Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is also known as novel coronavirus of 2019 (COVID -19) [1] . SARS-CoV-2 causes a wide array of respiratory, gastrointestinal, and neurological diseases in humans [2] [3] [4] . Coronavirus has the largest genomes of the known RNA viruses, ranging ~30 kb [5] , which encodes Structural proteins, S (spike), E (envelope), M (membrane), [6, 7] and Non-structural N (nucleocapsid) proteins [8, 9] . Non-structural protein 15 (NSP15) is an endoribonuclease that cleaves 3' of uridylate through a ribonuclease A (RNase A) [10, 11] . Though it is not required for viral replication, but it mediates evasion of host dsRNA sensors [12, 13] . The structure of SARS-CoV-2 NSP15 protein is very similar to other Coronavirus NSP15 monomers, consisting of mainly three regions: the N-terminal domain, a subsequent middle domain, and a catalytic C-terminal nidoviral RNA uridylate-specific endoribonuclease domain. The active-site residues of NSP15 indicate His262, His277, and Lys317 are conserved across the entire endoribonuclease family and play an important role in enzyme catalysis [13] . The mutant viruses of NSP15 causing apoptotic cell death and significant reduction of replication in macrophages [14, 15] . SARS-CoV-2 has infected more than 14 million people and caused over 532,340 deaths worldwide (https://www.who.int). The rapidly increasing numbers of the infected patients, prompted the World Health Organization to declare a state of global health emergency to coordinate the scientific and medical efforts to expedite the development of a cure for the patients.
NSP15 is important for disease progression and thus, is a potential target for drug and vaccine development. Till date, no targeted treatment molecule has been developed to prevent the COVID-19 infection. Recently in-silico studies have reported the possible inhibitors against NSP15 [16] [17] [18] [19] [20] . Remedesvir and Favipiravir are the latest approved drugs for the treatment of COVID-19 [21, 22] . However, these drugs are not able to control the novel Coronavirus outbreak and the subsequent pandemic [23] . In order to design specific inhibitors against the Non-structural protein 15 (NSP15), Libraries of Selleckchem Natural products (https://www.selleckchem.com/screening/natural-productlibrary.html) were chosen for Virtual screening [24] [25] [26] . Top 10 compounds were selected based on their binding affinities. Further, Molecular dynamic simulation [25] [26] [27] was used to analyze the stability and the inter-molecular interactions between the NSP15 and the lead compounds.
The crystal structure of the Non-structural protein 15 (NSP15) was retrieved from the RCSB Protein Data Bank (entry code 6W01) and, was used as target for our modeling studies. Starting structure of NSP15 for docking studies was prepared with Protein Preparation Wizard [28] . The process adds hydrogen, neutralizes appropriate amino acid chains, and relieves steric clashes. Also, it performs a series of restrained, partial minimizations on the co-crystallized structure, each of which employs a limited number of minimization steps. It is not intended to minimize the system completely. In our study, the minimization (OPLS 2003 force field) [28] was stopped when RMSD of the nonhydrogen atoms reached 0.30 Å, which is the default specified limit.
Selleckchem Natural product libraries with about 900,000 unique molecules and 1,350,000 drug-like and lead-like screening compounds were chosen for virtual screening. Libraries were prepared by energy minimization of 100 steps with the Ligprep module of Schrodinger [29] .
Experimental studies on NSP15 have revealed that His235, His250, and Lys290 [10] are the critical residues for catalysis that are located in the C-terminal domain of the enzyme.
Docking studies [30] [31] [32] [33] [34] were performed using GOLD [35] , and the protein was kept as a rigid molecule, and the number of Genetic Algorithm (GA) runs was set to 10 runs per ligand with the default search algorithm parameters. GOLD score was then used as the final scoring method.
In order to estimate the accuracy of binding affinity of GLIDE [36] , MOE docking [31] and Auto-dock [37] were used for cross-docking analysis.
In the Glide-docking [36] , the prepared structure was used to generate the receptor grid and no scaling was done for the Van der Waals radii of nonpolar receptor atoms. An enclosing box was used as the docking space, centered on the His235, His250, and Lys290, catalytic triad using the crystallographic position as their reference; the ligand diameter midpoint box was set to the default value (10 Å). Docking experiments were performed using 0.80 to scale the VdW radii of the nonpolar ligand atoms with a charge cutoff of 0.15. Poses were discarded as duplicates if both, the rms deviations in the ligand (all atoms) was less than 0.5 Å and maximum atomic displacement was less than 1.3 Å.
