Tamoxifen for COVID-19
Tamoxifen has been reported as potentially beneficial for
treatment of COVID-19. We have not reviewed these studies.
See all other treatments.
Molecular docking as a tool for the discovery of novel insight about the role of acid sphingomyelinase inhibitors in SARS- CoV-2 infectivity, BMC Public Health, doi:10.1186/s12889-024-17747-z
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AbstractRecently, COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants, caused > 6 million deaths. Symptoms included respiratory strain and complications, leading to severe pneumonia. SARS-CoV-2 attaches to the ACE-2 receptor of the host cell membrane to enter. Targeting the SARS-CoV-2 entry may effectively inhibit infection. Acid sphingomyelinase (ASMase) is a lysosomal protein that catalyzes the conversion of sphingolipid (sphingomyelin) to ceramide. Ceramide molecules aggregate/assemble on the plasma membrane to form “platforms” that facilitate the viral intake into the cell. Impairing the ASMase activity will eventually disrupt viral entry into the cell. In this review, we identified the metabolism of sphingolipids, sphingolipids' role in cell signal transduction cascades, and viral infection mechanisms. Also, we outlined ASMase structure and underlying mechanisms inhibiting viral entry 40 with the aid of inhibitors of acid sphingomyelinase (FIASMAs). In silico molecular docking analyses of FIASMAs with inhibitors revealed that dilazep (S = − 12.58 kcal/mol), emetine (S = − 11.65 kcal/mol), pimozide (S = − 11.29 kcal/mol), carvedilol (S = − 11.28 kcal/mol), mebeverine (S = − 11.14 kcal/mol), cepharanthine (S = − 11.06 kcal/mol), hydroxyzin (S = − 10.96 kcal/mol), astemizole (S = − 10.81 kcal/mol), sertindole (S = − 10.55 kcal/mol), and bepridil (S = − 10.47 kcal/mol) have higher inhibition activity than the candidate drug amiodarone (S = − 10.43 kcal/mol), making them better options for inhibition.
In vitro screening of a FDA approved chemical library reveals potential inhibitors of SARS-CoV-2 replication, bioRxiv, doi:10.1101/2020.04.03.023846
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SummaryA novel coronavirus, named SARS-CoV-2, emerged in 2019 from Hubei region in China and rapidly spread worldwide. As no approved therapeutics exists to treat Covid-19, the disease associated to SARS-Cov-2, there is an urgent need to propose molecules that could quickly enter into clinics. Repurposing of approved drugs is a strategy that can bypass the time consuming stages of drug development. In this study, we screened the Prestwick Chemical Library® composed of 1,520 approved drugs in an infected cell-based assay. 90 compounds were identified. The robustness of the screen was assessed by the identification of drugs, such as Chloroquine derivatives and protease inhibitors, already in clinical trials. The hits were sorted according to their chemical composition and their known therapeutic effect, then EC50 and CC50 were determined for a subset of compounds. Several drugs, such as Azithromycine, Opipramol, Quinidine or Omeprazol present antiviral potency with 2<EC50<20µM. By providing new information on molecules inhibiting SARS-CoV-2 replication in vitro, this study could contribute to the short-term repurposing of drugs against Covid-19.
Broad anti-coronaviral activity of FDA approved drugs against SARS-CoV-2 in vitro and SARS-CoV in vivo, bioRxiv, doi:10.1101/2020.03.25.008482
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AbstractSARS-CoV-2 emerged in China at the end of 2019 and has rapidly become a pandemic with roughly 2.7 million recorded COVID-19 cases and greater than 189,000 recorded deaths by April 23rd, 2020 (www.WHO.org). There are no FDA approved antivirals or vaccines for any coronavirus, including SARS-CoV-2. Current treatments for COVID-19 are limited to supportive therapies and off-label use of FDA approved drugs. Rapid development and human testing of potential antivirals is greatly needed. A quick way to test compounds with potential antiviral activity is through drug repurposing. Numerous drugs are already approved for human use and subsequently there is a good understanding of their safety profiles and potential side effects, making them easier to fast-track to clinical studies in COVID-19 patients. Here, we present data on the antiviral activity of 20 FDA approved drugs against SARS-CoV-2 that also inhibit SARS-CoV and MERS-CoV. We found that 17 of these inhibit SARS-CoV-2 at a range of IC50 values at non-cytotoxic concentrations. We directly follow up with seven of these to demonstrate all are capable of inhibiting infectious SARS-CoV-2 production. Moreover, we have evaluated two of these, chloroquine and chlorpromazine, in vivo using a mouse-adapted SARS-CoV model and found both drugs protect mice from clinical disease.
Broad Anti-coronavirus Activity of Food and Drug Administration-Approved Drugs against SARS-CoV-2
In Vitro
and SARS-CoV
In Vivo, Journal of Virology, doi:10.1128/jvi.01218-20
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There are no FDA-approved antivirals for any coronavirus, including SARS-CoV-2. Numerous drugs are already approved for human use that may have antiviral activity and therefore could potentially be rapidly repurposed as antivirals. Here, we present data assessing the antiviral activity of 20 FDA-approved drugs against SARS-CoV-2 that also inhibit SARS-CoV and MERS-CoV in vitro . We found that 17 of these inhibit SARS-CoV-2, suggesting that they may have pan-anti-coronaviral activity. We directly followed up seven of these and found that they all inhibit infectious-SARS-CoV-2 production. Moreover, we evaluated chloroquine and chlorpromazine in vivo using mouse-adapted SARS-CoV. We found that neither drug inhibited viral replication in the lungs, but both protected against clinical disease.
