key: cord-0990414-0nqz5y20
authors: Mirza, Muhammad Usman; Froeyen, Matheus
title: Structural elucidation of SARS-CoV-2 vital proteins: Computational methods reveal potential drug candidates against main protease, Nsp12 polymerase and Nsp13 helicase
date: 2020-04-28
journal: J Pharm Anal
DOI: 10.1016/j.jpha.2020.04.008
sha: 0dbf4748c37b581123eb4daeb457f849cd18bd37
doc_id: 990414
cord_uid: 0nqz5y20

Abstract The recently emerged SARS-CoV-2 caused a major outbreak of coronavirus disease 2019 (COVID-19) and instigated a widespread fear, threatening global health security. To date, no licensed antiviral drugs or vaccines are available against COVID-19 although several clinical trials are underway to test possible therapies. During this urgency situation, computational drug discovery methods provide an alternative to tiresome high-throughput screening, particularly in the hit-to-lead-optimization stage. Identification of small molecules that specifically target viral replication apparatus has indicated highest potential towards antiviral drug discovery. In this work, we present potential compounds that specifically target SARS-CoV-2 vital proteins, including the main protease, Nsp12 RNA polymerase and Nsp13 helicase. An integrative virtual screening and molecular dynamics simulations approach led to the identification of potential binding modes and favourable molecular interaction profile of corresponding compounds. Moreover, the identification of structurally important binding site residues in conserved motifs located inside the active site highlights relative importance of ligand binding based on residual energy decomposition analysis. Although the current study lacks experimental validation, the structural information obtained from this computational study has paved way for the design of targeted inhibitors to combat COVID-19 outbreak.

The ongoing 2019-20 outbreak of coronavirus disease 2019 (COVID-19) [1] , as of 20 April 2020, has claimed 157, 847 lives globally and has been declared as a pandemic. SARS-CoV-2 belongs to the Coronaviruses family and is the seventh known human coronavirus (HCoV) from the same family after 229E, NL63, OC43, HKU1, MERS-CoV, and SARS-CoV [1] .

Currently, there is no licensed drug or vaccine available for SARS-CoV-2. Although several clinical trials are in progress to test possible therapies, the treatment is focused on the alleviation of symptoms which may include dry cough, fever and pneumonia [2] . Following the SARS outbreak, existing antivirals, including nine protease inhibitors [3] , nelfinavir blocked SARS-CoV-2 replication at lowest concentration (EC 50 = 1.13 µM, CC 50 = 24.32 µM, SI = 21.52). Following this, antiviral efficiency of several FDA-approved drugs have been reported, including remdesivir (GS-5734, Gilead) (EC50 = 0.77 μM) and chloroquine (EC50 = 1.13 μM) against a clinical isolate of SARS-CoV-2 in vitro showed potential inhibition at low-micromolar concentration [4] . The efficacy of remdesivir is evident from a recent recovery of US patient infected with SARS-CoV-2 after intravenous treatment [5] , while chloroquine is being evaluated in an open-label trial (ChiCTR2000029609). Moreover, Ivermectin, a broad spectrum anti-parasitic agent reported in vitro activity (~5000-fold reduction) in a model of Vero/hSLAM cells infected with a SARS-CoV-2 isolate (Australia/VIC01/2020) [6] . Others include Nafamostat (EC50 = 22.50 μM), Nitazoxanide (EC50 = 2.12 μM) and Favipiravir (EC50 = 61.88 μM) [4] . Recently, hydroxychloroquine has shown to be effective in COVID-19 patients [7] and its efficiency has been reportedly reinforced by azithromycin for virus elimination [8] , despite there is no well-controlled, randomized clinical evidence support azithromycin therapy in COVID-19 [9] .

