A Review of the Potential Roles of Antioxidant and Anti-Inflammatory Pharmacological Approaches for the Management of Mild-to-Moderate Symptomatic COVID-19.

In the past 2 years, the coronavirus disease 2019 (COVID-19) pandemic has driven investigational studies and controlled clinical trials on antiviral treatments and vaccines that have undergone regulatory approval. Now that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants may become endemic over time, there remains a need to identify drugs that treat the symptoms of COVID-19 and prevent progression toward severe cases, hospitalization, and death. Understanding the molecular mechanisms of SARS-CoV-2 infection is extremely important for the development of effective therapies against COVID-19. This review outlines the key pathways involved in the host response to SARS-CoV-2 infection and discusses the potential role of antioxidant and anti-inflammatory pharmacological approaches for the management of early mild-to-moderate COVID-19, using the examples of combined indomethacin, low-dose aspirin, omeprazole, hesperidin, quercetin, and vitamin C. The pharmacological targets of these substances are described here for their possible synergism in counteracting SARS-CoV-2 replication and progression of the infection from the upper respiratory airways to the blood, avoiding vascular complications and cytokine and bradykinin storms.

Generation of Spike-Extracellular Vesicles (S-EVs) as a Tool to Mimic SARS-CoV-2 Interaction with Host Cells.

Extracellular vesicles (EVs) and viruses share common features: size, structure, biogenesis and uptake. In order to generate EVs expressing the SARS-CoV-2 spike protein on their surface (S-EVs), we collected EVs from SARS-CoV-2 spike expressing human embryonic kidney (HEK-293T) cells by stable transfection with a vector coding for the S1 and S2 subunits. S-EVs were characterized using nanoparticle tracking analysis, ExoView and super-resolution microscopy. We obtained a population of EVs of 50 to 200 nm in size. Spike expressing EVs represented around 40% of the total EV population and co-expressed spike protein with tetraspanins on the surfaces of EVs. We subsequently used ACE2-positive endothelial and bronchial epithelial cells for assessing the internalization of labeled S-EVs using a cytofluorimetric analysis. Internalization of S-EVs was higher than that of control EVs from non-transfected cells. Moreover, S-EV uptake was significantly decreased by anti-ACE2 antibody pre-treatment. Furthermore, colchicine, a drug currently used in clinical trials, significantly reduced S-EV entry into the cells. S-EVs represent a simple, safe, and scalable model to study host-virus interactions and the mechanisms of novel therapeutic drugs.

Lung disease network reveals impact of comorbidity on SARS-CoV-2 infection and opportunities of drug repurposing.

BACKGROUND: Higher mortality of COVID-19 patients with lung disease is a formidable challenge for the health care system. Genetic association between COVID-19 and various lung disorders must be understood to comprehend the molecular basis of comorbidity and accelerate drug development. METHODS: Lungs tissue-specific neighborhood network of human targets of SARS-CoV-2 was constructed. This network was integrated with lung diseases to build a disease-gene and disease-disease association network. Network-based toolset was used to identify the overlapping disease modules and drug targets. The functional protein modules were identified using community detection algorithms and biological processes, and pathway enrichment analysis. RESULTS: In total, 141 lung diseases were linked to a neighborhood network of SARS-CoV-2 targets, and 59 lung diseases were found to be topologically overlapped with the COVID-19 module. Topological overlap with various lung disorders allows repurposing of drugs used for these disorders to hit the closely associated COVID-19 module. Further analysis showed that functional protein-protein interaction modules in the lungs, substantially hijacked by SARS-CoV-2, are connected to several lung disorders. FDA-approved targets in the hijacked protein modules were identified and that can be hit by exiting drugs to rescue these modules from virus possession. CONCLUSION: Lung diseases are clustered with COVID-19 in the same network vicinity, indicating the potential threat for patients with respiratory diseases after SARS-CoV-2 infection. Pathobiological similarities between lung diseases and COVID-19 and clinical evidence suggest that shared molecular features are the probable reason for comorbidity. Network-based drug repurposing approaches can be applied to improve the clinical conditions of COVID-19 patients.

Immune-viral dynamics modeling for SARS-CoV-2 drug development.

