Virtual screening of COVID-19 drug from three Indian traditional medicinal plants through in silico approach

ABSTRACT

Novel Corona Virus (2019 nCoV/COVID-19) emerged from Wuhan city of Hubei Province China in November 2019. Now it causes pandemic disease COVID-19 across the globe in 2020. There is no proper medication and vaccine treatment option available for novel corona virus. There is a global urge set to prepare effective drug and vaccines from various possible routes against SARS-CoV-2. In the present study, four ligand groups (I - IV) were made comprising of one commercial anti-viral drug group (14 Nos) and three ligands group (84 Nos) constituted from phytocompounds of three anti-viral Indian Traditional Medicinal plants (ITMP) such as Azadirachta indica, Phyllanthus niruri andrographis paniculata to search effective drug candidate for treating novel coronavirus. Four levels of in silico virtual screening procedures (molecular docking, Lipinski rule, ADME, DFT analysis) were employed to sort out and choose potential drug candidate for COVID-19. Virtual screening of 98 ligands from four ligands group was done against six corona viral protein targets (SARS-CoV-1 and 2) through in silico approach. Preliminary molecular docking analysis revealed that twenty high scored ligands against viral target proteins were subject to Lipinski rule of drug likeliness screening. Based on Lipinski rule and some consideration of best docking score, eight ligands were chosen out of twenty ligands. Eight ligands chosen from Lipinski rule were subjected to final in silico virtual screening steps such as ADME and DFT analysis. Finally in silico virtual screening analysis showed four best ligands Baloxavir marboxil (CID124081896), Limocinin (CID 14845550), Formononetin 7 O Glucuronide (CID 71316927) and Bisandrographolide A (CID12000062). One from each ligands group was considered as best drug candidate for SARS CoV-2.