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Quinadoline B for COVID-19

Quinadoline B has been reported as potentially beneficial for treatment of COVID-19. We have not reviewed these studies. See all other treatments.
Alkafaas et al., A study on the effect of natural products against the transmission of B.1.1.529 Omicron, Virology Journal, doi:10.1186/s12985-023-02160-6
Abstract Background The recent outbreak of the Coronavirus pandemic resulted in a successful vaccination program launched by the World Health Organization. However, a large population is still unvaccinated, leading to the emergence of mutated strains like alpha, beta, delta, and B.1.1.529 (Omicron). Recent reports from the World Health Organization raised concerns about the Omicron variant, which emerged in South Africa during a surge in COVID-19 cases in November 2021. Vaccines are not proven completely effective or safe against Omicron, leading to clinical trials for combating infection by the mutated virus. The absence of suitable pharmaceuticals has led scientists and clinicians to search for alternative and supplementary therapies, including dietary patterns, to reduce the effect of mutated strains. Main body This review analyzed Coronavirus aetiology, epidemiology, and natural products for combating Omicron. Although the literature search did not include keywords related to in silico or computational research, in silico investigations were emphasized in this study. Molecular docking was implemented to compare the interaction between natural products and Chloroquine with the ACE2 receptor protein amino acid residues of Omicron. The global Omicron infection proceeding SARS-CoV-2 vaccination was also elucidated. The docking results suggest that DGCG may bind to the ACE2 receptor three times more effectively than standard chloroquine. Conclusion The emergence of the Omicron variant has highlighted the need for alternative therapies to reduce the impact of mutated strains. The current review suggests that natural products such as DGCG may be effective in binding to the ACE2 receptor and combating the Omicron variant, however, further research is required to validate the results of this study and explore the potential of natural products to mitigate COVID-19. Graphical abstract
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.
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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