Coronavirus disease 2019 (COVID-19) global pandemic is caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) viral infection, which can lead to pneumonia, lung injury, and death in susceptible populations. Understanding viral dynamics of SARS-CoV-2 is critical for development of effective treatments. An Immune-Viral Dynamics Model (IVDM) is developed to describe SARS-CoV-2 viral dynamics and COVID-19 disease progression. A dataset of 60 individual patients with COVID-19 with clinical viral load (VL) and reported disease severity were assembled from literature. Viral infection and replication mechanisms of SARS-CoV-2, viral-induced cell death, and time-dependent immune response are incorporated in the model to describe the dynamics of viruses and immune response. Disease severity are tested as a covariate to model parameters. The IVDM was fitted to the data and parameters were estimated using the nonlinear mixed-effect model. The model can adequately describe individual viral dynamics profiles, with disease severity identified as a covariate on infected cell death rate. The modeling suggested that it takes about 32.6 days to reach 50% of maximum cell-based immunity. Simulations based on virtual populations suggested a typical mild case reaches VL limit of detection (LOD) by 13 days with no treatment, a moderate case by 17 days, and a severe case by 41 days. Simulations were used to explore hypothetical treatments with different initiation time, disease severity, and drug effects to demonstrate the usefulness of such modeling in informing decisions. Overall, the IVDM modeling and simulation platform enables simulations for viral dynamics and treatment efficacy and can be used to aid in clinical pharmacokinetic/pharmacodynamic (PK/PD) and dose-efficacy response analysis for COVID-19 drug development.

Hard Nanomaterials in Time of Viral Pandemics.

The SARS-Cov-2 pandemic has spread worldwide during 2020, setting up an uncertain start of this decade. The measures to contain infection taken by many governments have been extremely severe by imposing home lockdown and industrial production shutdown, making this the biggest crisis since the second world war. Additionally, the continuous colonization of wild natural lands may touch unknown virus reservoirs, causing the spread of epidemics. Apart from SARS-Cov-2, the recent history has seen the spread of several viral pandemics such as H2N2 and H3N3 flu, HIV, and SARS, while MERS and Ebola viruses are considered still in a prepandemic phase. Hard nanomaterials (HNMs) have been recently used as antimicrobial agents, potentially being next-generation drugs to fight viral infections. HNMs can block infection at early (disinfection, entrance inhibition) and middle (inside the host cells) stages and are also able to mitigate the immune response. This review is focused on the application of HNMs as antiviral agents. In particular, mechanisms of actions, biological outputs, and limitations for each HNM will be systematically presented and analyzed from a material chemistry point-of-view. The antiviral activity will be discussed in the context of the different pandemic viruses. We acknowledge that HNM antiviral research is still at its early stage, however, we believe that this field will rapidly blossom in the next period.

Long Noncoding RNAs as Emerging Regulators of COVID-19.

Coronavirus disease 2019 (COVID-19), which has high incidence rates with rapid rate of transmission, is a pandemic that spread across the world, resulting in more than 3,000,000 deaths globally. Currently, several drugs have been used for the clinical treatment of COVID-19, such as antivirals (radecivir, baritinib), monoclonal antibodies (tocilizumab), and glucocorticoids (dexamethasone). Accumulating evidence indicates that long noncoding RNAs (lncRNAs) are essential regulators of virus infections and antiviral immune responses including biological processes that are involved in the regulation of COVID-19 and subsequent disease states. Upon viral infections, cellular lncRNAs directly regulate viral genes and influence viral replication and pathology through virus-mediated changes in the host transcriptome. Additionally, several host lncRNAs could help the occurrence of viral immune escape by inhibiting type I interferons (IFN-1), while others could up-regulate IFN-1 production to play an antiviral role. Consequently, understanding the expression and function of lncRNAs during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection will provide insights into the development of lncRNA-based methods. In this review, we summarized the current findings of lncRNAs in the regulation of the strong inflammatory response, immune dysfunction and thrombosis induced by SARS-CoV-2 infection, discussed the underlying mechanisms, and highlighted the therapeutic challenges of COVID-19 treatment and its future research directions.

