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1.
Med Sci Monit ; 28: e936292, 2022 Mar 08.
Article in English | MEDLINE | ID: covidwho-1732487

ABSTRACT

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.


Subject(s)
COVID-19/drug therapy , Host Microbial Interactions/drug effects , SARS-CoV-2/drug effects , Anti-Inflammatory Agents/pharmacology , Antioxidants/pharmacology , Antiviral Agents/therapeutic use , Endemic Diseases , Host Microbial Interactions/physiology , Humans , Pharmacological Phenomena/physiology , SARS-CoV-2/pathogenicity
2.
Cells ; 11(1)2022 01 03.
Article in English | MEDLINE | ID: covidwho-1580990

ABSTRACT

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.


Subject(s)
COVID-19/metabolism , Extracellular Vesicles/metabolism , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/metabolism , Angiotensin-Converting Enzyme 2/immunology , Antibodies, Blocking/pharmacology , COVID-19/virology , Cell Line , Cells, Cultured , Colchicine/pharmacology , Flow Cytometry/methods , HEK293 Cells , Host Microbial Interactions/drug effects , Human Umbilical Vein Endothelial Cells/metabolism , Human Umbilical Vein Endothelial Cells/virology , Humans , Microscopy, Fluorescence/methods , Protein Binding/drug effects , SARS-CoV-2/physiology
3.
J Allergy Clin Immunol ; 149(3): 923-933.e6, 2022 03.
Article in English | MEDLINE | ID: covidwho-1560006

ABSTRACT

BACKGROUND: Treatments for coronavirus disease 2019, which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), are urgently needed but remain limited. SARS-CoV-2 infects cells through interactions of its spike (S) protein with angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2) on host cells. Multiple cells and organs are targeted, particularly airway epithelial cells. OM-85, a standardized lysate of human airway bacteria with strong immunomodulating properties and an impeccable safety profile, is widely used to prevent recurrent respiratory infections. We found that airway OM-85 administration inhibits Ace2 and Tmprss2 transcription in the mouse lung, suggesting that OM-85 might hinder SARS-CoV-2/host cell interactions. OBJECTIVES: We sought to investigate whether and how OM-85 treatment protects nonhuman primate and human epithelial cells against SARS-CoV-2. METHODS: ACE2 and TMPRSS2 mRNA and protein expression, cell binding of SARS-CoV-2 S1 protein, cell entry of SARS-CoV-2 S protein-pseudotyped lentiviral particles, and SARS-CoV-2 cell infection were measured in kidney, lung, and intestinal epithelial cell lines, primary human bronchial epithelial cells, and ACE2-transfected HEK293T cells treated with OM-85 in vitro. RESULTS: OM-85 significantly downregulated ACE2 and TMPRSS2 transcription and surface ACE2 protein expression in epithelial cell lines and primary bronchial epithelial cells. OM-85 also strongly inhibited SARS-CoV-2 S1 protein binding to, SARS-CoV-2 S protein-pseudotyped lentivirus entry into, and SARS-CoV-2 infection of epithelial cells. These effects of OM-85 appeared to depend on SARS-CoV-2 receptor downregulation. CONCLUSIONS: OM-85 inhibits SARS-CoV-2 epithelial cell infection in vitro by downregulating SARS-CoV-2 receptor expression. Further studies are warranted to assess whether OM-85 may prevent and/or reduce the severity of coronavirus disease 2019.