CoVs are single-stranded positive-sense RNA (+ssRNA) viruses with 5'-cap and 3'-poly-A tail. The ~30kb SARS-CoV-2 genome contains at least six open reading frames (ORFs). The first ORF (ORF1a/b) is about two-thirds of the whole genome length and encodes 16 nonstructural proteins (nsp1-16). ORFs near 3'-end of the genome encodes four main structural proteins including spike (S), membrane (M), envelope (E), and nucleocapsid (N) proteins. Among non-structural proteins, most are known to play a vital role in CoV replication. Structural proteins, however, are important for virion assembly as well as for causing CoV infection. Additionally, specific structural and accessory proteins such as HE protein are also encoded by the CoV genome [10] . SARS-CoV-2 maintains ~80% nucleotide identity to the original SARS epidemic viruses [11] .

To address the current outbreak, the development of wide-spectrum inhibitors against CoVassociated diseases is an attractive strategy. However, this approach requires the identification of a conserved target region within entire Coronavirus genus [12, 13] . On the contrary, all structural proteins including S, E, M, HE, and N proteins among different CoVs have considerable variations as reported [14] [15] [16] therefore, adding more complexity towards identification of SARS-CoV-2 inhibitors. Subsequently, the Nsp12 RNA-dependent RNA polymerase (RdRp), Nsp13 helicase, and main protease (Mpro) or chymotrypsin-like protease (3CLpro) [17] constitute highly conserved regions in non-structural proteins among coronaviruses which can be targeted.

Although no structural data was available for SARS-CoV-2 proteins at the start of this study, however, considering high sequence similarity, SARS-CoV-2 proteins were modeled for rational drug design which can later lead to downstream modification for drug leads. The current study focusses on structure elucidation of a critically important nCoV-Nsp12 polymerase, Nsp13 helicase and Mpro together with virtual screening (VS). The study reports potential hits identified through integrative VS and molecular dynamics simulation approach. Although the current study lacks experimental validation of proposed hits, however, structural information along with the identified potential hits may serve as the starting point for structure-guided drug discovery.

Homology models of key SARS-CoV-2 proteins including Mpro, Nsp12 polymerase, Nsp13 helicase were designed using SWISSMODEL [18] as there were no resolved crystal structures available at the time of this study. Later for molecular docking studies, a recently reported co-crystalized Mpro structure was utilized (PDB ID: 6LU7). Templates with the highest identity were selected, and respective models were generated. The residues inside the binding pocket were predicted using an analytical tool, COACH meta-server and compared after superimposing various closely related X-ray resolved co-crystallized structures with bound inhibitors. The generated homology models were refined using 20ns molecular dynamics (MD) simulations to remove steric clashes and optimize side-chain geometry.

AMBER18 simulation package was utilized for unrestrained MD simulations using AMBER ff99SB force field [19] . The stepwise minimization and equilibration protocol were performed (details in SI), and solvated system for each model with explicit TIP3 water molecules was submitted to a production run of 20 ns at constant 300K temperature and 1 bar pressure. The protein backbone conformation was analyzed using CPPTRAJ module and evaluated through Ramachandhran plots. The most favourable conformation was selected for virtual screening.

Small molecules dataset in SMILES format was downloaded from ZINC database [20] and uploaded to Mcule which is a fully automated drug discovery platform [21] . Virtual screening pipeline was established using drug-like filters. Diversity selection was implemented to reduce the size of the library and to maximize the coverage of chemical space at the same time. This procedure excluded the closest analogues based on the Tanimoto similarity coefficient and maximized the diversity of the potential active scaffolds identified from the huge dataset. A thorough analysis of binding site residues was performed prior to docking, as depicted from COACH and structure comparisons. Docking grid was set up covering the key binding site residues to reduce the search space for ligand optimization.