LUNAR :Drug Screening for Novel Coronavirus Based on Representation Learning Graph Convolutional Network.

An outbreak of COVID-19 that began in late 2019 was caused by a novel coronavirus(SARS-CoV-2). It has become a global pandemic. As of June 9, 2020, it has infected nearly 7 million people and killed more than 400,000, but there is no specific drug. Therefore, there is an urgent need to find or develop more drugs to suppress the virus. Here, we propose a new nonlinear end-to-end model called LUNAR. It uses graph convolutional neural networks to automatically learn the neighborhood information of complex heterogeneous relational networks and combines the attention mechanism to reflect the importance of the sum of different types of neighborhood information to obtain the representation characteristics of each node. Finally, through the topology reconstruction process, the feature representations of drugs and targets are forcibly extracted to match the observed network as much as possible. Through this reconstruction process, we obtain the strength of the relationship between different nodes and predict drug candidates that may affect the treatment of COVID-19 based on the known targets of COVID-19. These selected candidate drugs can be used as a reference for experimental scientists and accelerate the speed of drug development. LUNAR can well integrate various topological structure information in heterogeneous networks, and skillfully combine attention mechanisms to reflect the importance of neighborhood information of different types of nodes, improving the interpretability of the model. The area under the curve(AUC) of the model is 0.949 and the accurate recall curve (AUPR) is 0.866 using 10-fold cross-validation. These two performance indexes show that the model has superior predictive performance. Besides, some of the drugs screened out by our model have appeared in some clinical studies to further illustrate the effectiveness of the model.

Long-chain polyphosphates impair SARS-CoV-2 infection and replication.

Inorganic polyphosphates (polyPs) are linear polymers composed of repeated phosphate (PO4 3-) units linked together by multiple high-energy phosphoanhydride bonds. In addition to being a source of energy, polyPs have cytoprotective and antiviral activities. Here, we investigated the antiviral activities of long-chain polyPs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In molecular docking analyses, polyPs interacted with several conserved amino acid residues in angiotensin-converting enzyme 2 (ACE2), the host receptor that facilitates virus entry, and in viral RNA-dependent RNA polymerase (RdRp). ELISA and limited proteolysis assays using nano- LC-MS/MS mapped polyP120 binding to ACE2, and site-directed mutagenesis confirmed interactions between ACE2 and SARS-CoV-2 RdRp and identified the specific amino acid residues involved. PolyP120 enhanced the proteasomal degradation of both ACE2 and RdRp, thus impairing replication of the British B.1.1.7 SARS-CoV-2 variant. We thus tested polyPs for functional interactions with the virus in SARS-CoV-2-infected Vero E6 and Caco2 cells and in primary human nasal epithelial cells. Delivery of a nebulized form of polyP120 reduced the amounts of viral positive-sense genomic and subgenomic RNAs, of RNA transcripts encoding proinflammatory cytokines, and of viral structural proteins, thereby presenting SARS-CoV-2 infection in cells in vitro.

Compartmental Model Suggests Importance of Innate Immune Response to COVID-19 Infection in Rhesus Macaques.

The pandemic outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has quickly spread worldwide, creating a serious health crisis. The virus is primarily associated with flu-like symptoms but can also lead to severe pathologies and death. We here present an ordinary differential equation model of the intrahost immune response to SARS-CoV-2 infection, fitted to experimental data gleaned from rhesus macaques. The model is calibrated to data from a nonlethal infection, but the model can replicate behavior from various lethal scenarios as well. We evaluate the sensitivity of the model to biologically relevant parameters governing the strength and efficacy of the immune response. We also simulate the effect of both anti-inflammatory and antiviral drugs on the host immune response and demonstrate the ability of the model to lessen the severity of a formerly lethal infection with the addition of the appropriately calibrated drug. Our model emphasizes the importance of tight control of the innate immune response for host survival and viral clearance.

Detection of Binding Sites on SARS-CoV-2 Spike Protein Receptor-Binding Domain by Molecular Dynamics Simulations in Mixed Solvents.