Subject(s)
Adjuvants, Immunologic/administration & dosage , COVID-19/prevention & control , Cell Extracts/administration & dosage , Receptors, Virus/antagonists & inhibitors , Receptors, Virus/immunology , SARS-CoV-2/immunology , Angiotensin-Converting Enzyme 2/antagonists & inhibitors , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/immunology , Animals , COVID-19/immunology , COVID-19/virology , Caco-2 Cells , Cell Extracts/immunology , Cells, Cultured , Chlorocebus aethiops , Down-Regulation/drug effects , Epithelial Cells/drug effects , Epithelial Cells/immunology , Epithelial Cells/virology , HEK293 Cells , Host Microbial Interactions/drug effects , Host Microbial Interactions/immunology , Humans , In Vitro Techniques , Lung/drug effects , Lung/immunology , Lung/virology , Mice , Mice, Inbred BALB C , Serine Endopeptidases/drug effects , Serine Endopeptidases/genetics , Serine Endopeptidases/immunology , Transcription, Genetic/drug effects , Transcription, Genetic/immunology , Vero Cells
4.
BMC Med Genomics ; 14(1): 226, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1542114

ABSTRACT

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.


Subject(s)
COVID-19/drug therapy , COVID-19/epidemiology , Drug Repositioning , Lung Diseases/epidemiology , Pandemics , SARS-CoV-2 , Algorithms , Antiviral Agents/therapeutic use , COVID-19/genetics , Comorbidity , Drug Discovery , Drug Repositioning/methods , Gene Regulatory Networks/drug effects , Host Microbial Interactions/drug effects , Host Microbial Interactions/genetics , Humans , Lung Diseases/drug therapy , Lung Diseases/genetics , Protein Interaction Maps/drug effects , Protein Interaction Maps/genetics , Systems Biology
5.
Clin Transl Sci ; 14(6): 2348-2359, 2021 11.
Article in English | MEDLINE | ID: covidwho-1526356

ABSTRACT

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.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , Drug Development/methods , Host Microbial Interactions/immunology , Models, Biological , Antiviral Agents/therapeutic use , COVID-19/diagnosis , COVID-19/immunology , COVID-19/virology , Cell Death/drug effects , Cell Death/immunology , Datasets as Topic , Dose-Response Relationship, Drug , Host Microbial Interactions/drug effects , Humans , Nonlinear Dynamics , SARS-CoV-2/drug effects , SARS-CoV-2/immunology , Severity of Illness Index , Treatment Outcome , Viral Load
6.
ACS Nano ; 14(8): 9364-9388, 2020 08 25.
Article in English | MEDLINE | ID: covidwho-1387150

ABSTRACT

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.


Subject(s)
Antiviral Agents/therapeutic use , Betacoronavirus , Coronavirus Infections/therapy , Nanostructures/therapeutic use , Pandemics , Pneumonia, Viral/therapy , Adaptive Immunity , Betacoronavirus/drug effects , Betacoronavirus/physiology , Betacoronavirus/ultrastructure , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Drug Delivery Systems , Fullerenes/therapeutic use , Host Microbial Interactions/drug effects , Humans , Immunity, Innate , Metal Nanoparticles/therapeutic use , Models, Biological , Nanotechnology , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Reactive Oxygen Species/therapeutic use , SARS-CoV-2 , Virus Internalization/drug effects
7.
Front Immunol ; 12: 700184, 2021.
Article in English | MEDLINE | ID: covidwho-1365542

ABSTRACT

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.


Subject(s)
COVID-19/immunology , Host Microbial Interactions/genetics , Immunity, Innate/genetics , RNA, Long Noncoding/metabolism , Thrombosis/immunology , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , Biomarkers/analysis , COVID-19/complications , COVID-19/drug therapy , COVID-19/genetics , COVID-19 Testing/methods , Cytokines/genetics , Cytokines/metabolism , Gene Expression Regulation, Viral/drug effects , Gene Expression Regulation, Viral/immunology , Host Microbial Interactions/drug effects , Host Microbial Interactions/immunology , Humans , Immune Evasion/genetics , Pandemics/prevention & control , RNA, Long Noncoding/analysis , RNA, Long Noncoding/antagonists & inhibitors , SARS-CoV-2/drug effects , SARS-CoV-2/genetics , SARS-CoV-2/immunology , SARS-CoV-2/pathogenicity , Signal Transduction/genetics , Signal Transduction/immunology , Thrombosis/genetics , Thrombosis/virology , Virus Replication/drug effects , Virus Replication/genetics , Virus Replication/immunology
8.
IEEE/ACM Trans Comput Biol Bioinform ; 18(4): 1290-1298, 2021.
Article in English | MEDLINE | ID: covidwho-1349906

