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

The use of knowledge management tools in viroinformatics. Example study of a highly conserved sequence motif in Nsp3 of SARS-CoV-2 as a therapeutic target

Knowledge management tools that assist in systematic review and exploration of scientific knowledge generally are of obvious potential importance in evidence based medicine in general, but also to the design of therapeutics based on the protein subsequences and fold motifs of virus proteins as considered here. Rapid access to bundles (clusters) of related elements of knowledge gathered from diverse sources on the Internet and from growing knowledge repositories seem particularly helpful when exploring less obvious therapeutic targets in viruses (for which knowledge new to the researcher is important), and when using the following concept. Subsequences of amino acid residue sequences of proteins that are conserved across strains and species are (a) more likely to be important targets and (b) less likely to exhibit escape mutations that would make them resistant to vaccines and therapeutic agents. However, the terms "conserved" and even "highly conserved" used by authors are matters of degree, depending on how distant from SARS-CoV-2 they wished to go in comparing other sequences. The binding site to the human ACE2 protein as virus receptor and human antibody CR3022 binding site on the spike glycoprotein are rather variable by the criteria used in the present and preceding studies. To look for more strongly conserved targets, open reading frames of SARS-CoV-2 were examined for extremely highly conserved regions, meaning recognizable across many viruses and organisms. Most prominent is a motif found in SARS-CoV-2 non-structural protein 3 (Nsp3). It relates to a fold called type called the macro domain and has remarkably wide distribution across organisms including humans with significant homologies involving three especially conserved subsequences (a) VVVNAANVYLKHGGGVAGALNK, (b) LHVVGPNVNKG, and (c) PLLSAGIFG. Careful study of the variations of these and of the more variable sequences between and around them might provide a finer "scalpel" to ensure inhibition of a vital function of the virus without impairing the functions of related host macro domains.

SARS-CoV-2/COVID-19: Evolving Reality, Global Response, Knowledge Gaps, and Opportunities

Approximately 3 billion people around the world have gone into some form of social separation to mitigate the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. The uncontrolled influx of patients in need of emergency care has rapidly brought several national health systems to near-collapse with deadly consequences to those afflicted by Coronavirus Disease 2019 (COVID-19) and other critical diseases associated with COVID-19. Solid scientific evidence regarding SARS-CoV-2/COVID-19 remains scarce; there is an urgent need to expand our understanding of the SARS-CoV-2 pathophysiology to facilitate precise and targeted treatments. The capacity for rapid information dissemination has emerged as a double-edged sword; the existing gap of high-quality data is frequently filled by anecdotal reports, contradictory statements, and misinformation. This review addresses several important aspects unique to the SARS-CoV-2/COVID-19 pandemic highlighting the most relevant knowledge gaps and existing windows-of-opportunity. Specifically, focus is given on SARS-CoV-2 immunopathogenesis in the context of experimental therapies and preclinical evidence and their applicability in supporting efficacious clinical trial planning. The review discusses the existing challenges of SARS-CoV-2 diagnostics and the potential application of translational technology for epidemiological predictions, patient monitoring, and treatment decision-making in COVID-19. Furthermore, solutions for enhancing international strategies in translational research, cooperative networks, and regulatory partnerships are contemplated.

SARS-CoV-2: generalidades bioquímicas y métodos de diagnóstico

El 31 de diciembre de 2019 la comisión municipal de salud de Wuhan (provincia de Hubei, China) informa sobre un inusitado brote de casos de neumonía en la ciudad. Posteriormente se determina que se trata de un nuevo coronavirus designado inicialmente como 2019-nCoV y posteriormente, SARS-CoV-2. El SARS-CoV-2 infecta y se replica en los neumocitos y macrófagos del sistema respiratorio específicamente en el parénquima pulmonar en donde reside el receptor celular ACE-2. Esta revisión describe aspectos relacionados con la transmisión, prevención, generalidades bioquímicas del SARS-CoV-2 y métodos diagnósticos del COVID-19. Inicialmente se describe la forma de transmisión del virus y algunas recomendaciones generales para su prevención. Posteriormente, se hace una descripción detallada de los aspectos bioquímicos del SARS-CoV-2, su ciclo infeccioso y la estructura de la proteína S, la cual está involucrada con el proceso de ingreso del virus a la célula. Finalmente, se describen los métodos y pruebas de laboratorio para el diagnóstico del COVID-19.