The novel SARS-CoV-2 uses ACE2 (Angiotensin-Converting Enzyme 2) receptor as an entry point. Insights on S protein receptor-binding domain (RBD) interaction with ACE2 receptor and drug repurposing has accelerated drug discovery for the novel SARS-CoV-2 infection. Finding small molecule binding sites in S protein and ACE2 interface is crucial in search of effective drugs to prevent viral entry. In this study, we employed molecular dynamics simulations in mixed solvents together with virtual screening to identify small molecules that could be potential inhibitors of S protein -ACE2 interaction. Observation of organic probe molecule localization during the simulations revealed multiple sites at the S protein surface related to small molecule, antibody, and ACE2 binding. In addition, a novel conformation of the S protein was discovered that could be stabilized by small molecules to inhibit attachment to ACE2. The most promising binding site on RBD-ACE2 interface was targeted with virtual screening and top-ranked compounds (DB08248, DB02651, DB03714, and DB14826) are suggested for experimental testing. The protocol described here offers an extremely fast method for characterizing key proteins of a novel pathogen and for the identification of compounds that could inhibit or accelerate spreading of the disease.

Network-Based Analysis of Fatal Comorbidities of COVID-19 and Potential Therapeutics.

COVID-19 is a highly contagious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The case-fatality rate is significantly higher in older patients and those with diabetes, cancer or cardiovascular disorders. The human proteins, angiotensin-converting enzyme 2 (ACE2), transmembrane protease serine 2 (TMPRSS2) and basigin (BSG), are involved in high-confidence host-pathogen interactions with SARS-CoV-2 proteins. We considered these three proteins as seed nodes and applied the random walk with restart method on the human interactome to construct a protein-protein interaction sub-network, which captures the effects of viral invasion. We found that 'Insulin resistance', 'AGE-RAGE signaling in diabetic complications' and 'adipocytokine signaling' were the common pathways associated with diabetes, cancer and cardiovascular disorders. The association of these critical pathways with aging and its related diseases explains the molecular basis of COVID-19 fatality. We further identified drugs that have effects on these proteins/pathways based on gene expression studies. We particularly focused on drugs that significantly downregulate ACE2 along with other critical proteins identified by the network-based approach. Among them, COL-3 had earlier shown activity against acute lung injury and acute respiratory distress, while entinostat and mocetinostat have been investigated for non-small-cell lung cancer. We propose that these drugs can be repurposed for COVID-19.

Evidence that Maackia amurensis seed lectin (MASL) exerts pleiotropic actions on oral squamous cells with potential to inhibit SARS-CoV-2 infection and COVID-19 disease progression.

COVID-19 was declared an international public health emergency in January, and a pandemic in March of 2020. There are over 125 million confirmed COVID-19 cases that have caused over 2.7 million deaths worldwide as of March 2021. COVID-19 is caused by the SARS-CoV-2 virus. SARS-CoV-2 presents a surface "spike" protein that binds to the ACE2 receptor to infect host cells. In addition to the respiratory tract, SARS-Cov-2 can also infect cells of the oral mucosa, which also express the ACE2 receptor. The spike and ACE2 proteins are highly glycosylated with sialic acid modifications that direct viral-host interactions and infection. Maackia amurensis seed lectin (MASL) has a strong affinity for sialic acid modified proteins and can be used as an antiviral agent. Here, we report that MASL targets the ACE2 receptor, decreases ACE2 expression and glycosylation, suppresses binding of the SARS-CoV-2 spike protein, and decreases expression of inflammatory mediators by oral epithelial cells that cause ARDS in COVID-19 patients. In addition, we report that MASL also inhibits SARS-CoV-2 infection of kidney epithelial cells in culture. This work identifies MASL as an agent with potential to inhibit SARS-CoV-2 infection and COVID-19 related inflammatory syndromes.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

CoronaPep: An Anti-Coronavirus Peptide Generation Tool.