ABSTRACT

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.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , COVID-19/virology , Drug Evaluation, Preclinical/methods , Neural Networks, Computer , SARS-CoV-2/drug effects , COVID-19/epidemiology , Computational Biology , Databases, Pharmaceutical/statistics & numerical data , Drug Development/methods , Drug Development/statistics & numerical data , Drug Evaluation, Preclinical/statistics & numerical data , Drug Repositioning/methods , Drug Repositioning/statistics & numerical data , Host Microbial Interactions/drug effects , Humans , Nonlinear Dynamics , Pandemics
9.
Sci Signal ; 14(690)2021 07 06.
Article in English | MEDLINE | ID: covidwho-1299215

ABSTRACT

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.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , Polyphosphates/pharmacology , SARS-CoV-2/drug effects , Administration, Inhalation , Amino Acid Sequence , Angiotensin-Converting Enzyme 2/chemistry , Angiotensin-Converting Enzyme 2/metabolism , Animals , Antiviral Agents/administration & dosage , Antiviral Agents/chemistry , COVID-19/metabolism , COVID-19/virology , Caco-2 Cells , Chlorocebus aethiops , Coronavirus RNA-Dependent RNA Polymerase/chemistry , Coronavirus RNA-Dependent RNA Polymerase/genetics , Coronavirus RNA-Dependent RNA Polymerase/metabolism , Cytokines/metabolism , HEK293 Cells , Host Microbial Interactions/drug effects , Host Microbial Interactions/genetics , Host Microbial Interactions/physiology , Humans , In Vitro Techniques , Models, Biological , Molecular Docking Simulation , Nebulizers and Vaporizers , Polyphosphates/administration & dosage , Polyphosphates/chemistry , Proteasome Endopeptidase Complex/metabolism , Protein Interaction Domains and Motifs , Proteolysis/drug effects , RNA, Viral/genetics , RNA, Viral/metabolism , SARS-CoV-2/genetics , SARS-CoV-2/physiology , Sequence Homology, Amino Acid , Signal Transduction/drug effects , Vero Cells , Virus Replication/drug effects
10.
Clin Transl Sci ; 14(6): 2348-2359, 2021 11.
Article in English | MEDLINE | ID: covidwho-1268104

ABSTRACT

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.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , Drug Development/methods , Host Microbial Interactions/immunology , Models, Biological , Antiviral Agents/therapeutic use , COVID-19/diagnosis , COVID-19/immunology , COVID-19/virology , Cell Death/drug effects , Cell Death/immunology , Datasets as Topic , Dose-Response Relationship, Drug , Host Microbial Interactions/drug effects , Humans , Nonlinear Dynamics , SARS-CoV-2/drug effects , SARS-CoV-2/immunology , Severity of Illness Index , Treatment Outcome , Viral Load
11.
Bull Math Biol ; 83(7): 79, 2021 05 26.
Article in English | MEDLINE | ID: covidwho-1242816

ABSTRACT

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.


Subject(s)
COVID-19/immunology , Immunity, Innate , Macaca mulatta/immunology , Models, Immunological , SARS-CoV-2 , Adaptive Immunity , Aging/immunology , Animals , Anti-Inflammatory Agents/administration & dosage , Anti-Inflammatory Agents/pharmacology , Antiviral Agents/administration & dosage , Antiviral Agents/pharmacology , COVID-19/drug therapy , COVID-19/epidemiology , Computer Simulation , Disease Models, Animal , Dose-Response Relationship, Drug , Host Microbial Interactions/drug effects , Host Microbial Interactions/immunology , Humans , Mathematical Concepts , Pandemics , Respiratory System/immunology , Respiratory System/virology , SARS-CoV-2/immunology , Viral Load/immunology
12.
IEEE/ACM Trans Comput Biol Bioinform ; 18(4): 1281-1289, 2021.
Article in English | MEDLINE | ID: covidwho-1207370

ABSTRACT

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.