At most, 10 poses per ligand were retained. GlideScore XP [36] was used as the scoring method to finalize the screening.
For MOE docking [31] , the protein was kept as a rigid entity, and a maximum of 10 conformations for each ligand was taken using the default parameters of MOE with In the AutoDock 4.2 [37] , empirical free energy function and the Lamarckian Genetic Algorithm were used for all the docking calculations and the AutoDockTools (ADT) package [28] was used to generate input files and to analyze the results. The NSP15 was set to be rigid and in small molecules all the torsional bonds were kept free during the docking process. The solvent molecules were not considered during the docking process.
A cubic grid box of 60 Å size (x62.520, y73.546, z29.278) with a spacing of 0.375 Å and grid maps was created. The ten best solutions based on the docking scores were retained for further investigations. XSCORE [38] has been used to estimate the binding affinity of the molecules. Interactions between the protein and the compounds were calculated using the Discovery Studio program [39] . All Molecular dynamic simulation (MD) were performed with GROMACS [40] , using the GROMOS 53A6 force field [40] . Further details of the simulation protocol have been used as described previously [25] [26] [27] .
Superposition of NSP15 with all other available coronavirus homologues reveals structural conservation amongst these proteins. The structure of the SARS-CoV-2 yielded a RMSD of 0.4 Å and 0.9Å with SARS-CoV, and Murine-CoV NSP15, respectively ( Figure 1 ). Comparison of all the 3 structures showed some deviations in the active site residues as marked in Figure 2 . These conformational changes at the active site of NSP15 need to be considered carefully during the inhibitor design. GOLD [35] was used to perform virtual screening. Further, multiple docking algorithms using GLIDE [36] , Auto-dock [37] and MOE [31] docking ensures the accurate prediction of binding affinities. These docking algorithms are the most commonly used to estimate the binding affinity and binding pose of the inhibitor and the enzyme. The identification of the inhibitors for various targets using these docking and virtual screening algorithms obtained high successful rate based on our previous studies [24] [25] [26] [27] .
Therefore, we used all of the above-mentioned software to dock the Selleckchem Natural Product database (https://www.selleckchem.com/screening/natural-product-library.html) of 28,228 small molecules against NSP15 in order to evaluate their binding affinities. Also, we docked the previously reported ligands [16-20, 41, 42] , Remedesvir [21, 22] and Lopinavir [21, 22] as reference.
The top-ranked docked molecules were sorted according to their GOLD score [35] , GLIDE score [36] , Auto-dock free energy of binding [37] and MOE score [31] and XSCORE [38] . These criteria were applied for the higher binding affinity compounds against NSP15 enzyme. Mainly the mode of binding and their potential interactions with the active site residues, and the estimated binding affinities were the major factors considered (Table 2) (Figure 3 & Figure 4 ).
We have chosen the top 10 compounds ( Figure 5 ) for further analysis since these drug compounds yielded higher binding affinities ( Table 1 ). The top 10 compounds were found to fit tightly into the hydrophobic binding pocket and in close interaction with the catalytic triad. Among these compounds, five compounds show higher binding affinities compared to the reported compounds for NSP15 (Table S1) ( Figure S1 ). The toxicity analysis does not indicate any adverse effects for the top compounds (Table S2) , and can be thus taken forward for further studies.
After the docking studies, the Molecular dynamic simulation [25] [26] [27] was performed for the top five screened compounds (Thymopentin, Ginsenoside, Oleuropein, Akebia Saponin D and Keampferitrin), to understand the binding stability of the docked complexes. The simulations were performed for a 100 ns to analyze the conformational stability of these complexes. Molecular dynamic simulation [25] [26] [27] is considered to be a reliable approach with greater insight into the dynamic behavior of proteins and that of the ligand conformations [25] [26] [27] . According to the RMSD (Root-Mean-Square Deviation) calculation, shown in Figure 5 , it can be seen that all the complexes tend to achieve equilibrium after 10 ns and lead to a stable trajectory throughout the simulation. We found that Ginsenoside, Kaempgeritrin and Akebia saponin D complexes with NSP15 tend to reach a higher equilibrium compared to the native, and remained distinguished throughout the simulation, resulting in the RMSD of 0.1 to 0.75 nm. The RMSD trajectories for the Thymopentin and
Oleuropein complexes with NSP15 observed a lower equilibrium compared to the native with minor difference in their trajectory that leads to a stable equilibrium through the end of the simulation, suggesting that the complexes stabilized themselves ( Figure 6A ). The higher RMSD obtained for all the complexes were limited to 0.75 nm that demonstrates the stable trajectories and provided us with an appropriate basis for further investigation.
