Candesartan for COVID-19
c19early.org
COVID-19 Treatment Clinical Evidence
COVID-19 involves the interplay of 400+ viral and host proteins and factors, providing many therapeutic targets.
c19early analyzes 6,000+ studies for 210+ treatments—over 17 million hours of research.
Only three high-profit early treatments are approved in the US.
In reality, many treatments reduce risk,
with 25 low-cost treatments approved across 163 countries.
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Naso/
oropharyngeal treatment Effective Treatment directly to the primary source of initial infection. -
Healthy lifestyles Protective Exercise, sunlight, a healthy diet, and good sleep all reduce risk.
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Immune support Effective Vitamins A, C, D, and zinc show reduced risk, as with other viruses.
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Thermotherapy Effective Methods for increasing internal body temperature, enhancing immune system function.
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Systemic agents Effective Many systemic agents reduce risk, and may be required when infection progresses.
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High-profit systemic agents Conditional Effective, but with greater access and cost barriers.
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Monoclonal antibodies Limited Utility Effective but rarely used—high cost, variant dependence, IV/SC admin.
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Acetaminophen Harmful Increased risk of severe outcomes and mortality.
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Remdesivir Harmful Increased mortality with longer followup. Increased kidney and liver injury, cardiac disorders.
Candesartan may be beneficial for
COVID-19 according to the studies below.
COVID-19 involves the interplay of 400+ viral and host proteins and factors providing many therapeutic targets.
Scientists have proposed 11,000+ potential treatments.
c19early.org analyzes
210+ treatments.
We have not reviewed candesartan in detail.
, Targeting asparagine and cysteine in SARS-CoV-2 variants and human pro-inflammatory mediators to alleviate COVID-19 severity; a cross-section and in-silico study, Scientific Reports, doi:10.1038/s41598-025-19359-y
Abstract To date, COVID-19 continues to pose a global health challenge, with substantial morbidity, mortality, and long-term post-COVID-19 complications threatening public health resilience. During the early pandemic, the IL-6 inhibitor (tocilizumab) was the widely used approved immunotherapy for critically ill patients; however, a subset of ICU cases exhibited normal interleukin-6 (IL-6) levels and failed to respond. We hypothesized that interleukin-17 (IL-17), which acts synergistically with IL-6, contributes to cytokine storm progression and severe inflammation. Our study uniquely integrates a clinical cross-sectional analysis with advanced in-silico modelling, directly linking patient-derived biomarker, radiological, and statistical data to molecular-level mechanisms of COVID-19 severity. Serum IL-17 was significantly elevated in critical versus moderate COVID-19 cases, with a threshold of 187.9 ng/mL predicting poor outcomes by ROC analysis. Logistic regression identified age and monocytes as independent predictors of severity, supporting a combined biomarker approach for improving the prognosis and clinical outcomes. Radiological findings, including ground-glass opacities and consolidations, alongside hematological abnormalities, were more frequent in critical cases. Computational docking revealed key amino acid residues—particularly asparagine (Asn) and cysteine (Cys)—as structural determinants shared by SARS-CoV-2 spike protein and human inflammatory mediators (IL-17R, IL-6R, CD41/CD61, CD47/SIRP). Asparaginase (ASNase) targeted critical residues such as the invariant gate residue “Asn343” and Cys213 of spike protein, Asn240 of IL-17R, and Asn136 of IL-6R. Several phytochemicals, including phytic acid and amygdalin, as well as synthetic agents such as candesartan, remdesivir, and enalapril, were found to preferentially bind to cysteine (Cys) residues—and, to a lesser extent, asparagine (Asn) residues—within key binding interfaces, in addition to targeting B-cell epitopes. This conserved residue preference supports the rationale for a dual-action therapeutic strategy in which asparaginase (ASNase) is combined with selected plant-derived ligands to simultaneously disrupt viral entry mechanisms and attenuate the inflammatory signalling. This dual-perspective approach not only identified IL-17 and IL-6 as independent severity predictors but also revealed conserved Asn and Cys motifs as critical therapeutic targets, leading to novel strategies—such as ASNase, synthetic agents and phytochemical combinations—for simultaneously blocking viral entry and modulating hyperinflammatory pathways. These findings warrant rigorous experimental and clinical validation to facilitate translation into effective therapeutic interventions.
, Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries, Briefings in Bioinformatics, doi:10.1093/bib/bbab113
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.
, Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches, Frontiers in Immunology, doi:10.3389/fimmu.2023.1282859
IntroductionThe COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. MethodsExtensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.ResultsResults revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. DiscussionThe key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.