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Progesterone for COVID-19

Progesterone has been reported as potentially beneficial for treatment of COVID-19. We have not reviewed these studies. See all other treatments.
Al‐Kuraishy et al., New insights on the potential effect of progesterone in Covid‐19: Anti‐inflammatory and immunosuppressive effects, Immunity, Inflammation and Disease, doi:10.1002/iid3.1100
AbstractBackground: Coronavirus disease 2019 (COVID‐19) is a pandemic disease caused by severe acute respiratory syndrome CoV type 2 (SARS‐CoV‐2). COVID‐19 is higher in men than women and sex hormones have immune‐modulator effects during different viral infections, including SARS‐CoV‐2 infection. One of the essential sex hormones is progesterone (P4). Aims: This review aimed to reveal the association between P4 and Covid‐19. Results and Discussion: The possible role of P4 in COVID‐19 could be beneficial through the modulation of inflammatory signaling pathways, induction of the release of anti‐inflammatory cytokines, and inhibition release of pro‐inflammatory cytokines. P4 stimulates skew of naïve T cells from inflammatory Th1 toward anti‐inflammatory Th2 with activation release of anti‐inflammatory cytokines, and activation of regulatory T cells (Treg) with decreased interferon‐gamma production that increased during SARS‐CoV‐2 infection. In addition, P4 is regarded as a potent antagonist of mineralocorticoid receptor (MR), it could reduce MRs that were activated by stimulated aldosterone from high AngII during SARS‐CoV‐2. P4 active metabolite allopregnanolone is regarded as a neurosteroid that acts as a positive modulator of γ‐aminobutyric acid (GABAA) so it may reduce neuropsychiatric manifestations and dysautonomia in COVID‐19 patients. Conclusion: Taken together, the anti‐inflammatory and immunomodulatory properties of P4 may improve central and peripheral complications in COVID‐19.
Cesar-Silva et al., The Endolysosomal System: The Acid Test for SARS-CoV-2, International Journal of Molecular Sciences, doi:10.3390/ijms23094576
This review aims to describe and discuss the different functions of the endolysosomal system, from homeostasis to its vital role during viral infections. We will initially describe endolysosomal system’s main functions, presenting recent data on how its compartments are essential for host defense to explore later how SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) and other coronaviruses subvert these organelles for their benefit. It is clear that to succeed, pathogens’ evolution favored the establishment of ways to avoid, escape, or manipulate lysosomal function. The unavoidable coexistence with such an unfriendly milieu imposed on viruses the establishment of a vast array of strategies to make the most out of the invaded cell’s machinery to produce new viruses and maneuvers to escape the host’s defense system.
Sha et al., Current state-of-the-art and potential future therapeutic drugs against COVID-19, Frontiers in Cell and Developmental Biology, doi:10.3389/fcell.2023.1238027
The novel coronavirus disease (COVID-19) continues to endanger human health, and its therapeutic drugs are under intensive research and development. Identifying the efficacy and toxicity of drugs in animal models is helpful for further screening of effective medications, which is also a prerequisite for drugs to enter clinical trials. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) invades host cells mainly by the S protein on its surface. After the SARS-CoV-2 RNA genome is injected into the cells, M protein will help assemble and release new viruses. RdRp is crucial for virus replication, assembly, and release of new virus particles. This review analyzes and discusses 26 anti-SARS-CoV-2 drugs based on their mechanism of action, effectiveness and safety in different animal models. We propose five drugs to be the most promising to enter the next stage of clinical trial research, thus providing a reference for future drug development.