Assessment of effective imidazole derivatives against SARS-CoV-2 main protease through computational approach

Because of the fast increase in deaths due to Corona Viral Infection in majority region in the world, the detection of drugs potent of this infection is a major need. With this idea, docking study was executed on eighteen imidazole derivatives based on 7-chloro-4-aminoquinoline against novel Coronavirus (SARS-CoV-2). In this study, we carried out a docking study of these molecules in the active site of SARS-CoV-2 main protease. The result indicate that Molecules N° 3, 7 and 14 have more binding energy with SARS-CoV-2 main protease recently crystallized (pdb code 6LU7) in comparison with the other imidazole derivatives and the two drug; Chloroquine and hydroxychloroquine. Because of the best energy of interaction, these three molecules could have the most potential antiviral treatment of COVID-19 than the other studied compounds. The structures with best affinity in the binding site of the protease have more than 3 cycles and electronegative atoms in the structure. This may increase the binding affinity of these molecules because of formation of π-bonds, halogen interactions and/or Hydrogen bond interactions between compounds and the enzyme. So, compounds with more cycles and electronegative atoms could have a potent inhibition of SARS-CoV-2 main protease.

Structural features of coronavirus SARS-CoV-2 spike protein: Targets for vaccination

Various human pathogenic viruses employ envelope glycoproteins for host cell receptor recognition and binding, membrane fusion and viral entry. The spike (S) glycoprotein of betacoronavirus SARS-CoV-2 is a homotrimeric class I fusion protein that exists in a metastable conformation for cleavage by host cell proteases furin and TMPRSS2, thereby undergoing substantial structural rearrangement for ACE2 host cell receptor binding and subsequent viral entry by membrane fusion. The S protein is densely decorated with N-linked glycans protruding from the trimer surface that affect S protein folding, processing by host cell proteases and the elicitation of humoral immune response. Deep insight into the sophisticated structure of SARS-CoV-2 S protein may provide a blueprint for vaccination strategies, as reviewed herein.

Potential Therapeutic Options for COVID-19: Current Status, Challenges, and Future Perspectives

The COVID-19 pandemic represents an unprecedented challenge for the researchers to offer safe, tolerable, and effective treatment strategies for its causative agent known as SARS-CoV-2. With the rapid evolution of the pandemic, even the off-label use of existing drugs has been restricted by limited availability. Several old antivirals, antimalarial, and biological drugs are being reconsidered as possible therapies. The effectiveness of the controversial treatment options for COVID-19 such as nonsteroidal antiinflammatory drugs, angiotensin 2 conversion enzyme inhibitors and selective angiotensin receptor blockers was also discussed. A systemic search in the PubMed, Science Direct, LitCovid, Chinese Clinical Trial Registry, and ClinicalTrials.gov data bases was conducted using the keywords "coronavirus drug therapy," passive immunotherapy for COVID-19', "convalescent plasma therapy," (CPT) "drugs for COVID-19 treatment," "SARS-CoV-2," "COVID-19," "2019-nCoV," "coronavirus immunology," "microbiology," "virology," and individual drug names. Systematic reviews, case presentations and very recent clinical guidelines were included. This narrative review summarizes the available information on possible therapies for COVID-19, providing recent data to health professionals.

A new advanced in silico drug discovery method for novel coronavirus (SARS-CoV-2) with tensor decomposition-based unsupervised feature extraction

BACKGROUND

COVID-19 is a critical pandemic that has affected human communities worldwide, and there is an urgent need to develop effective drugs. Although there are a large number of candidate drug compounds that may be useful for treating COVID-19, the evaluation of these drugs is time-consuming and costly. Thus, screening to identify potentially effective drugs prior to experimental validation is necessary.

METHOD

In this study, we applied the recently proposed method tensor decomposition (TD)-based unsupervised feature extraction (FE) to gene expression profiles of multiple lung cancer cell lines infected with severe acute respiratory syndrome coronavirus 2. We identified drug candidate compounds that significantly altered the expression of the 163 genes selected by TD-based unsupervised FE.

RESULTS

Numerous drugs were successfully screened, including many known antiviral drug compounds such as C646, chelerythrine chloride, canertinib, BX-795, sorafenib, sorafenib, QL-X-138, radicicol, A-443654, CGP-60474, alvocidib, mitoxantrone, QL-XII-47, geldanamycin, fluticasone, atorvastatin, quercetin, motexafin gadolinium, trovafloxacin, doxycycline, meloxicam, gentamicin, and dibromochloromethane. The screen also identified ivermectin, which was first identified as an anti-parasite drug and recently the drug was included in clinical trials for SARS-CoV-2.

CONCLUSIONS

The drugs screened using our strategy may be effective candidates for treating patients with COVID-19.

