Pioglitazone for COVID-19
Pioglitazone has been reported as potentially beneficial for
treatment of COVID-19. We have not reviewed these studies.
See all other treatments.
Synergistic Antiviral Activity of Pamapimod and Pioglitazone against SARS-CoV-2 and Its Variants of Concern, International Journal of Molecular Sciences, doi:10.3390/ijms23126830
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The SARS-CoV-2 pandemic remains a major public health threat, especially due to newly emerging SARS-CoV-2 Variants of Concern (VoCs), which are more efficiently transmitted, more virulent, and more able to escape naturally acquired and vaccine-induced immunity. Recently, the protease inhibitor Paxlovid® and the polymerase inhibitor molnupiravir, both targeting mutant-prone viral components, were approved for high-risk COVID-19 patients. Nevertheless, effective therapeutics to treat COVID-19 are urgently needed, especially small molecules acting independently of VoCs and targeting genetically stable cellular pathways which are crucial for viral replication. Pamapimod is a selective inhibitor of p38 Mitogen-Activated Protein Kinase alpha (p38 MAPKα) that has been extensively clinically evaluated for the treatment of rheumatoid arthritis. Signaling via p38 has recently been described as a key pathway for the replication of SARS-CoV-2. Here, we reveal that the combination of pamapimod with pioglitazone, an anti-inflammatory and approved drug for the treatment of type 2 diabetes, possesses potent and synergistic activity to inhibit SARS-CoV-2 replication in vitro. Both drugs showed similar antiviral potency across several cultured cell types and similar antiviral activity against SARS-CoV-2 Wuhan type, and the VoCs Alpha, Beta, Gamma, Delta, and Omicron. These data support the combination of pamapimod and pioglitazone as a potential therapy to reduce duration and severity of disease in COVID-19 patients, an assumption currently evaluated in an ongoing phase II clinical study.
Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries, Briefings in Bioinformatics, doi:10.1093/bib/bbab113
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AbstractTo attain promising pharmacotherapies, researchers have applied drug repurposing (DR) techniques to discover the candidate medicines to combat the coronavirus disease 2019 (COVID-19) outbreak. Although many DR approaches have been introduced for treating different diseases, only structure-based DR (SBDR) methods can be employed as the first therapeutic option against the COVID-19 pandemic because they rely on the rudimentary information about the diseases such as the sequence of the severe acute respiratory syndrome coronavirus 2 genome. Hence, to try out new treatments for the disease, the first attempts have been made based on the SBDR methods which seem to be among the proper choices for discovering the potential medications against the emerging and re-emerging infectious diseases. Given the importance of SBDR approaches, in the present review, well-known SBDR methods are summarized, and their merits are investigated. Then, the databases and software applications, utilized for repurposing the drugs against COVID-19, are introduced. Besides, the identified drugs are categorized based on their targets. Finally, a comparison is made between the SBDR approaches and other DR methods, and some possible future directions are proposed.
Novel Method for Detection of Genes With Altered Expression Caused by Coronavirus Infection and Screening of Candidate Drugs for SARS-CoV-2, MDPI AG, doi:10.20944/preprints202004.0431.v1
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To better understand the genes with altered expression caused by infection with the novel coronavirus strain SARS-CoV-2 causing COVID-19 infectious disease, a tensor decomposition (TD)-based unsupervised feature extraction (FE) approach was applied to a gene expression profile dataset of the mouse liver and spleen with experimental infection of mouse hepatitis virus, which is regarded as a suitable model of human coronavirus infection. TD-based unsupervised FE selected 134 altered genes, which were enriched in protein-protein interactions with orf1ab, polyprotein, and 3C-like protease that are well known to play critical roles in coronavirus infection, suggesting that these 134 genes can represent the coronavirus infectious process. We then selected compounds targeting the expression of the 134 selected genes based on a public domain database. The identified drug compounds were mainly related to known antiviral drugs, several of which were also included in those previously screened with an in silico method to identify candidate drugs for treating COVID-19.
A New Advanced In Silico Drug Discovery Method for Novel Coronavirus (SARS-CoV-2) with Tensor Decomposition-Based Unsupervised Feature Extraction, MDPI AG, doi:10.20944/preprints202004.0524.v1
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Background: COVID-19 is a critical pandemic that has affected human communities worldwide. Although it is urgent to rapidly develop effective drugs, large number of candidate drug compounds may be useful for treating COVID-19, and evaluation of these drugs is time-consuming and costly. Thus, screening to identify potentially effective drugs prior to experimental validation is necessary. Method: In this study, we applied the recently proposed method tensor decomposition (TD)-based unsupervised feature extraction (FE) to gene expression profiles of multiple lung cancer cell lines infected with severe acute respiratory syndrome coronavirus 2. We identified drug candidate compounds that significantly altered the expression of the 163 genes selected by TD-based unsupervised FE. Results: Numerous drugs were successfully screened, including many known antiviral drug compounds. Conclusions: The drugs screened using our strategy may be effective candidates for treating patients with COVID-19.
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.
Multi-omics data integration and network-based analysis drives a multiplex drug repurposing approach to a shortlist of candidate drugs against COVID-19, Briefings in Bioinformatics, doi:10.1093/bib/bbab114
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Abstract The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is undeniably the most severe global health emergency since the 1918 Influenza outbreak. Depending on its evolutionary trajectory, the virus is expected to establish itself as an endemic infectious respiratory disease exhibiting seasonal flare-ups. Therefore, despite the unprecedented rally to reach a vaccine that can offer widespread immunization, it is equally important to reach effective prevention and treatment regimens for coronavirus disease 2019 (COVID-19). Contributing to this effort, we have curated and analyzed multi-source and multi-omics publicly available data from patients, cell lines and databases in order to fuel a multiplex computational drug repurposing approach. We devised a network-based integration of multi-omic data to prioritize the most important genes related to COVID-19 and subsequently re-rank the identified candidate drugs. Our approach resulted in a highly informed integrated drug shortlist by combining structural diversity filtering along with experts’ curation and drug–target mapping on the depicted molecular pathways. In addition to the recently proposed drugs that are already generating promising results such as dexamethasone and remdesivir, our list includes inhibitors of Src tyrosine kinase (bosutinib, dasatinib, cytarabine and saracatinib), which appear to be involved in multiple COVID-19 pathophysiological mechanisms. In addition, we highlight specific immunomodulators and anti-inflammatory drugs like dactolisib and methotrexate and inhibitors of histone deacetylase like hydroquinone and vorinostat with potential beneficial effects in their mechanisms of action. Overall, this multiplex drug repurposing approach, developed and utilized herein specifically for SARS-CoV-2, can offer a rapid mapping and drug prioritization against any pathogen-related disease.
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