An automated in-built Autodock (AD) Vina docking engine was utilized to screen the composed docking library, which uses gradient optimization method in its local optimization process to rank the best poses efficiently [22] . Individual compounds of the docking library together with Mcule database were docked iteratively into respective binding pockets of the representative SARS-CoV-2 Mpro, Nsp12 polymerase, Nsp13 helicase structures. The compounds were ranked based on Vina empirical scoring function that approximates the ligand binding affinity in kcal/mol. Since, various docking programs only estimate the real binding affinity, therefore testing different docking programs adds reliability. The top hits obtained from first round of docking were then evaluated with Glide "extra precision" docking mode (Glide XP) as implemented in Schrödinger's Maestro modeling package (a trial version was utilized for this study). SARS-CoV-2 proteins were prepared using protein preparation wizard by adding hydrogen atoms and missing side chains, while short minimization of only the hydrogen atoms was carried out using the OPLS 3 force field. Selected ligands ranked by AutoDock Vina were prepared using LigPrep as described previously [23] . The grid box was generated with dimensions covering the predicted active site residues. Top hits were selected after extensive post-docking analysis by comparing the binding poses predicted from AD Vina and Glide.

To gain more understanding of the predicted molecular interactions, the best docked complexes were analysed over a period of 20ns MD simulations using AMBER 18 simulation package. The antechamber module of AMBER18 was used to generate atomic partial charges for the selected hits. In this study, previously reported MD simulation protocol was followed [23, 24] (details in SI). To gain rational insights into the different binding modes and residual contribution, the Molecular Mechanics/Generalized Born Solvent Area (MM/GBSA) method was employed and total binding free energies (kcal/mol) were calculated. The MM/GBSA approach is well detailed in binding free energy calculations [25] for antiviral inhibitors [26, 27] .

In silico modeling work was initiated by analysing Wuhan seafood market pneumonia virus genome (NCBI genome ID MN908947), which was recently deposited by Wu et al., [28] . For the current work, orf1ab polyprotein sequence (GenBank ID: QHD43415.1) was considered (a total of 7096 amino acids). In order to locate the potential Nsp12, Nsp13 and Mpro sequence, a multiple sequence alignment was performed with known SARS-CoV proteins (Uniprot ID: P0C6X7). The corresponding regions in SARS-CoV-2 genome were identified based on the sequence identity and similarity score. Sequence alignment revealed that SARS-CoV-2 Nsp12 polymerase, Nsp13 helicase and Mpro shared high similarity with that of SARS.

Homology modeling was performed using SWISSMODEL and generated models were validated accordingly. SARS-CoV proteins deposited in Protein Data Bank (PDB) indicated 96.35%, 99.83% and 96.08% identities with SARS-CoV Nsp12 (6NUR), Nsp13 (6JYT) and Mpro (2Z9J). As a result of high sequence similarity (>96 %), the homology models revealed a strikingly conserved overall architecture. The superimposition of RdRp, helicase and Mpro with SARS-CoV proteins demonstrated high structural similarity, with root mean square deviation (RMSD) values of 1.35 Å, 0.25 Å and 0.46 Å respectively. Model validation using PROCHECK indicated 96.51% (Mpro) and 97.5% (RdRp) of all residues in Ramachandran favoured regions with 3.27% and 0.28% were rotamer outliers, while helicase indicated 84.34% with 4.43% outliers. The models were further refined by 20ns MD simulation and compared with the templates. With the availability of the crystal structure of SARS-CoV-2 Mpro (6LU7) complexed with N3 peptide, homology model was also compared and less than 0.5 Å RMSD was found which indicated the reliability of the generated model with only subtle difference (Figures S1 -S3) . Overall, SARS-CoV-2 Nsp12 polymerase and Nsp13 helicase models were reliable enough to perform virtual screening. For Mpro, co-crystalized structure (6LU7) was utilized. All models revealed the conserved features especially in functional regions due to strikingly similar protein conformation. However, some of the structural features have been elucidated together with the identification of inhibitor binding site in SARS-CoV-2 proteins as shown in Figure 1 . [13] , N1 (1WOF), I2 (2D2D), N3 (2AMQ), N9 (2AMD) also revealed the similar position of S1, S2, and S4 subsites, especially in the active site close to His41 and Cys145, which is crucial for substrate recognition [13] , along with Tyr161 and His163 in the substrate-binding pocket [29] . Docking grid was formed around these subsites for virtual screening by taking co-crystalized SARS-CoV-2 Mpro (6LU7), and top hits were identified based on the docking scores.

