Strategies for SARS-CoV-2

Coronavirus disease 2019 (COVID-19) is a novel disease caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2 virus that was first detected in December of 2019 in Wuhan, China, and has rapidly spread worldwide. The search for a suitable vaccine as well as effective therapeutics for the treatment of COVID-19 is underway. Drug repurposing screens provide a useful and effective solution for identifying potential therapeutics against SARS-CoV-2. For example, the experimental drug remdesivir, originally developed for Ebola virus infections, has been approved by the US Food and Drug Administration as an emergency use treatment of COVID-19. However, the efficacy and toxicity of this drug need further improvements. In this review, we discuss recent findings on the pathology of coronaviruses and the drug targets for the treatment of COVID-19. Both SARS-CoV-2-specific inhibitors and broad-spectrum anticoronavirus drugs against SARS-CoV, Middle East respiratory syndrome coronavirus, and SARS-CoV-2 will be valuable additions to the anti-SARS-CoV-2 armament. A multitarget treatment approach with synergistic drug combinations containing different mechanisms of action may be a practical therapeutic strategy for the treatment of severe COVID-19. SIGNIFICANCE STATEMENT: Understanding the biology and pathology of RNA viruses is critical to accomplish the challenging task of developing vaccines and therapeutics against SARS-CoV-2. This review highlights the anti-SARS-CoV-2 drug targets and therapeutic development strategies for COVID-19 treatment.