Subject(s)
COVID-19/virology , SARS-CoV-2/chemistry , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/metabolism , Angiotensin-Converting Enzyme 2/chemistry , Angiotensin-Converting Enzyme 2/metabolism , Antiviral Agents/pharmacology , Binding Sites , COVID-19/drug therapy , COVID-19/metabolism , Computational Biology , Computer Simulation , Crystallography, X-Ray , Drug Design , Drug Discovery , Drug Evaluation, Preclinical , Drug Repositioning , Host Microbial Interactions/drug effects , Host Microbial Interactions/physiology , Humans , Ligands , Molecular Dynamics Simulation , Protein Binding , Protein Interaction Domains and Motifs , SARS-CoV-2/drug effects , Solvents , User-Computer Interface
13.
IEEE/ACM Trans Comput Biol Bioinform ; 18(4): 1271-1280, 2021.
Article in English | MEDLINE | ID: covidwho-1199626

ABSTRACT

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.


Subject(s)
COVID-19/mortality , SARS-CoV-2 , Angiotensin-Converting Enzyme 2/antagonists & inhibitors , Angiotensin-Converting Enzyme 2/genetics , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/epidemiology , COVID-19/therapy , Cardiovascular Diseases/epidemiology , Comorbidity , Computational Biology , Drug Repositioning , Gastrointestinal Diseases/epidemiology , Gene Expression Profiling/statistics & numerical data , Host Microbial Interactions/drug effects , Host Microbial Interactions/genetics , Host Microbial Interactions/physiology , Humans , Pandemics , Protein Interaction Maps/drug effects , Respiratory Tract Diseases/epidemiology , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity , SARS-CoV-2/physiology
14.
Exp Cell Res ; 403(1): 112594, 2021 06 01.
Article in English | MEDLINE | ID: covidwho-1171431

ABSTRACT

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.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , Lectins/pharmacology , Mouth/drug effects , SARS-CoV-2/drug effects , Spike Glycoprotein, Coronavirus/drug effects , Disease Progression , Epithelial Cells/drug effects , Epithelial Cells/metabolism , Host Microbial Interactions/drug effects , Humans , Maackia/metabolism , SARS-CoV-2/pathogenicity , Spike Glycoprotein, Coronavirus/metabolism
15.
Nat Commun ; 12(1): 1660, 2021 03 12.
Article in English | MEDLINE | ID: covidwho-1132065

ABSTRACT

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.


Subject(s)
COVID-19/genetics , COVID-19/virology , SARS-CoV-2/genetics , Adult , Aged , Angiotensin Receptor Antagonists/pharmacology , Angiotensin-Converting Enzyme Inhibitors/pharmacology , Antiviral Agents/pharmacology , COVID-19/drug therapy , COVID-19/epidemiology , COVID-19 Nucleic Acid Testing , Drug Interactions , Female , Gene Expression Profiling , Genome, Viral , HLA Antigens/genetics , Host Microbial Interactions/drug effects , Host Microbial Interactions/genetics , Humans , Male , Middle Aged , Molecular Diagnostic Techniques , New York City/epidemiology , Nucleic Acid Amplification Techniques , Pandemics , RNA-Seq , SARS-CoV-2/classification , SARS-CoV-2/drug effects
16.
IEEE/ACM Trans Comput Biol Bioinform ; 18(4): 1299-1304, 2021.
Article in English | MEDLINE | ID: covidwho-1123494

ABSTRACT

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.


