ABSTRACT
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.