The SARS-CoV-2 Nsp12 polymerase was predicted to contain 932 amino acids (located in the polyprotein, from 4393 -5324 a.a). The nsp12 comprised of N-terminal (1-397 a.a) and a polymerase domain (a.a. 398-919) when compared with SARS-CoV Nsp12 (6NUR). The polymerase domain adopted a structure resembling a cupped "right hand" like other polymerases [24] . Nsp 12 polymerase is comprised of a finger (398-581 and 628-687 a.a), a palm (582-627 and 688-815 a.a), and a thumb subdomain (816-919 a.a) ( Figure 1B) . Similar to MERS and SARS-Nsp12, the finger and the thumb subdomains of nCoV-RdRp contact each other, which configured the RdRp active site in the centre for the substrate access through template entry, template-primer exit, and NTP tunnels [30] . Alongside, the SARS-CoV-2 nsp12 also revealed seven conserved motifs (A -G) arranged in the polymerase active site chamber, which are involved in a template and nucleotide binding and catalysis [31] . The binding site of SARS-CoV-2 nsp12 was further analysed through the superimposition of elongation complex of Poliovirus bound with CTP-Mn (3LO8) [32] and crystal structure of Japanese encephalitis RdRp in complex with ATP (4HDH) [33] . Docking grid was formed around the polymerase active site chamber covering the conserved motifs (A -G), and potential hits were identified.

The SARS-CoV-2 Nsp13 was predicted to contain 596 amino acids (located in orflab polyprotein, from 5325-5925 a.a). Like SARS and MERS-Nsp13, the overall structure of SARS-CoV-2 nsp13 adopted a triangular pyramid shape comprising five domains. Among these, two "RecA-like" domains, 1A (261-441 a.a) and 2A (442-596 a.a), and 1B domain (150-260 a.a) forming the triangular base, while N-terminal Zinc binding domain (ZBD) (1-99 a.a) and stalk domain (100-149 a.a) , which connects ZBD and 1B domain, are arranged at the apex of the pyramid ( Figure 1C) . Small molecules able to inhibit the NTPase activity by interferences with ATP binding may serve as an ideal strategy to develop inhibitors. The SARS-CoV-2 nsp13 revealed the similar conserved NTPase active site residues including Lys288, Ser289, Asp374, Glu375, Gln404 and Arg567 as present in SARS-Nsp13. All these residues were clustered together in the cleft located at the base between domain 1A and 2B, while docking grid was formed by locating bound ADP of crystalized yeast Upf1 and top hits were identified.

A stepwise structure-based virtual screening pipeline was adopted considering the putative binding sites of SARS-CoV-2 Mpro, Nsp12 polymerase and Nsp13 helicase to identity potential hits as described in previous studies [24, 34, 35] . The identified potential hits against each target were subjected to in silico ADMET (absorption, distribution, metabolism, elimination, toxicity) predictions, which includes drug-likeness and toxicity potential. This filtering removed substantial hits that exhibited poor ADMET due to inhibitory effects on the renal organic cation transporter and CYP450 isozymes. While a large subset of hits was found to contain high-risk chemical groups like epoxides and quinones, the potential hits against each target with the lowest docking energy were analysed for their binding pose inside the binding site. After careful inspection, best hits based on AD Vina predicted binding energies were re-docked with Glide and best docked complexes were further processed through 20ns MD simulations. MMGBSA method was employed to analyse electrostatic and vdW energy contribution towards total free energy of binding. The MD-simulated complexes indicating protein backbone stability (during the last 5ns in a 20 ns production run) were considered for further molecular interaction analysis. Based on molecular interactions and binding free energy calculations, the subsequent screening resulted in 5, 4 and 3 hits for SARS-CoV-2 Mpro, Nsp12 and Nsp13, respectively (Detailed ADMET profile of these compounds is tabulated in Table S1 , estimated from Swiss-ADME server [36] ). The top hits with AD Vina, Glide XP-score together with contribution of electrostatic (ΔE ele ), van der Waals (ΔE vdw ), and solute-solvent energies (ΔG np and ΔG p ) towards total binding free energy (ΔG tol ) were estimated through Amber-MMGBSA module as tabulated in Table 1 . All energy contributions were calculated in kcal/mol. Note: ΔG tol is the sum of molecular mechanics energy (ΔE MM ) and solvation free energy (ΔG sol ). Both ΔE MM and ΔG sol are further divided into internal energy (ΔE int ), electrostatic energy (ΔE ele ), and van der Waals (ΔE vdw ) energy in the gas phase, and polar (ΔG p ) and non-polar (ΔG np ) contributions to the solvation free energy. The units of these parameters are calculated in kcal/mol.