The novel coronavirus (COVID-19) infections have adopted the shape of a global pandemic now, demanding an urgent vaccine design. The current work reports contriving an anti-coronavirus peptide scanner tool to discern anti-coronavirus targets in the embodiment of peptides. The proffered CoronaPep tool features the fast fingerprinting of the anti-coronavirus target serving supreme prominence in the current bioinformatics research. The anti-coronavirus target protein sequences reported from the current outbreak are scanned against the anti-coronavirus target data-sets via CORONAPEP which provides precision-based anti-coronavirus peptides. This tool is specifically for the coronavirus data, which can predict peptides from the whole genome, or a gene or protein's list. Besides it is relatively fast, accurate, userfriendly and can generate maximum output from the limited information. The availability of tools like CORONAPEP will immeasurably perquisite researchers in the discipline of oncology and structure-based drug design.

Success of prophylactic antiviral therapy for SARS-CoV-2: Predicted critical efficacies and impact of different drug-specific mechanisms of action.

Repurposed drugs that are safe and immediately available constitute a first line of defense against new viral infections. Despite limited antiviral activity against SARS-CoV-2, several drugs are being tested as medication or as prophylaxis to prevent infection. Using a stochastic model of early phase infection, we evaluate the success of prophylactic treatment with different drug types to prevent viral infection. We find that there exists a critical efficacy that a treatment must reach in order to block viral establishment. Treatment by a combination of drugs reduces the critical efficacy, most effectively by the combination of a drug blocking viral entry into cells and a drug increasing viral clearance. Below the critical efficacy, the risk of infection can nonetheless be reduced. Drugs blocking viral entry into cells or enhancing viral clearance reduce the risk of infection more than drugs that reduce viral production in infected cells. The larger the initial inoculum of infectious virus, the less likely is prevention of an infection. In our model, we find that as long as the viral inoculum is smaller than 10 infectious virus particles, viral infection can be prevented almost certainly with drugs of 90% efficacy (or more). Even when a viral infection cannot be prevented, antivirals delay the time to detectable viral loads. The largest delay of viral infection is achieved by drugs reducing viral production in infected cells. A delay of virus infection flattens the within-host viral dynamic curve, possibly reducing transmission and symptom severity. Thus, antiviral prophylaxis, even with reduced efficacy, could be efficiently used to prevent or alleviate infection in people at high risk.

In well-differentiated primary human bronchial epithelial cells, TGF-ß1 and TGF-ß2 induce expression of furin.

The COVID-19 pandemic is an ongoing threat to public health. Since the identification of COVID-19, the disease caused by SARS-CoV-2, no drugs have been developed to specifically target SARS-CoV-2. To develop effective and safe treatment options, a better understanding of cellular mechanisms underlying SARS-CoV-2 infection is required. To fill this knowledge gap, researchers require reliable experimental systems that express the host factor proteins necessary for the cellular entry of SARS-CoV-2. These proteins include the viral receptor, angiotensin-converting enzyme 2 (ACE2), and the proteases, transmembrane serine protease 2 (TMPRSS2) and furin. A number of studies have reported cell-type-specific expression of the genes encoding these molecules. However, less is known about the protein expression of these molecules. We assessed the suitability of primary human bronchial epithelial (HBE) cells maintained in an air-liquid interface (ALI) as an experimental system for studying SARS-CoV-2 infection in vitro. During cellular differentiation, we measured the expression of ACE2, TMPRSS2, and furin over progressive ALI days by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), Western blot, and immunofluorescence staining. We also explored the effect of the fibrotic cytokine TGF-ß on the expression of these proteins in well-differentiated HBE cells. Like ACE2, TMPRSS2 and furin proteins are localized in differentiated ciliated cells, as confirmed by immunofluorescence staining. These data suggest that well-differentiated HBE cells maintained in ALI are a reliable in vitro system for investigating cellular mechanisms of SARS-CoV-2 infection. We further identified that the profibrotic mediators, TGF-ß1 and TGF-ß2, increase the expression of furin, which is a protease required for the cellular entry of SARS-CoV-2.

SAveRUNNER: A network-based algorithm for drug repurposing and its application to COVID-19.