The New Coronavirus (SARS-CoV-2): A Comprehensive Review on Immunity and the Application of Bioinformatics and Molecular Modeling to the Discovery of Potential Anti-SARS-CoV-2 Agents

On March 11, 2020, the World Health Organization (WHO) officially declared the outbreak caused by the new coronavirus (SARS-CoV-2) a pandemic. The rapid spread of the disease surprised the scientific and medical community. Based on the latest reports, news, and scientific articles published, there is no doubt that the coronavirus has overloaded health systems globally. Practical actions against the recent emergence and rapid expansion of the SARS-CoV-2 require the development and use of tools for discovering new molecular anti-SARS-CoV-2 targets. Thus, this review presents bioinformatics and molecular modeling strategies that aim to assist in the discovery of potential anti-SARS-CoV-2 agents. Besides, we reviewed the relationship between SARS-CoV-2 and innate immunity, since understanding the structures involved in this infection can contribute to the development of new therapeutic targets. Bioinformatics is a technology that assists researchers in coping with diseases by investigating genetic sequencing and seeking structural models of potential molecular targets present in SARS-CoV2. The details provided in this review provide future points of consideration in the field of virology and medical sciences that will contribute to clarifying potential therapeutic targets for anti-SARS-CoV-2 and for understanding the molecular mechanisms responsible for the pathogenesis and virulence of SARS-CoV-2.

Tuberculosis and COVID-19: Lessons from the Past Viral Outbreaks and Possible Future Outcomes

Background

The threat of contagious infectious diseases is constantly evolving as demographic explosion, travel globalization, and changes in human lifestyle increase the risk of spreading pathogens, leading to accelerated changes in disease landscape. Of particular interest is the aftermath of superimposing viral epidemics (especially SARS-CoV-2) over long-standing diseases, such as tuberculosis (TB), which remains a significant disease for public health worldwide and especially in emerging economies.

Methods and Results

The PubMed electronic database was systematically searched for relevant articles linking TB, influenza, and SARS-CoV viruses and subsequently assessed eligibility according to inclusion criteria. Using a data mining approach, we also queried the COVID-19 Open Research Dataset (CORD-19). We aimed to answer the following questions: What can be learned from other coronavirus outbreaks (focusing on TB patients)? Is coinfection (TB and SARS-CoV-2) more severe? Is there a vaccine for SARS-CoV-2? How does the TB vaccine affect COVID-19? How does one diagnosis affect the other? Discussions. Few essential elements about TB and SARS-CoV coinfections were discussed. First, lessons from past outbreaks (other coronaviruses) and influenza pandemic/seasonal outbreaks have taught the importance of infection control to avoid the severe impact on TB patients. Second, although challenging due to data scarcity, investigating the pathological pathways linking TB and SARS-CoV-2 leads to the idea that their coexistence might yield a more severe clinical evolution. Finally, we addressed the issues of vaccination and diagnostic reliability in the context of coinfection.

Conclusions

Because viral respiratory infections and TB impede the host's immune responses, it can be assumed that their lethal synergism may contribute to more severe clinical evolution. Despite the rapidly growing number of cases, the data needed to predict the impact of the COVID-19 pandemic on patients with latent TB and TB sequelae still lies ahead. The trial is registered with NCT04327206, NCT01829490, and NCT04121494.

Analysis of Spatial Spread Relationships of Coronavirus (COVID-19) Pandemic in the World using Self Organizing Maps

We describe in this paper an analysis of the spatial evolution of coronavirus pandemic around the world by using a particular type of unsupervised neural network, which is called self-organizing maps. Based on the clustering abilities of self-organizing maps we are able to spatially group together countries that are similar according to their coronavirus cases, in this way being able to analyze which countries are behaving similarly and thus can benefit by using similar strategies in dealing with the spread of the virus. Publicly available datasets of coronavirus cases around the globe from the last months have been used in the analysis. Interesting conclusions have been obtained, that could be helpful in deciding the best strategies in dealing with this virus. Most of the previous papers dealing with data of the Coronavirus have viewed the problem on temporal aspect, which is also important, but this is mainly concerned with the forecast of the numeric information. However, we believe that the spatial aspect is also important, so in this view the main contribution of this paper is the use of unsupervised self-organizing maps for grouping together similar countries in their fight against the Coronavirus pandemic, and thus proposing that strategies for similar countries could be established accordingly.

Structural and functional properties of SARS-CoV-2 spike protein: potential antivirus drug development for COVID-19

Coronavirus disease 2019 is a newly emerging infectious disease currently spreading across the world. It is caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spike (S) protein of SARS-CoV-2, which plays a key role in the receptor recognition and cell membrane fusion process, is composed of two subunits, S1 and S2. The S1 subunit contains a receptor-binding domain that recognizes and binds to the host receptor angiotensin-converting enzyme 2, while the S2 subunit mediates viral cell membrane fusion by forming a six-helical bundle via the two-heptad repeat domain. In this review, we highlight recent research advance in the structure, function and development of antivirus drugs targeting the S protein.