Different drug approaches to COVID-19 treatment worldwide: an update of new drugs and drugs repositioning to fight against the novel coronavirus, Therapeutic Advances in Vaccines and Immunotherapy, doi:10.1177/25151355221144845
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According to the World Health Organization (WHO), in the second half of 2022, there are about 606 million confirmed cases of COVID-19 and almost 6,500,000 deaths around the world. A pandemic was declared by the WHO in March 2020 when the new coronavirus spread around the world. The short time between the first cases in Wuhan and the declaration of a pandemic initiated the search for ways to stop the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or to attempt to cure the disease COVID-19. More than ever, research groups are developing vaccines, drugs, and immunobiological compounds, and they are even trying to repurpose drugs in an increasing number of clinical trials. There are great expectations regarding the vaccine’s effectiveness for the prevention of COVID-19. However, producing sufficient doses of vaccines for the entire population and SARS-CoV-2 variants are challenges for pharmaceutical industries. On the contrary, efforts have been made to create different vaccines with different approaches so that they can be used by the entire population. Here, we summarize about 8162 clinical trials, showing a greater number of drug clinical trials in Europe and the United States and less clinical trials in low-income countries. Promising results about the use of new drugs and drug repositioning, monoclonal antibodies, convalescent plasma, and mesenchymal stem cells to control viral infection/replication or the hyper-inflammatory response to the new coronavirus bring hope to treat the disease.
Immune-Related Protein Interaction Network in Severe COVID-19 Patients toward the Identification of Key Proteins and Drug Repurposing, Biomolecules, doi:10.3390/biom12050690
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Coronavirus disease 2019 (COVID-19) is still an active global public health issue. Although vaccines and therapeutic options are available, some patients experience severe conditions and need critical care support. Hence, identifying key genes or proteins involved in immune-related severe COVID-19 is necessary to find or develop the targeted therapies. This study proposed a novel construction of an immune-related protein interaction network (IPIN) in severe cases with the use of a network diffusion technique on a human interactome network and transcriptomic data. Enrichment analysis revealed that the IPIN was mainly associated with antiviral, innate immune, apoptosis, cell division, and cell cycle regulation signaling pathways. Twenty-three proteins were identified as key proteins to find associated drugs. Finally, poly (I:C), mitomycin C, decitabine, gemcitabine, hydroxyurea, tamoxifen, and curcumin were the potential drugs interacting with the key proteins to heal severe COVID-19. In conclusion, IPIN can be a good representative network for the immune system that integrates the protein interaction network and transcriptomic data. Thus, the key proteins and target drugs in IPIN help to find a new treatment with the use of existing drugs to treat the disease apart from vaccination and conventional antiviral therapy.
Target-agnostic drug prediction integrated with medical record analysis uncovers differential associations of statins with increased survival in COVID-19 patients, PLOS Computational Biology, doi:10.1371/journal.pcbi.1011050 (Table 2)
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Drug repurposing requires distinguishing established drug class targets from novel molecule-specific mechanisms and rapidly derisking their therapeutic potential in a time-critical manner, particularly in a pandemic scenario. In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. However, it is unknown if different statins exhibit consistent function or may have varying therapeutic benefit. A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2. Top drug predictions included statins, which were then assessed using electronic medical records containing over 4,000 COVID-19 patients on statins to determine mortality risk in patients prescribed specific statins versus untreated matched controls. The same drugs were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins, including atorvastatin, were predicted to be active in > 50% of analyses. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent direct inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. Statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared drug target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and clinically evaluate non-obvious mechanisms and derisk and accelerate drug repurposing opportunities.
Improved And Optimized Drug Repurposing For The SARS-CoV-2 Pandemic, bioRxiv, doi:10.1101/2022.03.24.485618
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The active global SARS-CoV-2 pandemic caused more than 426 million cases and 5.8 million deaths worldwide. The development of completely new drugs for such a novel disease is a challenging, time intensive process. Despite researchers around the world working on this task, no effective treatments have been developed yet. This emphasizes the importance of drug repurposing, where treatments are found among existing drugs that are meant for different diseases. A common approach to this is based on \emph{knowledge graphs}, that condense relationships between entities like drugs, diseases and genes. Graph neural networks (GNNs) can then be used for the task at hand by predicting links in such knowledge graphs. Expanding on state-of-the-art GNN research, Doshi {\sl et al.} recently developed the \drcov \ model. We further extend their work using additional output interpretation strategies. The best aggregation strategy derives a top-100 ranking of 8,070 candidate drugs, 32 of which are currently being tested in COVID-19-related clinical trials. Moreover, we present an alternative application for the model, the generation of additional candidates based on a given pre-selection of drug candidates using collaborative filtering. In addition, we improved the implementation of the \drcov \ model by significantly shortening the inference and pre-processing time by exploiting data-parallelism. As drug repurposing is a task that requires high computation and memory resources, we further accelerate the post-processing phase using a new emerging hardware --- we propose a new approach to leverage the use of high-capacity Non-Volatile Memory for aggregate drug ranking.
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