Interfering Reactive Cysteine Proteome in Covid-19 Disease

AbstractTherapeutic options for coronavirus remain limited. To address this unmet medical need, we screened 5,406 compounds, including United States Food and Drug Administration (FDA)- approved drugs and bioactives, for activity against a South Korean Middle East respiratory syndrome coronavirus (MERS-CoV) clinical isolate. Among 221 identified hits, 54 had therapeutic indexes (TI) greater than 6. Time-of-addition studies with selected drugs demonstrated eight and four FDA-approved drugs acted on the early and late stages of the viral life cycle, respectively. Confirmed hits included several cardiotonic agents (TI>100), atovaquone, an anti-malarial (TI>34), and ciclosonide, an inhalable corticosteroid (TI>6). Furthermore, utilizing the severe acute respiratory syndrome CoV-2 (SARS-CoV-2), combinations of remedesivir with selected dugs were evaluated, which identified ciclosonide and nelfinavir to be additive and synergistic drugs in vitro, respectively. Together, we screened FDA-approved drugs using patient-derived MERS-CoV, triaged hits to discriminate between early and late viral life cycle inhibitors, confirmed selected drugs using SARS-CoV-2, and demonstrated the added value of selected medications in combination with remedesivir. Our results identify potential therapeutic options for MERS-CoV infections, and provide a basis to treat coronavirus disease 2019 (COVID-19) and other coronavirus-related illnesses.

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Molecular Docking of Azithromycin, Ritonavir, Lopinavir, Oseltamivir, Ivermectin and Heparin Interacting with Coronavirus Disease 2019 Main and Severe Acute Respiratory Syndrome Coronavirus-2 3C-Like Proteases

Journal of Nanoscience and Nanotechnology ◽

10.1166/jnn.2021.19029 ◽

2021 ◽

Vol 21 (4) ◽

pp. 2075-2089

Author(s):

Tiago da Silva Arouche ◽

Anderson Yuri Martins ◽

Teodorico de Castro Ramalho ◽

Raul Nunes Carvalho Júnior ◽

Fabio Luiz Paranhos Costa ◽

...

Keyword(s):

Life Cycle ◽

Viral Life Cycle ◽

Stable Complex ◽

Viral Agent ◽

Main Protease ◽

Wide Range ◽

Approved Drugs ◽

Pharmacologically Active ◽

3Cl Protease

In the current pandemic situation raised due to COVID-19, drug reuse is emerging as the first line of treatment. The viral agent that causes this highly contagious disease and the acute respiratory syndrome coronavirus (SARS-CoV) share high nucleotide similarity. Therefore, it is structurally expected that many existing viral targets are similar to the first SARS-CoV, probably being inhibited by the same compounds. Here, we selected two viral proteins based on their vital role in the viral life cycle: Structure of the main protease SARS-CoV-2 and the structural base of the SARS-CoV-2 protease 3CL, both supporting the entry of the virus into the human host. The approved drugs used were azithromycin, ritonavir, lopinavir, oseltamivir, ivermectin and heparin, which are emerging as promising agents in the fight against COVID-19. Our hypothesis behind molecular coupling studies is to determine the binding affinities of these drugs and to identify the main amino acid residues that play a fundamental role in their mechanism of action. Additional studies on a wide range of FDA-approved drugs, including a few more protein targets, molecular dynamics studies, in vitro and biological in vivo evaluation are needed to identify combination therapy targeted at various stages of the viral life cycle. In our experiment in silico, based mainly on the molecular coupling approach, we investigated six different types of pharmacologically active drugs, aiming at their potential application alone or in combination with the reuse of drugs. The ligands showed stable conformations when analyzing the affinity energy in both proteases: ivermectin forming a stable complex with the two proteases with values −8.727 kcal/mol for Main Protease and −9.784 kcal/mol for protease 3CL, Heparin with values of −7.647 kcal/mol for the Main protease and −7.737 kcal/mol for the 3CL protease. Both conform to the catalytic site of the proteases. Our studies can provide an insight into the possible interactions between ligands and receptors, through better conformation. The ligands ivermectin, heparin and ritonavir showed stable conformations. Our in-silica docking data shows that the drugs we have identified can bind to the binding compartment of both proteases, this strongly supports our hypothesis that the development of a single antiviral agent targeting Main protease, or 3CL protease, or an agent used in combination with other potential therapies, it could provide an effective line of defense against diseases associated with coronaviruses.