As a validation docking protocol, the cocrystalized N3 peptide was removed and redocked with the substrate-binding site of SARS-CoV-2 Mpro (6LU7) using the same docking parameters. The generated redocked pose was quite similar with the co-crystalized conformation ( Figure S4 ). Top-ranked SARS-CoV-2 Mpro hits were filtered based on the interaction with the catalytic dyad (at least one H-bond with either His41 or Cys145 or strong vdW interactions). A total of 13 compounds were analysed after 20 ns MD simulation based on the stability for at least last 5 ns. MMGBSA calculations were performed for the most stable complexes. Among top hits, total binding free energies (ΔG tol ) were very promising for cmp12, cmp14, cmp17 and cmp18 which exhibited ΔG tol = -45. (Table 1) . Further in-depth molecular interaction analysis after 20ns MD simulations unveiled significant findings with respect to Mpro-subsites ( Figure 2A ) and per-residue decomposition is displayed in Figure 2B . Among all compounds, cmp12 and 14 showed some consensus features, where pentacyclic moiety of cmp12 anchored right inside the subsites and formed H-bonds with Ser144 of S1 Figure 2B) . Such favourable residual energy contribution was evident from the H-bonds formed by Glu166, Glu189 and Met165. The 2D chemical structure representation of each compound is displayed in connection with interactions of structural moieties with binding pocket subsites ( Figure 2C, 2D) . 

For SARS-CoV-2 Nsp12 RdRp, hits were selected based on establishing H-bond with conserved motifs, especially with signature motif C (SDD), which has been experimentally evaluated in altering polymerase activity supported from various mutational studies [37] [38] [39] .

A total of 17 hits were analysed through 20ns MD simulations, and complexes with stable RMSD were further processed through MMGBSA binding free energy calculations. Among all hits, cmp2, 17a and 21 showed promising ΔG tol (-41.74, -34.37, -24.9 kcal/mol) which mainly interacted through H-bonds, thus contributing electrostatically ( Table 1 ). All these complexes remained stable throughout 20 ns MD simulations ( Figure S6) . A careful molecular inspection after MD revealed the similar conformation of these compounds, which were found to interact extensively with the conserved motifs (Figure 3 ). Cmp2 established three H-bonds with the residues belonging to signature motif C (Ser759), motif D (Lys798) and motif E (Ser814) (Figure 3B ), Cmp17a formed five H-bonds with Arg624 (motif A), Thr680 and Ser682 (motif B), Ser756 (motif C) and Lys798 (motif D) (Figure 3C) , whereas cmp21 interacted mainly with the residues of motif A (Asp623), motif F (Arg553 and Arg555), and motif C (Ser759) through four H-bonds ( Figure 3D ). Together various residues also contributed through strong hydrophobic interactions, for instance, Tyr455 established strong stalking interaction with terminal difluorobenzene of cmp21. Perresidue binding energy decomposition analysis revealed a key role of important residues located in conserved polymerase motifs ( Figure 3F) . These include the residues: (i) Arg553 and Arg555 of motif F which exhibited most favourable ΔG tol with cmp2 (-2.05 and -2.14 kcal/mol), 17a (-1.84 and -2.57 kcal/mol) and 21 (-2.4 and -1.04 kcal/mol), (ii) conserved Aspartate residues of motif A (Asp618 and Asp623) and C (Asp760), and (iii) conserved Serine residues of motif B (Ser682) and motif C (Ser759) and, d) Lys798 of motif D. Among these, Ser759 and Asp760 of motif C exhibited significant binding free energy with all compounds (ranging from -0.988 to -1.76 kcal/mol and -1.03 to -1.47 kcal/mol), while most of the residues interacted electrostatically. By the end of long run simulation process, an xray resolved SARS-CoV-2 Nsp12 polymerase structure was deposited (6M71) [40] . We compared crystal structure of SARS-CoV-2 and found only 0.41Å deviation ( Figure S7) . In further support, MD simulations of homology model and 6M71 also showed consensus RMSD over a period of 50ns. Moreover, the conformations of cmp2, 17a and 21 showed identical binding modes when docked inside the polymerase active site of crystal structure. Additionally, the binding mode and molecular interaction profile of cmp2, 17a and 21 agreed with the reported comparative binding model of remdesivir and sofosbuvir diphosphate (HCV-RdRp, 4WTG) [41] with polymerase ( Figure S7 ) [40] .