Fight against novel coronavirus: A perspective of medicinal chemists

The ongoing novel coronavirus disease (COVID-19) pandemic makes us painfully perceive that our bullet shells are blank so far for fighting against severe human coronavirus (HCoV). In spite of vast research work, it is crystal clear that the evident does not warrant the commercial blossoming of anti-HCoV drugs. In this circumstance, drug repurposing and/or screening of databases are the only fastest option. This study is an initiative to recapitulate the medicinal chemistry of severe acute respiratory syndrome (SARS)-CoV-2 (SARS-CoV-2). The aim is to present an exquisite delineation of the current research from the perspective of a medicinal chemist to allow the rapid development of anti-SARS-CoV-2 agents.

Design an Efficient Multi-Epitope Peptide Vaccine Candidate Against SARS-CoV-2: An in silico Analysis

BACKGROUND

To date, no specific vaccine or drug has been proven to be effective against SARS-CoV-2 infection. Therefore, we implemented an immunoinformatic approach to design an efficient multi-epitopes vaccine against SARS-CoV-2.

RESULTS

The designed-vaccine construct consists of several immunodominant epitopes from structural proteins of spike, nucleocapsid, membrane, and envelope. These peptides promote cellular and humoral immunity and interferon-gamma responses. Also, these epitopes have a high antigenic capacity and are not likely to cause allergies. To enhance the vaccine immunogenicity, we used three potent adjuvants: Flagellin of Salmonella enterica subsp. enterica serovar Dublin, a driven peptide from high mobility group box 1 as HP-91, and human beta-defensin 3 protein. The physicochemical and immunological properties of the vaccine structure were evaluated. The tertiary structure of the vaccine protein was predicted and refined by Phyre2 and Galaxi refine and validated using RAMPAGE and ERRAT. Results of ElliPro showed 246 sresidues from vaccine might be conformational B-cell epitopes. Docking of the vaccine with toll-like receptors (TLR) 3, 5, 8, and angiotensin-converting enzyme 2 approved an appropriate interaction between the vaccine and receptors. Prediction of mRNA secondary structure and in silico cloning demonstrated that the vaccine can be efficiently expressed in Escherichia coli.

CONCLUSION

Our results demonstrated that the multi-epitope vaccine might be potentially antigenic and induce humoral and cellular immune responses against SARS-CoV-2. This vaccine can interact appropriately with the TLR3, 5, and 8. Also, it has a high-quality structure and suitable characteristics such as high stability and potential for expression in Escherichia coli .

Identification of a Potential Peptide Inhibitor of SARS-CoV-2 Targeting its Entry into the Host Cells

BACKGROUND AND OBJECTIVE

Coronavirus disease (COVID-19) is an ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to the incessant spread of the disease with substantial morbidity and mortality rates, there is an urgent demand for effective therapeutics and vaccines to control and diminish this pandemic. A critical step in the crosstalk between the virus and the host cell is the binding of SARS-CoV-2 spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor present on the surface of the host cells. Hence, inhibition of this interaction could be a promising strategy to combat the SARS-CoV-2 infection.

METHODS

Docking and Molecular Dynamics (MD) simulation studies revealed that designed peptide maintains their secondary structure and provide a highly specific and stable binding (blocking) to SARS-CoV-2.

RESULTS

We have designed a novel peptide that could inhibit SARS-CoV-2 spike protein interaction with ACE2, thereby blocking the cellular entry of the virus.

CONCLUSION

Our findings suggest that computationally developed inhibitory peptide may be developed as an anti-SARS-CoV-2 agent for the treatment of SARS-CoV-2 infection. We further plan to pursue the peptide in cell-based assays and eventually for clinical trials.

Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review

BACKGROUND

Artificial intelligence (AI) and the Internet of Intelligent Things (IIoT) are promising technologies to prevent the concerningly rapid spread of coronavirus disease (COVID-19) and to maximize safety during the pandemic. With the exponential increase in the number of COVID-19 patients, it is highly possible that physicians and health care workers will not be able to treat all cases. Thus, computer scientists can contribute to the fight against COVID-19 by introducing more intelligent solutions to achieve rapid control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease.

OBJECTIVE

The objectives of this review were to analyze the current literature, discuss the applicability of reported ideas for using AI to prevent and control COVID-19, and build a comprehensive view of how current systems may be useful in particular areas. This may be of great help to many health care administrators, computer scientists, and policy makers worldwide.

METHODS

We conducted an electronic search of articles in the MEDLINE, Google Scholar, Embase, and Web of Knowledge databases to formulate a comprehensive review that summarizes different categories of the most recently reported AI-based approaches to prevent and control the spread of COVID-19.

RESULTS

Our search identified the 10 most recent AI approaches that were suggested to provide the best solutions for maximizing safety and preventing the spread of COVID-19. These approaches included detection of suspected cases, large-scale screening, monitoring, interactions with experimental therapies, pneumonia screening, use of the IIoT for data and information gathering and integration, resource allocation, predictions, modeling and simulation, and robotics for medical quarantine.

