Computational approaches to define poncirin from Magnolia champaka leaves as a novel multi-target inhibitor of SARS-CoV-2

Abstract

Phytochemical-based drug discovery against the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been the focus of the current scenario. In this context, we aimed to perform the phytochemical profiling of Magnolia champaka, an evergreen tree from the Magnoliaceae family, in order to perform a virtual screening of its phytoconstituents against different biological targets of SARS-CoV-2. The phytochemicals identified from the ethanol extract of M. champaka leaves using liquid chromatography-mass spectroscopy (LC-MS) technique were screened against SARS-CoV-2 spike glycoprotein (PDB ID: 6M0J), main protease/Mpro (PDB ID: 6LU7), and papain-like protease/PLpro (PDB ID: 7CMD) through computational tools. The experimentation design included molecular docking simulation, molecular dynamics simulation, and binding free energy calculations. Through molecular docking simulation, we identified poncirin as a common potential inhibitor of all the above-mentioned target proteins. In addition, molecular dynamics simulations, binding free energy calculations, and PCA analysis also supported the outcomes of the virtual screening. By the virtue of all the in silico results obtained, poncirin could be taken for in vitro and in vivo studies in near future. Communicated by Ramaswamy H. Sarma