Target prediction, computational identification, and network-based pharmacology of most potential phytoconstituent in medicinal leaves of Justicia adhatoda against SARS-CoV-2

The current global epidemic of the novel coronavirus (SARS-CoV-2) has been labeled a global public health emergency since it is causing substantial morbidity and mortality on daily basis. We need to identify an effective medication against SARS-CoV-2 because of its fast dissemination and re-emergence. This research is being carried out as part of a larger strategy to identify the most promising therapeutic targets using protein-protein interactions analysis. Mpro has been identified as one of the most important therapeutic targets. In this study, we did in-silico investigations to identify the target and further molecular docking, ADME, and toxicity prediction were done to assess the potential phyto-active antiviral compounds from Justicia adhatoda as powerful inhibitors of the Mpro of SARSCOV-2. We also investigated the capacity of these molecules to create stable interactions with the Mpro using 100 ns molecular dynamics simulation. The highest scoring compounds (taraxerol, friedelanol, anisotine, and adhatodine) were also found to exhibit excellent solubility and pharmacodynamic characteristics. We employed MMPBSA simulations to assess the stability of docked molecules in the Mpro binding site, revealing that the above compounds form the most stable complex with the Mpro. Network-based Pharmacology suggested that the selected compounds have various modes of action against SARS-CoV-2 that include immunoreaction enrichment, inflammatory reaction suppression, and more. These findings point to a promising class of drugs that should be investigated further in biochemical and cell-based studies to see their effectiveness against nCOVID-19.