The novelty of new human coronavirus COVID-19/SARS-CoV-2 and the lack of effective drugs and vaccines gave rise to a wide variety of strategies employed to fight this worldwide pandemic. Many of these strategies rely on the repositioning of existing drugs that could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we presented a new network-based algorithm for drug repositioning, called SAveRUNNER (Searching off-lAbel dRUg aNd NEtwoRk), which predicts drug-disease associations by quantifying the interplay between the drug targets and the disease-specific proteins in the human interactome via a novel network-based similarity measure that prioritizes associations between drugs and diseases locating in the same network neighborhoods. Specifically, we applied SAveRUNNER on a panel of 14 selected diseases with a consolidated knowledge about their disease-causing genes and that have been found to be related to COVID-19 for genetic similarity (i.e., SARS), comorbidity (e.g., cardiovascular diseases), or for their association to drugs tentatively repurposed to treat COVID-19 (e.g., malaria, HIV, rheumatoid arthritis). Focusing specifically on SARS subnetwork, we identified 282 repurposable drugs, including some the most rumored off-label drugs for COVID-19 treatments (e.g., chloroquine, hydroxychloroquine, tocilizumab, heparin), as well as a new combination therapy of 5 drugs (hydroxychloroquine, chloroquine, lopinavir, ritonavir, remdesivir), actually used in clinical practice. Furthermore, to maximize the efficiency of putative downstream validation experiments, we prioritized 24 potential anti-SARS-CoV repurposable drugs based on their network-based similarity values. These top-ranked drugs include ACE-inhibitors, monoclonal antibodies (e.g., anti-IFNγ, anti-TNFα, anti-IL12, anti-IL1ß, anti-IL6), and thrombin inhibitors. Finally, our findings were in-silico validated by performing a gene set enrichment analysis, which confirmed that most of the network-predicted repurposable drugs may have a potential treatment effect against human coronavirus infections.

Human coronavirus dependency on host heat shock protein 90 reveals an antiviral target.

Rapid accumulation of viral proteins in host cells render viruses highly dependent on cellular chaperones including heat shock protein 90 (Hsp90). Three highly pathogenic human coronaviruses, including MERS-CoV, SARS-CoV and SARS-CoV-2, have emerged in the past 2 decades. However, there is no approved antiviral agent against these coronaviruses. We inspected the role of Hsp90 for coronavirus propagation. First, an Hsp90 inhibitor, 17-AAG, significantly suppressed MERS-CoV propagation in cell lines and physiological-relevant human intestinal organoids. Second, siRNA depletion of Hsp90ß, but not Hsp90α, significantly restricted MERS-CoV replication and abolished virus spread. Third, Hsp90ß interaction with MERS-CoV nucleoprotein (NP) was revealed in a co-immunoprecipitation assay. Hsp90ß is required to maintain NP stability. Fourth, 17-AAG substantially inhibited the propagation of SARS-CoV and SARS-CoV-2. Collectively, Hsp90 is a host dependency factor for human coronavirus MERS-CoV, SARS-CoV and SARS-COV-2. Hsp90 inhibitors can be repurposed as a potent and broad-spectrum antiviral against human coronaviruses.

Hypothesis: Alpha-1-antitrypsin is a promising treatment option for COVID-19.