CONCLUSIONS

We found few or almost no studies regarding the use of AI to examine COVID-19 interactions with experimental therapies, the use of AI for resource allocation to COVID-19 patients, or the use of AI and the IIoT for COVID-19 data and information gathering/integration. Moreover, the adoption of other approaches, including use of AI for COVID-19 prediction, use of AI for COVID-19 modeling and simulation, and use of AI robotics for medical quarantine, should be further emphasized by researchers because these important approaches lack sufficient numbers of studies. Therefore, we recommend that computer scientists focus on these approaches, which are still not being adequately addressed.

Elucidating the microscopic and computational techniques to study the structure and pathology of SARS-CoVs

Severe Acute Respiratory Syndrome Coronaviruses (SARS‐CoVs), causative of major outbreaks in the past two decades, has claimed many lives all over the world. The virus effectively spreads through saliva aerosols or nasal discharge from an infected person. Currently, no specific vaccines or treatments exist for coronavirus; however, several attempts are being made to develop possible treatments. Hence, it is important to study the viral structure and life cycle to understand its functionality, activity, and infectious nature. Further, such studies can aid in the development of vaccinations against this virus. Microscopy plays an important role in examining the structure and topology of the virus as well as pathogenesis in infected host cells. This review deals with different microscopy techniques including electron microscopy, atomic force microscopy, fluorescence microscopy as well as computational methods to elucidate various prospects of this life‐threatening virus.

Structural analysis of SARS‐CoVs aids in understanding its nature, activity, and pathophysiology

Revealing the surface morphology of SARS‐CoVs using scanning electron microscope and atomic force microscopy

Computational methods help to understand the structure of SARS‐CoVs and their interactions with various inhibitors

Unlocking COVID therapeutic targets: A structure-based rationale against SARS-CoV-2, SARS-CoV and MERS-CoV Spike

There are no approved target therapeutics against SARS-CoV-2 or other beta-CoVs. The beta-CoV Spike protein is a promising target considering the critical role in viral infection and pathogenesis and its surface exposed features. We performed a structure-based strategy targeting highly conserved druggable regions resulting from a comprehensive large-scale sequence analysis and structural characterization of Spike domains across SARSr- and MERSr-CoVs. We have disclosed 28 main consensus druggable pockets within the Spike. The RBD and SD1 (S1 subunit); and the CR, HR1 and CH (S2 subunit) represent the most promising conserved druggable regions. Additionally, we have identified 181 new potential hot spot residues for the hSARSr-CoVs and 72 new hot spot residues for the SARSr- and MERSr-CoVs, which have not been described before in the literature. These sites/residues exhibit advantageous structural features for targeted molecular and pharmacological modulation. This study establishes the Spike as a promising anti-CoV target using an approach with a potential higher resilience to resistance development and directed to a broad spectrum of Beta-CoVs, including the new SARS-CoV-2 responsible for COVID-19. This research also provides a structure-based rationale for the design and discovery of chemical inhibitors, antibodies or other therapeutic modalities successfully targeting the Beta-CoV Spike protein.

Genomics insights of SARS-CoV-2 (COVID-19) into target-based drug discovery

Coronavirus disease (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is a global health emergency and no clinically approved vaccines or antiviral drugs available to date. Intensive research on SARS-CoV-2 is urgently warranted to understand its pathogenesis and virulence mechanisms and to discover target-based antiviral therapeutics. Among various research logics, current bioinformatics highlights novel testable hypotheses for systematic drug repositioning and designing against COVID-19. A total of 121 articles related to bioinformatics facets of this virus were collected from the PubMed Central. The content of each investigation was comprehensively reviewed, manually curated, and included herein. Interestingly, 109 COVID-19-related literature published in 2020 (January-June) were included in this review. The present article emphasizes novel resource development on its genome structure, evolution, therapeutic targets, drug designing, and drug repurposing strategies. Genome organization, the function of coding genes, origin, and evolution of SARS-CoV-2 is described in detail. Genomic insights into understanding the structure-function relationships of drug targets including spike, main protease, and RNA-dependent RNA polymerase of SARS-CoV-2 are discussed intensively. Several molecular docking and systems pharmacology approaches have been investigated some promising antiviral drugs against SARS-CoV-2 based on its genomic characteristics, pathogenesis mechanism, and host specificity. Perhaps, the present genomic insights of this virus will provide a lead to the researchers to design or repurpose of antiviral drugs soon and future directions to control the spread of COVID-19.

