In this study for carrying out all the calculations and generating the figure the Prescience in silico Multi Target Multi Ligand Enhanced Sampling Screening (PRinMTML-ESS) has been used. In PRinMTML-ESS the process flow is in-build and fully automated, so no manual intervention is required from the user-side. The process flow here consists of molecular docking for docking the ligands in by automated grid generation at the target binding site. To explore the stability of the target-ligand complex all-atom molecular dynamic simulation is carried out in the next step and enhanced free energy sampling at the last stage for final analysis of the binding property of the ligand with the target (protein/enzyme/DNA-RNA). Efficient scoring algorithms are used after Docking and MD simulation for screening at each stages. All molecular docking calculation and MD simulations are performed using Autodock 4 and GROMACS-5.1.4 simulation package. The enhanced sampling using metadynamics (metaD) and its variant well-tempered metadynamics (wt-metaD) using , is widely used in simple and complex molecules due to its advantage over free energy perturbation and thermodynamic integration methods which are computationally more expensive for larger complex system like protein-ligand, protein-protein binding. A time-dependent bias is included to the system in a metadynamic simulation along with some deposited bias like a suitably chosen reaction coordinate(s) which will eventually push the complex away from the minimum energy state, so that the system doesn't get trapped at a local minima for sufficiently long time. Since this method is independent on the choice of reaction coordinate and not very sensitive to the precise choice of biasing parameters (except in the case where the parameters are chosen to be too high or low), any rudimentary reaction coordinate can bias the system helping it to escape the local minima within a small time and generate a qualitative free energy surface (FES). Metadynamics simulation uses a historydependent bias which inhibits the system from repeated revisiting previously visited regions of the phase space. Another, widely used scoring method over molecular dynamic simulation is the molecular mechanics Poisson-Boltzmann surface area (MMPBSA) which uses approximations to calculate enthalpic and entropic contributions using implicit continuum solvent hence less accurate in comparison to enhanced free energy sampling method used in our study. Additionally, as an alternative to MMPBSA we have performed all-atom simulation in explicit solvent medium including dynamics of solvent, solute and ions. Considering the effectiveness and computational viability of enhanced free energy sampling method, it has been used as the final scoring method for calculating free energy barrier for dissociation in PRinMTML-ESS platform. Inhouse codes have been used for generating the analysis in each section of computational methods used. A scheme of the methodologies and analysis used in PRinMTML-ESS platform are shown in Scheme 2. The structure of ligands used in this study has been downloaded from PubChem (). The crystal structure of the viral proteins of SAR-COV2 PLpro (PDB ID: 6wuu), 3CLpro (PDB ID: 6lu7), RNA-dependent RNA polymerase (PDB ID: 7bv1) and the Hexokinase enzyme (PDB ID: 1QHA) are obtained from RCSB Protein Data Bank(). All the protein and enzyme structures were cleaned (removing ligands, ions, water molecules) and missing loop was modelled using our PRinBio platform. A ligand conformational search is carried out generating an automated grid box of the dimension 60*60*60 Å by taking the binding site centroid as a grid center with a spacing of 0.375 Å. The docking was conducted the Lamarckian genetic algorithm (LGA), and a total of 100 GA-LA hybrid runs for performing the conformational search. In the MD simulation the proteins and enzyme were modelled using the CHARMM27 force field 28 parameters. For generating the CHARMM27 force field for all the ligands, SwissParam was used and the force field generation is automated in PRinMTML-ESS platform. The target-ligand systems were solvated in water and equilibrated using MD simulations at room temperature. The systems were first equilibrated using an NVT ensemble at 300 K for 1 ns and extended to the NPT ensemble at 300 K and 1 atm for another 2 ns. The temperature and pressure during the simulations were maintained using a velocity rescaling thermostat and Parrinello-Rahman barostat, respectively. A time step of 1 fs was used to integrate the equation of motion, and a nonbonded cutoff of 10Å was used to perform the MD simulations. We have used a bias V(s,t) in the form of Gaussians with every 500 steps (1 ps) deposition pace with a Gaussian hill-height of 2.0 kJ/mol, width of σ (0.1 nm), bias factor of 15, and temperature (T) of 300 K. For smooth convergence of the system in a wt-metaD the amplitude of the bias is tuned accordingly. Here a tempering factor ΔT (Equation ) is used to adjust the height of the hills, and henceforth a smooth convergence of the free energy landscape is attained.