No definitive treatment for COVID-19 exists although promising results have been reported with remdesivir and glucocorticoids. Short of a truly effective preventive or curative vaccine against SARS-CoV-2, it is becoming increasingly clear that multiple pathophysiologic processes seen with COVID-19 as well as SARS-CoV-2 itself should be targeted. Because alpha-1-antitrypsin (AAT) embraces a panoply of biologic activities that may antagonize several pathophysiologic mechanisms induced by SARS-CoV-2, we hypothesize that this naturally occurring molecule is a promising agent to ameliorate COVID-19. We posit at least seven different mechanisms by which AAT may alleviate COVID-19. First, AAT is a serine protease inhibitor (SERPIN) shown to inhibit TMPRSS-2, the host serine protease that cleaves the spike protein of SARS-CoV-2, a necessary preparatory step for the virus to bind its cell surface receptor ACE2 to gain intracellular entry. Second, AAT has anti-viral activity against other RNA viruses HIV and influenza as well as induces autophagy, a known host effector mechanism against MERS-CoV, a related coronavirus that causes the Middle East Respiratory Syndrome. Third, AAT has potent anti-inflammatory properties, in part through inhibiting both nuclear factor-kappa B (NFκB) activation and ADAM17 (also known as tumor necrosis factor-alpha converting enzyme), and thus may dampen the hyper-inflammatory response of COVID-19. Fourth, AAT inhibits neutrophil elastase, a serine protease that helps recruit potentially injurious neutrophils and implicated in acute lung injury. AAT inhibition of ADAM17 also prevents shedding of ACE2 and hence may preserve ACE2 inhibition of bradykinin, reducing the ability of bradykinin to cause a capillary leak in COVID-19. Fifth, AAT inhibits thrombin, and venous thromboembolism and in situ microthrombi and macrothrombi are increasingly implicated in COVID-19. Sixth, AAT inhibition of elastase can antagonize the formation of neutrophil extracellular traps (NETs), a complex extracellular structure comprised of neutrophil-derived DNA, histones, and proteases, and implicated in the immunothrombosis of COVID-19; indeed, AAT has been shown to change the shape and adherence of non-COVID-19-related NETs. Seventh, AAT inhibition of endothelial cell apoptosis may limit the endothelial injury linked to severe COVID-19-associated acute lung injury, multi-organ dysfunction, and pre-eclampsia-like syndrome seen in gravid women. Furthermore, because both NETs formation and the presence of anti-phospholipid antibodies are increased in both COVID-19 and non-COVID pre-eclampsia, it suggests a similar vascular pathogenesis in both disorders. As a final point, AAT has an excellent safety profile when administered to patients with AAT deficiency and is dosed intravenously once weekly but also comes in an inhaled preparation. Thus, AAT is an appealing drug candidate to treat COVID-19 and should be studied.

Inhibition of SARS-CoV-2 viral entry upon blocking N- and O-glycan elaboration.

The Spike protein of SARS-CoV-2, its receptor-binding domain (RBD), and its primary receptor ACE2 are extensively glycosylated. The impact of this post-translational modification on viral entry is yet unestablished. We expressed different glycoforms of the Spike-protein and ACE2 in CRISPR-Cas9 glycoengineered cells, and developed corresponding SARS-CoV-2 pseudovirus. We observed that N- and O-glycans had only minor contribution to Spike-ACE2 binding. However, these carbohydrates played a major role in regulating viral entry. Blocking N-glycan biosynthesis at the oligomannose stage using both genetic approaches and the small molecule kifunensine dramatically reduced viral entry into ACE2 expressing HEK293T cells. Blocking O-glycan elaboration also partially blocked viral entry. Mechanistic studies suggest multiple roles for glycans during viral entry. Among them, inhibition of N-glycan biosynthesis enhanced Spike-protein proteolysis. This could reduce RBD presentation on virus, lowering binding to host ACE2 and decreasing viral entry. Overall, chemical inhibitors of glycosylation may be evaluated for COVID-19.

COVID-19 is an infectious disease caused by the virus SARS-CoV-2. To access the internal machinery necessary for its replication, the virus needs to latch onto and then enter host cells. Such processes rely on specific 'glycoproteins' that carry complex sugar molecules (or glycans), and can be found at the surface of both viruses and host cells. In particular, the viral 'Spike' glycoprotein can attach to human proteins called ACE2, which coat the cells that line the inside of the lungs, heart, kidney and brain. Yet the roles played by glycans in these processes remains unclear. To investigate the role of Spike and ACE-2 glycans, Yang et al. designed a form of SARS-CoV-2 that could be handled safely in the laboratory. How these viruses infect human kidney cells that carry ACE2 was then examined, upon modifying the structures of the sugars on the viral Spike protein as well as the host ACE2 receptor. In particular, the sugar structures displayed by the virus were modified either genetically or chemically, using a small molecule that disrupts the formation of the glycans. Similar methods were also applied to modify the glycans of ACE2. Together, these experiments showed that the sugars present on the Spike protein play a minor role in helping the virus stick to human cells.However, they were critical for the virus to fuse and enter the host cells. These findings highlight the important role of Spike protein sugars in SARS-CoV-2 infection, potentially offering new paths to treat COVID-19 and other coronavirus-related illnesses. In particular, molecules designed to interfere with Spike-proteins and the viral entrance into cells could be less specific to SARS-CoV-2 compared to vaccines, allowing treatments to be efficient even if the virus changes.