Wei et al., Total network controllability analysis discovers explainable drugs for Covid-19 treatment, Biology Direct, doi:10.1186/s13062-023-00410-9
Abstract Background The active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural controllability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against viral infections. Accordingly, we extended structural controllability to total structural controllability and introduced the concept of control hubs. Perturbing any control hub may render the cell uncontrollable by exogenous stimuli like viral infections, so control hubs are ideal drug targets. Results We developed an efficient algorithm to identify all control hubs, applying it to a largest homogeneous network of human protein interactions, including interactions between human and SARS-CoV-2 proteins. Our method recognized 65 druggable control hubs with enriched antiviral functions. Utilizing these hubs, we categorized potential drugs into four groups: antiviral and anti-inflammatory agents, drugs acting on the central nervous system, dietary supplements, and compounds enhancing immunity. An exemplification of our approach’s effectiveness, Fostamatinib, a drug initially developed for chronic immune thrombocytopenia, is now in clinical trials for treating Covid-19. Preclinical trial data demonstrated that Fostamatinib could reduce mortality rates, ICU stay length, and disease severity in Covid-19 patients. Conclusions Our findings confirm the efficacy of our novel strategy that leverages control hubs as drug targets. This approach provides insights into the molecular mechanisms of potential therapeutics for Covid-19, making it a valuable tool for interpretable drug discovery. Our new approach is general and applicable to repurposing drugs for other diseases.
Wei et al., Total controllability analysis discovers explainable drugs for Covid-19 treatment, arXiv, doi:10.48550/arXiv.2206.02970
Network medicine has been pursued for Covid-19 drug repurposing. One such approach adopts structural controllability, a theory for controlling a network (the cell). Motivated to protect the cell from viral infections, we extended this theory to total controllability and introduced a new concept of control hubs. Perturbation to any control hub renders the cell uncontrollable by exogenous stimuli, e.g., viral infections, so control hubs are ideal drug targets. We developed an efficient algorithm for finding all control hubs and applied it to the largest homogenous human protein-protein interaction network. Our new method outperforms several popular gene-selection methods, including that based on structural controllability. The final 65 druggable control hubs are enriched with functions of cell proliferation, regulation of apoptosis, and responses to cellular stress and nutrient levels, revealing critical pathways induced by SARS-CoV-2. These druggable control hubs led to drugs in 4 major categories: antiviral and anti-inflammatory agents, drugs on central nerve systems, and dietary supplements and hormones that boost immunity. Their functions also provided deep insights into the therapeutic mechanisms of the drugs for Covid-19 therapy, making the new approach an explainable drug repurposing method. A remarkable example is Fostamatinib that has been shown to lower mortality, shorten the length of ICU stay, and reduce disease severity of hospitalized Covid-19 patients. The drug targets 10 control hubs, 9 of which are kinases that play key roles in cell differentiation and programmed death. One such kinase is RIPK1 that directly interacts with viral protein nsp12, the RdRp of the virus. The study produced many control hubs that were not targets of existing drugs but were enriched with proteins on membranes and the NF-$κ$B pathway, so are excellent candidate targets for new drugs.
Schake et al., An interaction-based drug discovery screen explains known SARS-CoV-2 inhibitors and predicts new compound scaffolds, Scientific Reports, doi:10.1038/s41598-023-35671-x
AbstractThe recent outbreak of the COVID-19 pandemic caused by severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) has shown the necessity for fast and broad drug discovery methods to enable us to react quickly to novel and highly infectious diseases. A well-known SARS-CoV-2 target is the viral main 3-chymotrypsin-like cysteine protease (Mpro), known to control coronavirus replication, which is essential for the viral life cycle. Here, we applied an interaction-based drug repositioning algorithm on all protein-compound complexes available in the protein database (PDB) to identify Mpro inhibitors and potential novel compound scaffolds against SARS-CoV-2. The screen revealed a heterogeneous set of 692 potential Mpro inhibitors containing known ones such as Dasatinib, Amodiaquine, and Flavin mononucleotide, as well as so far untested chemical scaffolds. In a follow-up evaluation, we used publicly available data published almost two years after the screen to validate our results. In total, we are able to validate 17% of the top 100 predictions with publicly available data and can furthermore show that predicted compounds do cover scaffolds that are yet not associated with Mpro. Finally, we detected a potentially important binding pattern consisting of 3 hydrogen bonds with hydrogen donors of an oxyanion hole within the active side of Mpro. Overall, these results give hope that we will be better prepared for future pandemics and that drug development will become more efficient in the upcoming years.
Sperry et al., 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)
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.
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Treatments and other interventions are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
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