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Diosmin for COVID-19

Diosmin has been reported as potentially beneficial for treatment of COVID-19. We have not reviewed these studies. See all other treatments.
Onyango, O., In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review, Advances in Pharmacological and Pharmaceutical Sciences, doi:10.1155/2023/4562974
The coronavirus disease 2019 (COVID-19) is a severe worldwide pandemic. Due to the emergence of various SARS-CoV-2 variants and the presence of only one Food and Drug Administration (FDA) approved anti-COVID-19 drug (remdesivir), the disease remains a mindboggling global public health problem. Developing anti-COVID-19 drug candidates that are effective against SARS-CoV-2 and its various variants is a pressing need that should be satisfied. This systematic review assesses the existing literature that used in silico models during the discovery procedure of anti-COVID-19 drugs. Cochrane Library, Science Direct, Google Scholar, and PubMed were used to conduct a literature search to find the relevant articles utilizing the search terms “In silico model,” “COVID-19,” “Anti-COVID-19 drug,” “Drug discovery,” “Computational drug designing,” and “Computer-aided drug design.” Studies published in English between 2019 and December 2022 were included in the systematic review. From the 1120 articles retrieved from the databases and reference lists, only 33 were included in the review after the removal of duplicates, screening, and eligibility assessment. Most of the articles are studies that use SARS-CoV-2 proteins as drug targets. Both ligand-based and structure-based methods were utilized to obtain lead anti-COVID-19 drug candidates. Sixteen articles also assessed absorption, distribution, metabolism, excretion, toxicity (ADMET), and drug-likeness properties. Confirmation of the inhibitory ability of the candidate leads by in vivo or in vitro assays was reported in only five articles. Virtual screening, molecular docking (MD), and molecular dynamics simulation (MDS) emerged as the most commonly utilized in silico models for anti-COVID-19 drug discovery.
Rafiq et al., A Comprehensive Update of Various Attempts by Medicinal Chemists to Combat COVID-19 through Natural Products, Molecules, doi:10.3390/molecules28124860
The ongoing COVID-19 pandemic has resulted in a global panic because of its continual evolution and recurring spikes. This serious malignancy is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the outbreak, millions of people have been affected from December 2019 till now, which has led to a great surge in finding treatments. Despite trying to handle the pandemic with the repurposing of some drugs, such as chloroquine, hydroxychloroquine, remdesivir, lopinavir, ivermectin, etc., against COVID-19, the SARS-CoV-2 virus continues its out-of-control spread. There is a dire need to identify a new regimen of natural products to combat the deadly viral disease. This article deals with the literature reports to date of natural products showing inhibitory activity towards SARS-CoV-2 through different approaches, such as in vivo, in vitro, and in silico studies. Natural compounds targeting the proteins of SARS-CoV-2—the main protease (Mpro), papain-like protease (PLpro), spike proteins, RNA-dependent RNA polymerase (RdRp), endoribonuclease, exoribonuclease, helicase, nucleocapsid, methyltransferase, adeno diphosphate (ADP) phosphatase, other nonstructural proteins, and envelope proteins—were extracted mainly from plants, and some were isolated from bacteria, algae, fungi, and a few marine organisms.
Oliver et al., 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
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.
Islam et al., Molecular-evaluated and explainable drug repurposing for COVID-19 using ensemble knowledge graph embedding, Scientific Reports, doi:10.1038/s41598-023-30095-z
AbstractThe search for an effective drug is still urgent for COVID-19 as no drug with proven clinical efficacy is available. Finding the new purpose of an approved or investigational drug, known as drug repurposing, has become increasingly popular in recent years. We propose here a new drug repurposing approach for COVID-19, based on knowledge graph (KG) embeddings. Our approach learns “ensemble embeddings” of entities and relations in a COVID-19 centric KG, in order to get a better latent representation of the graph elements. Ensemble KG-embeddings are subsequently used in a deep neural network trained for discovering potential drugs for COVID-19. Compared to related works, we retrieve more in-trial drugs among our top-ranked predictions, thus giving greater confidence in our prediction for out-of-trial drugs. For the first time to our knowledge, molecular docking is then used to evaluate the predictions obtained from drug repurposing using KG embedding. We show that Fosinopril is a potential ligand for the SARS-CoV-2 nsp13 target. We also provide explanations of our predictions thanks to rules extracted from the KG and instanciated by KG-derived explanatory paths. Molecular evaluation and explanatory paths bring reliability to our results and constitute new complementary and reusable methods for assessing KG-based drug repurposing.
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. Vaccines and treatments are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment, vaccine, 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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