Identification of a potential SARS-CoV2 inhibitor via molecular dynamics simulations and amino acid decomposition analysis

Considering lack of validated therapeutic drugs or vaccines against contagious SARS-CoV2, various efforts have been focused on repurposing of existing drugs or identifying new agents. In an attempt to identify new and potential SARS-CoV2 inhibitors targeting specific enzyme of the pathogen, a few induced fit models of SARS-CoV2 main protease (Mpro) including N-aryl amide and aryl sulfonamide based fragments were subjected to a multi-step in silico strategy. Sub-structure query of co-crystallographic fragments provided numerous ZINC15 driven commercially available compounds that entered molecular docking stage to find binding interactions/modes inside Mpro active site. Docking results were reevaluated through time dependent stability of top-ranked ligand-protease complexes by molecular dynamics (MD) simulations within 50 ns. Relative contribution of interacted residues in binding to the most probable binding pose was estimated through amino acid decomposition analysis in B3LYP level of theory with Def2-TZVPP split basis set. In confirmation of docking results, MD simulations revealed less perceptible torsional distortions (more stable binding mode) in binding of ZINC_252512772 (ΔG_b −9.18 kcal/mol) into Mpro active site. H-bond interactions and hydrophobic contacts were determinant forces in binding interactions of in silico hit. Quantum chemical calculations confirmed MD results and proved the pivotal role of a conserved residue (Glu166) in making permanent hydrogen bond (98% of MD simulations time) with ZINC_252512772. Drug-like physicochemical properties as well as desirable target binding interactions nominated ZINC_252512772 as a desirable in silico hit for further development toward SARS-CoV2 inhibitors.

Highlights

A few N-aryl amide/aryl sulfonamide based fragments were subjected to a multi-step in silico strategy to afford potential SARS-CoV2 Mpro inhibitors.

MD simulations revealed less perceptible torsional distortions (more stable binding mode) in binding of ZINC_252512772 (ΔG_b -9.18 kcal/mol) into Mpro active site.

H-bond interactions and hydrophobic contacts were determinant forces in binding interactions of in silico hit.

Quantum chemical calculations confirmed MD results and proved pivotal role of a conserved residue (Glu166) in making permanent hydrogen bond (98% of MD simulations time) with ZINC_252512772.

Communicated by Ramaswamy H. Sarma

Efficient Production of Light Olefin Based on Methanol Dehydration: Simulation and Design Improvement

BACKGROUND

Ethylene, propylene, and butylene as light olefins are the most important intermediates in the petrochemical industry worldwide. Methanol to olefins (MTO) process is a new technology based on catalytic cracking to produce ethylene and propylene from methanol.

AIMS AND OBJECTIVE

This study aims to simulate the process of producing ethylene from methanol by using Aspen HYSYS software from the initial design to the improved design.

METHODS

Ethylene is produced in a two-step reaction. In an equilibrium reactor, the methanol is converted to dimethyl ether by an equilibrium reaction. The conversion of the produced dimethyl ether to ethylene is done in a conversion reactor. Changes have been made to improve the conditions and get closer to the actual process design carried out in the industry. The plug flow reactor has been replaced by the equilibrium reactor, and the distillation column was employed to separate the dimethyl ether produced from the reactor.

RESULT

The effect of the various parameters on the ethylene production was investigated. Eventually, ethylene is produced with a purity of 95.5 % in the improved design, and thermal integration was performed to minimize energy consumption.

CONCLUSION

It was finally found according to the exothermic reaction of the dimethyl ether production, thermal integration in the process reduces the energy consumption in the heater and cooler.

Identification and Analysis of Unstructured, Linear B-Cell Epitopes in SARS-CoV-2 Virion Proteins for Vaccine Development

The efficacy of SARS-CoV-2 nucleic acid-based vaccines may be limited by proteolysis of the translated product due to anomalous protein folding. This may be the case for vaccines employing linear SARS-CoV-2 B-cell epitopes identified in previous studies since most of them participate in secondary structure formation. In contrast, we have employed a consensus of predictors for epitopic zones plus a structural filter for identifying 20 unstructured B-cell epitope-containing loops (uBCELs) in S, M, and N proteins. Phylogenetic comparison suggests epitope switching with respect to SARS-CoV in some of the identified uBCELs. Such events may be associated with the reported lack of serum cross-protection between the 2003 and 2019 pandemic strains. Incipient variability within a sample of 1639 SARS-CoV-2 isolates was also detected for 10 uBCELs which could cause vaccine failure. Intermediate stages of the putative epitope switch events were observed in bat coronaviruses in which additive mutational processes possibly facilitating evasion of the bat immune system appear to have taken place prior to transfer to humans. While there was some overlap between uBCELs and previously validated SARS-CoV B-cell epitopes, multiple uBCELs had not been identified in prior studies. Overall, these uBCELs may facilitate the development of biomedical products for SARS-CoV-2.