For SARS-CoV-2 Nsp13 helicase, top hits were selected based on significant interactions with six key residues (Lys288, Ser289, Asp374, Glu375, Gln404 and Arg567) including neighbouring residues involved in NTP hydrolysis [42] . A 20 ns MD simulations on top ranked complexes led to the identification of 4 best compounds based on considerable interactions with key residues and demonstrated favourable MMGBSA binding free energy ( Table 1) . All these complexes remained stable throughout 20 ns MD simulations except Cmp3a, which fluctuated in the start and adopted a more favourable conformation inside the binding pocket ( Figure S8 ). The superimposition of Upf1-ADP showed the overall same binding mode as identified with these 4 compounds (Figure 4 ). Two dimensional (2D) interaction plot of yeast Upf1-ADP revealed a network of H-bonds established by phosphate groups with Lys436, Thr434, Gly433, Arg639 Gly435 which were also conserved in nCoV-helicase ( Figure 4A ). MMGBSA method estimated favourable ΔG tol in cmp1 (-37.29 kcal/mol), cmp3a (-40.08 kcal/mol) and cmp11 (-49.73 kcal/mol) except cmp15 (-30.56 kcal/mol) and contributed mainly through vdW energies, while nonpolar solvation energies also slightly contributed (Table 1 ). In-depth molecular analysis of cmp11 showed most significant MMGBSA total energy which indicated 3 H-bonds established between Ser310, Glu375 and Lys288 and terminal region of cmp11, and interacted mainly with the side chains of Glu374, Met378, Ala312, Arg178, Ser535. Ser539 and Asp534 ( Figure 4B) . These residues were also found conserved in Upf1-ADP complex except Met378 and Arg178. Per-residue energy decomposition analysis indicated major contributions from Arg178 of domain 1B, Ala312 and Ala314 of domain 1A which indicated < -1.5 kcal/mol binding energy with all four compounds. Together with, Ser288 and Ser310 also contributed in total free energy of binding ( Figure 4C ).

The computational methods offer an immediate and scientifically sound basis to design highly specific inhibitor against important viral proteins and give aid in antiviral drug discovery [43, 44] . A recent structural modeling effort predicted few repurposed drugs against SARS-CoV-2 vital proteins including anti-bacterial, anti-fungal, anti-HIV drugs, and flavonoids from different sources [45] . In the current study, a brief structural elucidation was performed together which revealed strikingly similar features in SARS-CoV-2, when compared with crystal structures of SARS-CoV-RdRp (6NUR) and helicase (6JYT). These viral proteins play a crucial role in the viral life cycle and considered among the most popular strategies for antiviral therapeutics [44, 46] . Structural analyses has revealed that the substrate-binding pockets of SARS-CoV-Mpro, active site of RdRp and NTPase binding pocket of helicase are highly conserved [47] , which can lead to the concept of "widespectrum inhibitors" for targeting CoVs. Furthermore, extensive SBVS procedure led to the identification of potential hits against each target, which were assessed through MD simulations. MM-GBSA and per residue energy decomposition divulged the relative importance of amino acid involved in binding supported with the contribution of different components of binding free energy.

