Abstract
The recent pandemic of novel corona virus infections (COVID19) has put the world on serious alert. This is caused by a recent form of a positive sense RNA virus (nCoV) of coronaviridae family which is known to cause respiratory tract infections in humans. Absence of any specific drugs, vaccines or treatment measures for this deadly virus warrants intense research to design new chemical entities in order to inhibit the viral replication in human cells. The main protease of nCov (nCov-MP) cleaves the long polyprotein chains to release functional proteins required for replication of the virus and thus is a potential drug target. The current study employs state of are computational methods to design new molecules by linking molecular fragments which specifically bind to different constituent sub-pockets of the nCov-MP binding site. A huge library of 191678 fragments was screened against the binding cavity of nCov-MP and high affinity fragments binding to adjacent sub-pockets were tailored to generate new molecules. These newly formed molecules were further subjected to molecular docking, ADMET property filters and MMGBSA binding free energy calculations to select 17 best molecules (named as MP-In1 to Mp-In17), which showed interactions with the key binding site residues as the reference ligand. Nine out of these 17 molecules with better MMGBSA binding free energy than the reference molecule, were subjected to molecular dynamics simulations, which assessed the stabilities of their binding with nCov-MP. Eight molecules were found to form stable complexes with nCov-MP. These molecules can be further evaluated as potential starting points for nCov drug discovery.