Garcinoxanthones from Garcinia mangostana L. against SARS-CoV-2 infection and cytokine storm pathway inhibition: A viroinformatics study

Abstract

Context: Mangosteen (Garcinia mangostana L.) is used in traditional medicine as an antibacterial, antioxidant, and anti-inflammatory. Aims: To determine the molecular mechanism and potential of garciniaxanthone derivate compounds from G. mangostana as SARS-CoV-2 antiviral and prevent cytokine storm through in silico approach. Methods: Ligand and protein samples were obtained from databases such as PubChem and Protein Databank, then drug-likeness analysis using Lipinski, Ghose, Veber, Egan, and Muege rules on SwissADME server, prediction of antiviral probability through PASSOnline server. Furthermore, molecular docking simulation with PyRx v1.0 software (Scripps Research, USA) with an academic license, identification of interactions and chemical bond positions of ligands on the target by PoseView server, 3D visualization of PyMOLv.2.5.2 software (Schrödinger, Inc., USA) with an academic license, molecular dynamics simulation for molecular stability prediction by CABS-flex v2.0 server, target prediction of antiviral candidate compounds by SwissTargetPrediction server, pathway analysis through STRING v11.5 database, and toxicity by ProTox-II server were used. Results: Garciniaxanthone C from G. mangostana was found to be a drug-like molecule with low toxicity. This can be a candidate for SARS-Cov-2 antiviral through inhibitor activity on two viral enzymes consisting of Mpro and replicase with a binding affinity value that is more negative than other garciniaxanthone derivates and is stable. Garciniaxanthone C is predicted to bind and inhibit pro-inflammatory proteins that trigger cytokine storms, such as NFKB1 and PTGS2. Conclusions: Garciniaxanthone derivative compounds from G. mangostana may be candidates for SARS-CoV-2 antiviral and preventing cytokine storm through garciniaxanthone C activity.