The average centre of mass (COM) distance plot shows that the combinations NSp16-2-DG(6wkq-2-DG) and RdRp-2-DG(7bv1-2-DG) have value 0.47 nm and 0.16 nm respectively, hence lies within the binding site cavity at the equilibrated structure after MD simulation. (Table ) However, in both the combination 3CL pro -2-DG(6lu7-2-DG) and PL pro -2-DG(6wuu-2-DG) the average COM distance are 1.27 nm and 1.08 nm respectively, hence here the ligand 2-DG have escaped the binding sites because of less interaction strength with the binding site residues of protein. The final equilibrated structure of the four combinations and visualization of the trajectory is consistent with the COM distance results. The equilibrated structure of NSp16-2-DG(6wkq-2-DG) have three hydrogen bonding interaction between 2-DG and the binding residues Asp-6897, Asp-6928 and Gly-6871. (Figure ). The equilibrated structure of RdRp-2-DG(7bv1-2-DG) has two hydrogen bonds with Ser-682. Our platform generates a combination score based on the average RMSD, internal energy and hydrogen bonding data obtained from analysis of MD simulation. Based on this score the selection of combinations for running the enhanced sampling free energy simulation is done. Among the four combination we have selected NSp16-2-DG(6wkq-2-DG) and RdRp-2-DG(7bv1-2-DG) combination based on their combination score 0.51 and 0.55 respectively, since only in these two combinations the ligand is still in the binding cavity after MD simulation. The sampling around the binding sites in instance of an MD simulation is not sufficient to predict the stability of the ligand in the binding cavity of protein, as conformations might get stuck in local minima. Therefore, meta-dynamics an enhanced sampling method of simulation for quantitatively predicting ligand binding energy and analysis of changes in the conformation of ligands is important to ascertain the most stable (bound) protein-ligand complex and predicting the inhibition property of the ligand. The equilibrium structures obtained from MD simulations were used as the starting configurations in the enhanced sampling free energy simulations (FES). The average free energy of dissociation obtained from 5 independent dissociation simulations for the combination NSp16-2-DG(6wkq-2-DG) and RdRp-2-DG(7bv1-2-DG) are 29.1 kJ/mol and 26.4 kJ/mol (Table ). For clarity and understanding of the free energy surfaces the individual free energy surfaces of all the independent runs and the average surface is shown in Figure . The free energy surfaces predict that the surfaces have multiple local minima and one global minimum for the ligand bound at the binding cavity. This structural characteristic represents multiple interactions between the ligands and residues of the binding site. The free energy of dissociation of the ligand 2-DG is of same order for both the viral protein NSp16(6wkq) and RdRp(7bv1), however the combination NSp16-2-DG(6wkq-2-DG) has the maximum ligand dissociation free energy. However previous studies show that antiviral drugs like Carfilzomib, Eravacycline, Valrubicin, Lopinavir, Elbasvir and Ritonavir interacts with SARS-COV-2 viral proteins 3CL pro , PL pro , RdRp and spike protein where total binding free energy ranges from -79.4 kJ/mol to -168.1 kJ/mol with the van der Waal On the other hand, several studies have shown glucose plays a major role in proliferation of SARS-CoV-2. This is one of the reasons why obese and diabetic patients with uncontrolled blood glucose level are more prone to develop a severe form of COVID-19. Due to the structural similarity between 2-DG and glucose (Scheme 1), it is expected that 2-DG would act as the competitive inhibitor of glucose metabolism and would strongly effect the metabolic processes like glycolysis and glycosylation which are dependent on glucose. When SARS-CoV-2 attacks our cells, they co-opt both of these metabolic processes to increase its replication and transcription. SARS-CoV-2 induces an anabolic state in their host cell which causes these infected cells to upregulate their production of energy using glycolysis as compared with their healthy neighbours. 2-DG differs from the glucose by removal of an oxygen atom from the 2-position (Scheme 1). In the glycolysis 2-DG is absorbed by the cell and undergoes phosphorylation at the 6 position to generate 2-DG-6P, in the next step unlike glucose-6-phosphate, 2-DG-6P cannot undergo isomerisation by glucose-6-phosphate isomerase hence the glycolytic flux is reduced (Scheme 2). Therefore, in presence of 2-DG, the rate limiting reaction of glycolysis is ATPdependent phosphorylation of glucose to form glucose-6-phosphate (G-6-P) and is catalysed by tissue-specific isoenzymes known as hexokinases. A recent study showed that SARS-COV-2 infection induces higher amount of glucose influx and glycolysis in the infected cells, resulting in selective high accumulation of the fluorescent glucose/2-DG analogue in the viral infected cells. They further observed that mannose inhibit the entry of 2-DG analogue at a very low concentration hence predicted that 2-DG entry in virus-infected cells might be manipulating specific mannose transporter or high-affinity glucose transporter, GLUT3, which was found to be increased on SARS-CoV-2 infection. In our study we have tried to explore the competitive inhibition property of 2-DG on the first step of phosphorylation with the aid of hexokinase enzyme after entering the viral infected cell. The 2-DG and glucose cyclic conformers were docked at the binding site of hexokinase (Thr-210, Thr-232, Ser-155, Lys-173).The binding energy was found to be -7.72 kcal/mol and -7.33 kcal/mol for glucose and 2-DG respectively. The entropic contribution associated with the solvent effect and conformational changes in the docked ligand is not accounted in the docking. The best docked pose and MD simulation is carried out in the next step. The non-bonded total interaction energy in the equilibrated structure were found to be slightly lower in glucose, -330.2 kJ/mol than 2-DG, -257.2 kJ/mol. The Coulomb energy and Van der Walls energy was also found to follow the same trend (Table ). RMSD was computed for the target binding pocket residues is the initial MD configuration and the MD equilibrated structure for both the 2-DG-hexokinase and glucose-hexokinase structure (Table ). The Centre of mass distance 0.50nm and 0.38 nm for glucose and 2-DG indicated that the ligands are stable in the binding cavity. Number of hydrogen bonding interaction in the equilibrated structure in glucose and 2-DG are ten and seven respectively, the interacting residues are indicated in Table and Figure . To increase the sampling around the binding site of the protein and calculate the more accurate binding energy of the ligand considering the changes in conformation of the ligand the equilibrium structure obtained from MD simulations was used as the starting configuration in the enhanced wt-metaD simulation. The average free energy barrier of dissociation obtained from enhanced wt-metaD simulations was found to be 66.3 kJ/mol and 52.4 kJ/mol for glucose and 2-DG (Table ). Hence, it can be predicted that since the free energy barrier is comparable and of same order in both glucose and 2-DG, they have the similar binding affinity to hexokinase enzyme. Therefore, the phosphorylation step of conversion of glucose to glucose-6-phosphate is inhibited in presence of 2-DG at a certain concentration. Thus, competitive inhibition is caused by 2-DG, which structurally similar to glucose and can combine at the same binding site of hexokinase. For clearly understanding the free energy surface the average and the individual surfaces are plotted in PRinMTML-ESS platform as shown in Figure . The free energy surfaces show jagged and uneven surfaces arising due to the multiple interaction of the ligand at the binding site. The MD simulation was extended to 50 ns keeping all other parameters same as the 2 ns simulation. However negligible change in the ligand configuration and interaction of the ligand with the binding residues at the final equilibrated structure.