COVID-19 and SARS-CoV-2. Modeling the present, looking at the future

Since December 2019 the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has produced an outbreak of pulmonary disease which has soon become a global pandemic, known as COronaVIrus Disease-19 (COVID-19). The new coronavirus shares about 82% of its genome with the one which produced the 2003 outbreak (SARS CoV-1). Both coronaviruses also share the same cellular receptor, which is the angiotensin-converting enzyme 2 (ACE2) one. In spite of these similarities, the new coronavirus has expanded more widely, more faster and more lethally than the previous one. Many researchers across the disciplines have used diverse modeling tools to analyze the impact of this pandemic at global and local scales. This includes a wide range of approaches - deterministic, data-driven, stochastic, agent-based, and their combinations - to forecast the progression of the epidemic as well as the effects of non-pharmaceutical interventions to stop or mitigate its impact on the world population. The physical complexities of modern society need to be captured by these models. This includes the many ways of social contacts - (multiplex) social contact networks, (multilayers) transport systems, metapopulations, etc. - that may act as a framework for the virus propagation. But modeling not only plays a fundamental role in analyzing and forecasting epidemiological variables, but it also plays an important role in helping to find cures for the disease and in preventing contagion by means of new vaccines. The necessity for answering swiftly and effectively the questions: could existing drugs work against SARS CoV-2? and can new vaccines be developed in time? demands the use of physical modeling of proteins, protein-inhibitors interactions, virtual screening of drugs against virus targets, predicting immunogenicity of small peptides, modeling vaccinomics and vaccine design, to mention just a few. Here, we review these three main areas of modeling research against SARS CoV-2 and COVID-19: (1) epidemiology; (2) drug repurposing; and (3) vaccine design. Therefore, we compile the most relevant existing literature about modeling strategies against the virus to help modelers to navigate this fast-growing literature. We also keep an eye on future outbreaks, where the modelers can find the most relevant strategies used in an emergency situation as the current one to help in fighting future pandemics.

Human Leukocyte Antigen Susceptibility Map for Severe Acute Respiratory Syndrome Coronavirus 2

Genetic variability across the three major histocompatibility complex (MHC) class I genes (human leukocyte antigen A [HLA-A], -B, and -C genes) may affect susceptibility to and severity of the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19). We performed a comprehensive in silico analysis of viral peptide-MHC class I binding affinity across 145 HLA-A, -B, and -C genotypes for all SARS-CoV-2 peptides. We further explored the potential for cross-protective immunity conferred by prior exposure to four common human coronaviruses. The SARS-CoV-2 proteome was successfully sampled and was represented by a diversity of HLA alleles. However, we found that HLA-B*46:01 had the fewest predicted binding peptides for SARS-CoV-2, suggesting that individuals with this allele may be particularly vulnerable to COVID-19, as they were previously shown to be for SARS (M. Lin, H.-T. Tseng, J. A. Trejaut, H.-L. Lee, et al., BMC Med Genet 4:9, 2003, https://bmcmedgenet.biomedcentral.com/articles/10.1186/1471-2350-4-9). Conversely, we found that HLA-B*15:03 showed the greatest capacity to present highly conserved SARS-CoV-2 peptides that are shared among common human coronaviruses, suggesting that it could enable cross-protective T-cell-based immunity. Finally, we reported global distributions of HLA types with potential epidemiological ramifications in the setting of the current pandemic.IMPORTANCE Individual genetic variation may help to explain different immune responses to a virus across a population. In particular, understanding how variation in HLA may affect the course of COVID-19 could help identify individuals at higher risk from the disease. HLA typing can be fast and inexpensive. Pairing HLA typing with COVID-19 testing where feasible could improve assessment of severity of viral disease in the population. Following the development of a vaccine against SARS-CoV-2, the virus that causes COVID-19, individuals with high-risk HLA types could be prioritized for vaccination.

Insights into SARS-CoV-2 genome, structure, evolution, pathogenesis and therapies: Structural genomics approach

The sudden emergence of severe respiratory disease, caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has recently become a public health emergency. Genome sequence analysis of SARS-CoV-2 revealed its close resemblance to the earlier reported SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). However, initial testing of the drugs used against SARS-CoV and MERS-CoV has been ineffective in controlling SARS-CoV-2. The present study highlights the genomic, proteomic, pathogenesis, and therapeutic strategies in SARS-CoV-2 infection. We have carried out sequence analysis of potential drug target proteins in SARS-CoV-2 and, compared them with SARS-CoV and MERS viruses. Analysis of mutations in the coding and non-coding regions, genetic diversity, and pathogenicity of SARS-CoV-2 has also been done. A detailed structural analysis of drug target proteins has been performed to gain insights into the mechanism of pathogenesis, structure-function relationships, and the development of structure-guided therapeutic approaches. The cytokine profiling and inflammatory signalling are different in the case of SARS-CoV-2 infection. We also highlighted possible therapies and their mechanism of action followed by clinical manifestation. Our analysis suggests a minimal variation in the genome sequence of SARS-CoV-2, may be responsible for a drastic change in the structures of target proteins, which makes available drugs ineffective.