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Potential Inhibitors Against Papain-like Protease of Novel Coronavirus (COVID-19) from FDA Approved Drugs

10.26434/chemrxiv.11860011.v1 ◽

2020 ◽

Cited By ~ 4

Author(s):

Rimanshee Arya ◽

Amit Das ◽

Vishal Prashar ◽

Mukesh Kumar

Keyword(s):

Life Cycle ◽

Active Site ◽

Homology Model ◽

Docking Studies ◽

Rational Selection ◽

Novel Coronavirus ◽

Approved Drugs ◽

Potential Inhibitors ◽

Fda Approved Drugs ◽

Selection Of

The cases of 2019 novel coronavirus (COVID-19) infection have been continuously increasing ever since its outbreak in China last December. Currently, there are no approved drugs to treat the infection. In this scenario, there is a need to utilize the existing repertoire of FDA approved drugs to treat the disease. The rational selection of these drugs could be made by testing their ability to inhibit any COVID-19 proteins essential for viral life-cycle. We chose one such crucial viral protein, the papain-like protease (PLpro), to screen the FDA approved drugs in silico. The homology model of the protease was built based on the SARS-coronavirus PLpro structure, and the drugs were docked in S3/S4 pockets of the active site of the enzyme. In our docking studies, fifteen FDA approved drugs, including chloroquine and formoterol, bind the target enzyme with significant affinity and good geometry, suggesting their potential to be utilized against the virus.

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TMPRSS2 Transcriptional Inhibition as a Therapeutic Strategy for COVID-19

10.20944/preprints202003.0360.v2 ◽

2020 ◽

Cited By ~ 1

Author(s):

Xinchen Wang ◽

Ryan Dhindsa ◽

Gundula Povysil ◽

Anthony Zoghbi ◽

Joshua Motelow ◽

...

Keyword(s):

Viral Entry ◽

Therapeutic Strategy ◽

Treatment Options ◽

Human Populations ◽

Expression Data ◽

Transcriptional Inhibition ◽

Transcriptional Modulators ◽

Approved Drugs ◽

Fda Approved Drugs ◽

Therapeutic Avenue

There is an urgent need to identify effective therapies for COVID-19. The SARS-CoV-2 host factor protease TMPRSS2 is required for viral entry and thus an attractive target for therapeutic intervention. In mouse, knockout of tmprss2 led to protection against SARS-CoV-1 with no deleterious phenotypes, and in human populations genetic loss of TMPRSS2 does not appear to be selected against. Here, we mined publicly available gene expression data to identify several compounds that down-regulate TMPRSS2. Recognizing the need for immediately available treatment options, we focused on FDA-approved drugs. We found 20 independent studies that implicate estrogenic and androgenic compounds as transcriptional modulators of TMPRSS2, suggesting these classes of drugs may be promising therapeutic candidates for clinical testing and observational studies of COVID-19. We also note that expression of TMPRSS2 is highly variable and skewed in humans, with a minority of individuals having extremely high expression. Combined with literature showing that inhibition of TMPRSS2 protease activity reduces SARS-CoV-2 viral entry in human cells, our results raise the hypothesis that modulation of TMPRSS2 expression is a promising therapeutic avenue for COVID-19.

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Intracellular Hepatitis C Virus Modeling Predicts Infection Dynamics and Viral Protein Mechanisms

Journal of Virology ◽

10.1128/jvi.02098-17 ◽

2018 ◽

Vol 92 (11) ◽

pp. e02098-17 ◽

Cited By ~ 4

Author(s):

Thomas R. Aunins ◽

Katherine A. Marsh ◽

Gitanjali Subramanya ◽

Susan L. Uprichard ◽

Alan S. Perelson ◽

...

