Liquiritigenin for COVID-19
COVID-19 involves the interplay of 350+ viral and host proteins and factors providing many therapeutic targets.
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, Elucidation of anti-SARS-CoV-2 and anti-inflammatory bioactives in Qingyan Dropping Pills via integrated in silico screening and bioactivity validation, Frontiers in Medicine, doi:10.3389/fmed.2025.1684713
Background The global outbreak of coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has raised significant public health concerns. Qingyan Dropping Pills (QDP), as a recommended drug, is issued by the National Health Commission of the People’s Republic of China for the treatment of COVID-19. However, its bioactive compounds and their mechanisms of action remain largely unidentified. In this study, the integration of computational and experimental approaches was performed to identify the bioactive compounds in QDP and elucidate its mechanisms against COVID-19. Methods Utilizing UPLC-Q/TOF-MS, the chemical compounds of QDP were delineated, followed by network pharmacology analysis and molecular docking targeting SARS-CoV-2 spike protein (S pro ), main protease (M pro ), and papain-like protease (PL pro ). To validate the inhibitory activity of these compounds, fluorescence resonance energy transfer (FRET) and surface plasmon resonance (SPR) assays were employed. The antivival efficacy was tested in Vero E6 cells infected with SARS-CoV-2 Omicron BA.5 variant. Moreover, anti-inflammatory potential was evaluated via the measurement of inflammatory markers, including nitric oxide (NO), interleukin-6 (IL-6), interleukin-1 beta (IL-1 β ), and tumor necrosis factor-alpha (TNF- α ). Results Among the 48 identified compounds, 33 demonstrated potential antiviral activity against COVID-19. Notably, Hamamelitannin (HAM), corilagin (COR), and rhoifolin (RHO) effectively interacted with S pro , M pro and PL pro in silico . In SPR assays, the equilibrium dissociation constant ( K D ) for COR and RHO ranged from 4.515 × 10 −8 M to 7.718 × 10 −6 M, while HAM showed strong binding affinity to S pro ( K D = 9.33 × 10 −8 M) but weaker affinity for M pro and PL pro . In FRET assays, COR and RHO inhibited..
, Deep learning-based network pharmacology for exploring the mechanism of licorice for the treatment of COVID-19, Scientific Reports, doi:10.1038/s41598-023-31380-7
AbstractLicorice, a traditional Chinese medicine, has been widely used for the treatment of COVID-19, but all active compounds and corresponding targets are still not clear. Therefore, this study proposed a deep learning-based network pharmacology approach to identify more potential active compounds and targets of licorice. 4 compounds (quercetin, naringenin, liquiritigenin, and licoisoflavanone), 2 targets (SYK and JAK2) and the relevant pathways (P53, cAMP, and NF-kB) were predicted, which were confirmed by previous studies to be associated with SARS-CoV-2-infection. In addition, 2 new active compounds (glabrone and vestitol) and 2 new targets (PTEN and MAP3K8) were further validated by molecular docking and molecular dynamics simulations (simultaneous molecular dynamics), as well as the results showed that these active compounds bound well to COVID-19 related targets, including the main protease (Mpro), the spike protein (S-protein) and the angiotensin-converting enzyme 2 (ACE2). Overall, in this study, glabrone and vestitol from licorice were found to inhibit viral replication by inhibiting the activation of Mpro, S-protein and ACE2; related compounds in licorice may reduce the inflammatory response and inhibit apoptosis by acting on PTEN and MAP3K8. Therefore, licorice has been proposed as an effective candidate for the treatment of COVID-19 through PTEN, MAP3K8, Mpro, S-protein and ACE2.