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The recent exposure to SARS-CoV-2 has affected entire world, resulted >0.4 million deaths.

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Potential drug targets of SARS-CoV-2 are highly conserved.

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A slight structural difference makes available drugs ineffective against SARS-CoV-2.

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Cytokine storm during SARS-CoV-2 infection may be targeted to handle COVID-19 patients.

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Many FDA approved drugs are showing positive effects in clinical trials but further validation in large subject groups is required.

Bioinformatics studies on a function of the SARS-CoV-2 spike glycoprotein as the binding of host sialic acid glycans

SARS-CoV and SARS-CoV-2 do not appear to have functions of a hemagglutinin and neuraminidase. This is a mystery, because sugar binding activities appear essential to many other viruses including influenza and even most other coronaviruses in order to bind to and escape from the glycans (sugars, oligosaccharides or polysaccharides) characteristic of cell surfaces and saliva and mucin. The S1 N terminal Domains (S1-NTD) of the spike protein, largely responsible for the bulk of the characteristic knobs at the end of the spikes of SARS-CoV and SARS-CoV-2, are here predicted to be “hiding” sites for recognizing and binding glycans containing sialic acid. This may be important for infection and the ability of the virus to locate ACE2 as its known main host cell surface receptor, and if so it becomes a pharmaceutical target. It might even open up the possibility of an alternative receptor to ACE2. The prediction method developed, which uses amino acid residue sequence alone to predict domains or proteins that bind to sialic acids, is naïve, and will be advanced in future work. Nonetheless, it was surprising that such a very simple approach was so useful, and it can easily be reproduced in a very few lines of computer program to help make quick comparisons between SARS-CoV-2 sequences and to consider the effects of viral mutations.

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This paper extends the studies of the author's previous SARS-CoV-2 papers.

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Designing vaccine and drugs must seek to avoid escape mutations.

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Strangely, SARS-CoV and SARS-CoV-2 appear to lack sialic acid binding functions.

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Sequence motifs are found, but they require a simple prediction method.

Dynamics of Population Immunity Due to the Herd Effect in the COVID-19 Pandemic

The novel Coronavirus 2 Severe Acute Respiratory Syndrome (SARS-Cov-2) has led to the Coronavirus Disease 2019 (COVID-19) pandemic, which has surprised health authorities around the world, quickly producing a global health crisis. Different actions to cope with this situation are being developed, including confinement, different treatments to improve symptoms, and the creation of the first vaccines. In epidemiology, herd immunity is presented as an area that could also solve this new global threat. In this review, we present the basis of herd immunology, the dynamics of infection transmission that induces specific immunity, and how the application of immunoepidemiology and herd immunology could be used to control the actual COVID-19 pandemic, along with a discussion of its effectiveness, limitations, and applications.

COVID-19 Coronavirus spike protein analysis for synthetic vaccines, a peptidomimetic antagonist, and therapeutic drugs, and analysis of a proposed achilles' heel conserved region to minimize probability of escape mutations and drug resistance

This paper continues a recent study of the spike protein sequence of the COVID-19 virus (SARS-CoV-2). It is also in part an introductory review to relevant computational techniques for tackling viral threats, using COVID-19 as an example. Q-UEL tools for facilitating access to knowledge and bioinformatics tools were again used for efficiency, but the focus in this paper is even more on the virus. Subsequence KRSFIEDLLFNKV of the S2′ spike glycoprotein proteolytic cleavage site continues to appear important. Here it is shown to be recognizable in the common cold coronaviruses, avian coronaviruses and possibly as traces in the nidoviruses of reptiles and fish. Its function or functions thus seem important to the coronaviruses. It might represent SARS-CoV-2 Achilles’ heel, less likely to acquire resistance by mutation, as has happened in some early SARS vaccine studies discussed in the previous paper. Preliminary conformational analysis of the receptor (ACE2) binding site of the spike protein is carried out suggesting that while it is somewhat conserved, it appears to be more variable than KRSFIEDLLFNKV. However compounds like emodin that inhibit SARS entry, apparently by binding ACE2, might also have functions at several different human protein binding sites. The enzyme 11β-hydroxysteroid dehydrogenase type 1 is again argued to be a convenient model pharmacophore perhaps representing an ensemble of targets, and it is noted that it occurs both in lung and alimentary tract. Perhaps it benefits the virus to block an inflammatory response by inhibiting the dehydrogenase, but a fairly complex web involves several possible targets.

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This paper “drills down” into the studies of the author's previous COVID-19 paper.

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Designing vaccine and drugs must seek to avoid escape mutations.

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Subsequence KRSFIEDLLFNKV seems recognizable across many coronaviruses.

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The ACE2 binding domain is a target, but shows variation.

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A steroid dehydrogenase is argued to remain an interesting model pharmacophore.