Keyword(s):

Life Cycle ◽

Hepatitis C Virus ◽

Hepatitis C ◽

Kinetic Data ◽

Viral Proteins ◽

Viral Life Cycle ◽

Hcv Infection ◽

Viral Rna ◽

Model Parameters ◽

Virus Life Cycle

ABSTRACTHepatitis C virus (HCV) infection is a global health problem, with nearly 2 million new infections occurring every year and up to 85% of these infections becoming chronic infections that pose serious long-term health risks. To effectively reduce the prevalence of HCV infection and associated diseases, it is important to understand the intracellular dynamics of the viral life cycle. Here, we present a detailed mathematical model that represents the full hepatitis C virus life cycle. It is the first full HCV model to be fit to acute intracellular infection data and the first to explore the functions of distinct viral proteins, probing multiple hypotheses ofcis- andtrans-acting mechanisms to provide insights for drug targeting. Model parameters were derived from the literature, experiments, and fitting to experimental intracellular viral RNA, extracellular viral titer, and HCV core and NS3 protein kinetic data from viral inoculation to steady state. Our model predicts higher rates for protein translation and polyprotein cleavage than previous replicon models and demonstrates that the processes of translation and synthesis of viral RNA have the most influence on the levels of the species we tracked in experiments. Overall, our experimental data and the resulting mathematical infection model reveal information about the regulation of core protein during infection, produce specific insights into the roles of the viral core, NS5A, and NS5B proteins, and demonstrate the sensitivities of viral proteins and RNA to distinct reactions within the life cycle.IMPORTANCEWe have designed a model for the full life cycle of hepatitis C virus. Past efforts have largely focused on modeling hepatitis C virus replicon systems, in which transfected subgenomic HCV RNA maintains autonomous replication in the absence of virion production or spread. We started with the general structure of these previous replicon models and expanded it to create a model that incorporates the full virus life cycle as well as additional intracellular mechanistic detail. We compared several different hypotheses that have been proposed for different parts of the life cycle and applied the corresponding model variations to infection data to determine which hypotheses are most consistent with the empirical kinetic data. Because the infection data we have collected for this study are a more physiologically relevant representation of a viral life cycle than data obtained from a replicon system, our model can make more accurate predictions about clinical hepatitis C virus infections.

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The Deacetylase SIRT1 Regulates the Replication Properties of Human Papillomavirus 16 E1 and E2

Journal of Virology ◽

10.1128/jvi.00102-17 ◽

2017 ◽

Vol 91 (10) ◽

Cited By ~ 16

Author(s):

Dipon Das ◽

Nathan Smith ◽

Xu Wang ◽

Iain M. Morgan

Keyword(s):

Life Cycle ◽

Dna Replication ◽

Viral Replication ◽

Viral Proteins ◽

Viral Life Cycle ◽

Human Papillomaviruses ◽

Dependent Manner ◽

Viral Origin ◽

Replication Complex

ABSTRACT Human papillomaviruses (HPV) replicate their genomes in differentiating epithelium using the viral proteins E1 and E2 in association with host proteins. While the roles of E1 and E2 in this process are understood, the host factors involved and how they interact with and regulate E1-E2 are not. Our previous work identified the host replication and repair factor TopBP1 as an E2 partner protein essential for optimal E1-E2 replication and for the viral life cycle. The role of TopBP1 in host DNA replication is regulated by the class III deacetylase SIRT1; activation of the DNA damage response prevents SIRT1 deacetylation of TopBP1, resulting in a switch from DNA replication to repair functions for this protein and cell cycle arrest. Others have demonstrated an essential role for SIRT1 in regulation of the HPV31 life cycle; here, we report that SIRT1 can directly regulate HPV16 E1-E2-mediated DNA replication. SIRT1 is part of the E1-E2 DNA replication complex and is recruited to the viral origin of replication in an E1-E2-dependent manner. CRISPR/Cas9 was used to generate C33a clones with undetectable SIRT1 expression and lack of SIRT1 elevated E1-E2 DNA replication, in part due to increased acetylation and stabilization of the E2 protein in the absence of SIRT1. The results demonstrate that SIRT1 is a member of, and can regulate, the HPV16 replication complex. We discuss the potential role of this protein in the viral life cycle. IMPORTANCE HPV are causative agents in a number of human diseases, and currently only the symptoms of these diseases are treated. To identify novel therapeutic approaches for combating these diseases, the viral life cycle must be understood in more detail. This report demonstrates that a cellular enzyme, SIRT1, is part of the HPV16 DNA replication complex and is brought to the viral genome by the viral proteins E1 and E2. Using gene editing technology (CRISPR/Cas9), the SIRT1 gene was removed from cervical cancer cells. The consequence of this was that viral replication was elevated, probably due to a stabilization of the viral replication factor E2. The overall results demonstrate that an enzyme with known inhibitors, SIRT1, plays an important role in controlling how HPV16 makes copies of itself. Targeting this enzyme could be a new therapeutic approach for combating HPV spread and disease.