Subject(s)
COVID-19/drug therapy , COVID-19/virology , SARS-CoV-2/chemistry , SARS-CoV-2/drug effects , Software , Viral Proteins/chemistry , Viral Proteins/drug effects , Antiviral Agents/pharmacology , COVID-19/prevention & control , COVID-19 Vaccines/chemistry , COVID-19 Vaccines/genetics , Computational Biology , Databases, Protein/statistics & numerical data , Drug Design , Genome, Viral , Host Microbial Interactions/drug effects , Humans , Pandemics , Peptides/chemistry , Peptides/drug effects , Peptides/genetics , SARS-CoV-2/genetics , Viral Proteins/genetics
17.
PLoS Comput Biol ; 17(3): e1008752, 2021 03.
Article in English | MEDLINE | ID: covidwho-1110080

ABSTRACT

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.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/prevention & control , SARS-CoV-2 , Antiviral Agents/administration & dosage , Basic Reproduction Number/statistics & numerical data , COVID-19/transmission , COVID-19/virology , Computational Biology , Drug Repositioning , Drug Therapy, Combination , Host Microbial Interactions/drug effects , Host Microbial Interactions/immunology , Humans , Models, Biological , Pandemics/prevention & control , Primary Prevention/methods , Risk Factors , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity , SARS-CoV-2/physiology , Stochastic Processes , Time Factors , Treatment Outcome , Viral Load/drug effects , Virus Internalization/drug effects , Virus Replication/drug effects
18.
Am J Physiol Lung Cell Mol Physiol ; 320(2): L246-L253, 2021 02 01.
Article in English | MEDLINE | ID: covidwho-1088311

ABSTRACT

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.


Subject(s)
Bronchi/metabolism , COVID-19/etiology , Furin/metabolism , SARS-CoV-2 , Transforming Growth Factor beta1/metabolism , Transforming Growth Factor beta2/metabolism , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/metabolism , Bronchi/cytology , Bronchi/drug effects , Cell Differentiation , Cells, Cultured , Disease Susceptibility , Epithelial Cells/cytology , Epithelial Cells/drug effects , Epithelial Cells/metabolism , Furin/genetics , Gene Expression/drug effects , Host Microbial Interactions/drug effects , Host Microbial Interactions/genetics , Host Microbial Interactions/physiology , Humans , Models, Biological , Pandemics , RNA, Messenger/genetics , RNA, Messenger/metabolism , SARS-CoV-2/pathogenicity , SARS-CoV-2/physiology , Serine Endopeptidases/genetics , Serine Endopeptidases/metabolism , Transforming Growth Factor beta1/pharmacology , Transforming Growth Factor beta2/pharmacology , Virus Internalization
19.
PLoS Comput Biol ; 17(2): e1008686, 2021 02.
Article in English | MEDLINE | ID: covidwho-1067382

ABSTRACT

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.


Subject(s)
Algorithms , Antiviral Agents/pharmacology , COVID-19/drug therapy , Drug Repositioning/methods , Pandemics , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/virology , Clinical Trials as Topic , Comorbidity , Computational Biology , Computer Simulation , Drug Discovery , Drug Evaluation, Preclinical/methods , Drug Evaluation, Preclinical/statistics & numerical data , Drug Repositioning/statistics & numerical data , Host Microbial Interactions/drug effects , Host Microbial Interactions/physiology , Humans , Protein Interaction Maps/drug effects , SARS-CoV-2/drug effects
20.
Med Hypotheses ; 146: 110394, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-919589

ABSTRACT

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.


Subject(s)
COVID-19/drug therapy , Models, Biological , alpha 1-Antitrypsin/therapeutic use , Acute Lung Injury/drug therapy , Anti-Inflammatory Agents/therapeutic use , Antithrombins/therapeutic use , Antiviral Agents/therapeutic use , Apoptosis/drug effects , COVID-19/physiopathology , Extracellular Traps/drug effects , Host Microbial Interactions/drug effects , Host Microbial Interactions/physiology , Humans , Leukocyte Elastase/antagonists & inhibitors , Pandemics , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity , SARS-CoV-2/physiology , Serine Endopeptidases/drug effects , Serine Endopeptidases/physiology , Virus Internalization/drug effects , alpha 1-Antitrypsin/administration & dosage
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