( Figure 6A ). Oleuropein complexes were more stable than the Akebia Saponin D and Keampgertrin complexes. (Fig. 6B ).
The Rg (radius of gyration) is used to calculate the compactness of a protein ( Figure 5C ).
The radius of gyration is the root mean square distance of a particular atom or group of atoms with its center of mass. The overall NSP15 structure at various time points during the trajectory can be analyzed for the competence, shape, and folding in the Rg plot (.
( Figure 5C ). Akebia Saponin D-NSP15 complex showed a higher deviation with a Rg score of 2.4 nm. All the other compounds, Ginsenoside, Thymopentin, Oleuropein, and
Keampgertrin had an aggregate Rg score of 2.2 nm in a decreasing trend followed by stabilisation after 40 ns towards the end of the simulation ( Figure 6C ).
We have measured the compactness of the hydrophobic core by analyzing the changes in SASA. As shown in Figure 5D , an increase of the SASA values were observed for Akebia Saponin D and Keampgertrin after 10 ns of simulation time maintained till the end, while the Ginsenoside, Thymopentin, and Oleuropein complexes showed stable conformation throughout the simulations. As higher SASA value leads to an increased exposure, there was loss of hydrophobic contact between the protein-ligand complexes ( Figure 6D ).
Finally, the number of hydrogen bonds for each of the protein complex was calculated during the simulation. An increase of hydrogen bonds, Van der Waals, and electrostatic interactions were observed for Ginsenoside, Thymopentin, Oleuropein compounds, while Akebia Saponin D and Keampgertrin formed lesser interactions (Fig. 3 & Fig. 4 ).
The top-ranked compound obtained from the virtual screening is the FDA approved drug, Thymopentin (Table 1) . Thymopentin binds to the active site of NSP15 endoribonuclease and may potentially block the replication of virus. Thymopentin (TP5)
is a synthetic pentapeptide (Arg-Lys-AspVal-Tyr) belongs to the native thymic hormone thymopoietin [43] . Thymopentin has been suggested for the treatment of autoimmune diseases, and including chronic lymphocytic leukemia [44] , rheumatoid arthritis [45] , cancer immunodeficiency [46] , acquired immunodeficiency syndrome (AIDS) [47] , and chronic heart failure [48] . Thymopentin [45] is also known to be an effective immunomodulatory agent and helps to improve immunological condition for patients.
The second compound, Oleuropein showed strong binding with NSP15 endoribonuclease. Oleuropein is a phenylethanoid, mainly found in the olive leaves.
Oleuropein suppresses cancer cells by activating the gerosuppressor AMPK by reduction of growth in human primary cells leads to several transcriptomic signatures [49] .
Oleuropein helps reducing colonic microflora by Hydroxytyrosol (HT) and is mainly present in the olive leaf and olive oil. Oleuropein is known to be a potent antioxidants observed in nature to date [50] .
The third rank compound, Ginsenoside also binds tightly to the catalytic center of NSP15 structure. Ginsenosides are the natural products of steroid glycosides and triterpene saponins. Ginsenosides family consists of the oleanane family and is pentacylic in nature, composed of a five-ring carbon skeleton [51] . Ginsenosides have shown diverse pharmacological and biological properties, such as antitumorogenic, anti-inflammatory, antioxidant, and inhibitor of cell apoptosis.
The top ranking compound Thymopentin [43] [44] [45] [46] [47] [48] , FDA approved drug is currently available in the market. The other two compounds, Oleuropein [49, 50] and Ginsensoside [51] are also promising ones. Hence, these drugs might help to reduce the virulence of the virus and can be considered for patients being treated for COVID -19.
In this study, structure based virtual screening followed by the validation through Molecular dynamic simulation approaches were carried out to find antiviral leads against NSP15 of SARS-CoV-2. Thymopentin (FDA-approved), Ginsenoside, and Oleuropein were identified as potential inhibitors of NSP15. Molecular docking and MD simulations investigated the binding affinities, mode of binding, stability of binding and their potential interactions. The drug leads identified in this study sheds light on the pandemic infectious disease that currently lacks specific drugs and vaccines. Further investigations will be carried out for these drugs to check their efficiency in vitro and in vivo.