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Potential inhibitors against papain-like protease of novel coronavirus (SARS-CoV-2) from FDA approved drugs

10.26434/chemrxiv.11860011 ◽

2020 ◽

Cited By ~ 6

Author(s):

Rimanshee Arya ◽

Amit Das ◽

Vishal Prashar ◽

Mukesh Kumar

Keyword(s):

Life Cycle ◽

Active Site ◽

Homology Model ◽

Docking Studies ◽

Rational Selection ◽

Novel Coronavirus ◽

Approved Drugs ◽

Potential Inhibitors ◽

Fda Approved Drugs ◽

Selection Of

The cases of 2019 novel coronavirus (SARS-CoV-2) infection have been continuously increasing ever since its outbreak in China last December. Currently, there are no approved drugs to treat the infection. In this scenario, there is a need to utilize the existing repertoire of FDA approved drugs to treat the disease. The rational selection of these drugs could be made by testing their ability to inhibit any SARS-CoV-2 proteins essential for viral life-cycle. We chose one such crucial viral protein, the papain-like protease (PLpro), to screen the FDA approved drugs in silico. The homology model of the protease was built based on the SARS-coronavirus PLpro structure, and the drugs were docked in S3/S4 pockets of the active site of the enzyme. In our docking studies, sixteen FDA approved drugs, including chloroquine and formoterol, was found to bind the target enzyme with significant affinity and good geometry, suggesting their potential to be utilized against the virus.

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Identification of Drugs Targeting Multiple Viral and Human Proteins Using Computational Analysis for Repurposing Against COVID-19

10.26434/chemrxiv.12366938.v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Sugandh Kumar ◽

Pratima Kumari ◽

Geetanjali Agnihotri ◽

Preethy VijayKumar ◽

Shaheerah Khan ◽

...

Keyword(s):

Interaction Network ◽

Viral Proteins ◽

Inhibitory Effect ◽

Host Proteins ◽

Disease Manifestation ◽

Protein Protein Interaction ◽

Human Proteins ◽

Approved Drugs ◽

Viral Lifecycle ◽

Fda Approved Drugs

The SARS-CoV2 is a highly contagious pathogen that causes a respiratory disease named COVID-19. The COVID-19 was declared a pandemic by the WHO on 11th March 2020. It has affected about 5.38 million people globally (identified cases as on 24th May 2020), with an average lethality of ~3%. Unfortunately, there is no standard cure for the disease, although some drugs are under clinical trial. Thus, there is an urgent need of drugs for the treatment of COVID-19. The molecularly targeted therapies have proven their utility in various diseases such as HIV, SARS, and HCV. Therefore, a lot of efforts are being directed towards the identification of molecules that can be helpful in the management of COVID-19. In the current studies, we have used state of the art bioinformatics techniques to screen the FDA approved drugs against thirteen SARS-CoV2 proteins in order to identify drugs for quick repurposing. The strategy was to identify potential drugs that can target multiple viral proteins simultaneously. Our strategy originates from the fact that individual viral proteins play specific role in multiple aspects of viral lifecycle such as attachment, entry, replication, morphogenesis and egress and targeting them simultaneously will have better inhibitory effect. Additionally, we analyzed if the identified molecules can also affect the host proteins whose expression is differentially modulated during SARS-CoV2 infection. The differentially expressed genes (DEGs) were identified using analysis of NCBI-GEO data (GEO-ID: GSE-147507). A pathway and protein-protein interaction network analysis of the identified DEGs led to the identification of network hubs that may play important roles in SARS-CoV2 infection. Therefore, targeting such genes may also be a beneficial strategy to curb disease manifestation. We have identified 29 molecules that can bind to various SARS-CoV2 and human host proteins. We hope that this study will help researchers in the identification and repurposing of multipotent drugs, simultaneously targeting the several viral and host proteins, for the treatment of COVID-19.

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Identification of Drugs Targeting Multiple Viral and Human Proteins Using Computational Analysis for Repurposing Against COVID-19

10.26434/chemrxiv.12366938 ◽

2020 ◽

Author(s):

Sugandh Kumar ◽

Pratima Kumari ◽

Geetanjali Agnihotri ◽

Preethy VijayKumar ◽

Shaheerah Khan ◽

...

