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Several studies have suggested that "cytokine storms" are significant causes of the severity of COVID-19. Controlling and inhibiting the cytokine storm in COVID-19 could prevent the spread of COVID-19 and saves patient lives. Soybean (Glycine max L.) is known to have various biological activities. This study aims to examine bioactive compounds in SSE and the effect of SSE on the ARDS rats model. A total of 25 Sprague Dawley Lipopolysaccharide-induced rats were used. Determination of serum IL-1β, IL-12, and lung TNF-α levels was performed by ELISA method. NF-κB and IFN-γ expression were determined by the qRTPCR method. IL-6 expressions were analyzed by immunohistochemistry assay. The bleeding, inflammation, and alveolus collapse score were analyzed using the HE staining method. The results showed that SSE could decrease the level of IL-1β, IL-12, TNF-α, IL-6, NF-kB, and IFN-γ and improve the bleeding, inflammation, and alveolus score in the lung. SSE could decrease the proinflammatory cytokines and improve lung condition in ARDS rats model. [ABSTRACT FROM AUTHOR]

Coronavirus disease is caused by the pathogen severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) known as COVID-19. COVID-19 has caused the deaths of 6,541,936 people worldwide as of September 27th, 2022. SARS-CoV-2 severity is determined by a cytokine storm condition, in which the innate immune system creates an unregulated and excessive production of pro-inflammatory such IL-1, IL-6, NF Kappa B, and TNF alpha signaling molecules known as cytokines. The patient died due to respiratory organ failure and an acute complication because of the hyper-inflammation phenomenon. Green tea, soybean, and guava bioactive substances are well-known to act as anti-inflammation, and antioxidants become prospective COVID-19 illness candidates to overcome the cytokine storm. Our research aims to discover the bioactivity, bioavailability, and protein targets of green tea, soybean, and guava bioactive compounds as anti-inflammatory agents via the TNF inhibition pathway. The experiment uses in silico methods and harnesses the accessible datasets. Samples of 3D structure and SMILE identity of bioactive compounds were retrieved from the KNApSAck and Dr Duke databases. The QSAR analysis was done by WAY2DRUG web server, while the ADME prediction was performed using SWISSADME web server, following the Lipinsky rules of drugs. The target protein and protein-protein interaction were analyzed using STRING DB and Cytoscape software. Lastly, molecular docking was performed using Autodock 4.2 and visualization with BioVia Discovery Studio 2019. The identified study showed the potential of green tea, soybean, and guava's bioactive compounds have played an important role as anti-inflammation agents through TNF inhibitor pathway. [Display omitted] • Green tea and soybean's active compounds fulfill the requirement as drugs. • Guava's active compounds have slightly over requirements rotatable bonds. • Green tea, Soybean, and Guava have a high potential as anti-inflammation agent. [ABSTRACT FROM AUTHOR]