Keyword(s):

Interaction Network ◽

Viral Proteins ◽

Inhibitory Effect ◽

Host Proteins ◽

Disease Manifestation ◽

Protein Protein Interaction ◽

Human Proteins ◽

Approved Drugs ◽

Viral Lifecycle ◽

Fda Approved Drugs

The SARS-CoV2 is a highly contagious pathogen that causes a respiratory disease named COVID-19. The COVID-19 was declared a pandemic by the WHO on 11th March 2020. It has affected about 5.38 million people globally (identified cases as on 24th May 2020), with an average lethality of ~3%. Unfortunately, there is no standard cure for the disease, although some drugs are under clinical trial. Thus, there is an urgent need of drugs for the treatment of COVID-19. The molecularly targeted therapies have proven their utility in various diseases such as HIV, SARS, and HCV. Therefore, a lot of efforts are being directed towards the identification of molecules that can be helpful in the management of COVID-19. In the current studies, we have used state of the art bioinformatics techniques to screen the FDA approved drugs against thirteen SARS-CoV2 proteins in order to identify drugs for quick repurposing. The strategy was to identify potential drugs that can target multiple viral proteins simultaneously. Our strategy originates from the fact that individual viral proteins play specific role in multiple aspects of viral lifecycle such as attachment, entry, replication, morphogenesis and egress and targeting them simultaneously will have better inhibitory effect. Additionally, we analyzed if the identified molecules can also affect the host proteins whose expression is differentially modulated during SARS-CoV2 infection. The differentially expressed genes (DEGs) were identified using analysis of NCBI-GEO data (GEO-ID: GSE-147507). A pathway and protein-protein interaction network analysis of the identified DEGs led to the identification of network hubs that may play important roles in SARS-CoV2 infection. Therefore, targeting such genes may also be a beneficial strategy to curb disease manifestation. We have identified 29 molecules that can bind to various SARS-CoV2 and human host proteins. We hope that this study will help researchers in the identification and repurposing of multipotent drugs, simultaneously targeting the several viral and host proteins, for the treatment of COVID-19.

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Combined Deep Learning and Molecular Docking Simulations Approach Identifies Potentially Effective FDA Approved Drugs for Repurposing Against SARS-CoV-2

10.26434/chemrxiv.12227363.v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Muhammad Umer Anwar ◽

Farjad Adnan ◽

Asma Abro ◽

Muhammad Rayyan Khan ◽

Asad Ur Rehman ◽

...

Keyword(s):

Deep Learning ◽

Molecular Docking ◽

Active Sites ◽

Drug Repurposing ◽

Viral Proteins ◽

Penicillin G ◽

Computational Approaches ◽

Docking Simulations ◽

Approved Drugs ◽

Fda Approved Drugs

The ongoing pandemic of Coronavirus Disease 2019 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has posed a serious threat to global public health. Currently no approved drug or vaccine exists against SARS-CoV-2. Drug repurposing, represented as an effective drug discovery strategy from existing drugs, is a time efficient approach to find effective drugs against SARS-CoV-2 in this emergency situation. Both experimental and computational approaches are being employed in drug repurposing with computational approaches becoming increasingly popular and efficient. In this study, we present a robust experimental design combining deep learning with molecular docking experiments to identify most promising candidates from the list of FDA approved drugs that can be repurposed to treat COVID-19. We have employed a deep learning based Drug Target Interaction (DTI) model, called DeepDTA, with few improvements to predict drug-protein binding affinities, represented as KIBA scores, for 2,440 FDA approved and 8,168 investigational drugs against 24 SARS-CoV-2 viral proteins. FDA approved drugs with the highest KIBA scores were selected for molecular docking simulations. We ran docking simulations for 168 selected drugs against 285 total predicted and/or experimentally proven active sites of all 24 SARS-CoV-2 viral proteins. We used a recently published open source AutoDock based high throughput screening platform virtualflow to reduce the time required to run around 50,000 docking simulations. A list of 49 most promising FDA approved drugs with best consensus KIBA scores and AutoDock vina binding affinity values against selected SARS-CoV-2 viral proteins is generated. Most importantly, anidulafungin, velpatasvir, glecaprevir, rifabutin, procaine penicillin G, tadalafil, riboflavin 5’-monophosphate, flavin adenine dinucleotide, terlipressin, desmopressin, elbasvir, oxatomide, enasidenib, edoxaban and selinexor demonstrate highest predicted inhibitory potential against key SARS-CoV-2 viral proteins.

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