Overall, SARS-CoV-2-Mpro hits were found to interact with catalytic dyad (His41 or Cys145) together with residues located at S4, S2 and S1 subsites of substrate binding pocket and mutational studies of His41 or Cys145 resulted in complete loss of enzymatic activity, which confirmed the role of catalytic dyad [48, 49] . In the substrate-binding pocket, catalytic dyad residues, highly conserved residues of S1, Gln189 and Met165 of S4, displayed relative importance in ligand binding, suggested a possibility for inhibitor design targeting this region in the Mpro. In case of SARS-CoV-2 Nsp12, the in-depth interaction analysis inside the conserved motifs (Figure 3 ) revealed functionally important aspartate residues of motif A (Asp623) and motif C (Asp760), together with conserved Arginine residues of motif F (Arg553 and Arg555), and Ser759 (motif C) which were found highly interacted with the compounds. Among these, motif A and C are most strikingly conserved aspartate residues that bind divalent metal ions necessary for catalytic activity [30, 31] . Moreover, the importance of aspartate residues in RdRps supported from various other mutational studies [37] [38] [39] , suggested a conserved binding feature of cmp2, cmp17a and cmp21 along with side chains of Arg553, Arg555 and Ser759 which line deep in the binding pocket of nCoV-RdRp, thus enhancing it as an anchor for inhibitory molecules.

In SARS-CoV-2-helicase, the structural information of NTPase active site obtained after superimposing SARS-helicase and Yeast-Upf1-ADP divulged the location of conserved residues. The identified hits positioned similarly with reference to the interaction network reported for co-crystalized ADP (Figure 4) . In the active site, the side chains of Ser310, Lys288 and Glu375 actively participated in H-bond, while Arg178 and conserved alanine residues (Ala312 and Ala314) contributed substantially towards total binding free energy.

Moreover, the importance of these residues has already been highlighted in mutational studies [42] .

Moreover, the identified compounds exhibited promising ADMET properties and none of the compounds were found to contain any high-risk chemical group. The drug candidates with poor ADMET might lead to toxic metabolites [50] or be unable to cross membranes [51] , and the predicted solubilities were estimated within an acceptable range [52] . Most of the compounds were predicted as non-inhibitors for cytochrome P450 isozymes which play a vital role in drug metabolism and inhibition of these enzymes leads to toxicity and poor excretion from liver [53] . Moreover, all compounds were found novel as they were not reported elsewhere against antiviral activities. Among various hits identified, cmp2 against SARS-CoV-2 RdRp was recently reported as Pan-Janus Kinase Inhibitor Clinical Candidate (PF-06263276) for its potential role in the treatment of inflammatory diseases of lungs [54] . Hence, the cmp2 could be ideal for reducing the inflammatory activity during pathogenic COVID-19 epidemic, as lung inflammation has been observed during the SARS and MERS outbreaks.

Conclusively, this comprehensive study presents an integrated computational approach towards the identification of novel inhibitors into the area of anti-nCoV treatment as a starting point, which warrants in vitro testing to evaluate compound efficacy. The in-depth structural elucidation of interacting residues together with the dynamic conformations adopted over a period of 20ns MD simulations of identified compounds offered the way to design wide-spectrum or selective inhibitors against HCoV.

The 2019-new Coronavirus epidemic: evidence for virus evolution, bioRxiv

Systematic Review of the Registered Clinical Trials of Coronavirus Diseases 2019 (COVID-19), medRxiv

Nelfinavir inhibits replication of severe acute respiratory syndrome coronavirus 2 in vitro, bioRxiv

Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro

First case of 2019 novel coronavirus in the United States

The FDA-approved Drug Ivermectin inhibits the replication of SARS-CoV-2 in vitro

Chloroquine and hydroxychloroquine as available weapons to fight COVID-19

Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial

Coronaviruses: genome structure, replication, and pathogenesis

Return of the Coronavirus: 2019-nCoV

Potential antivirals and antiviral strategies against SARS coronavirus infections, Expert review of anti-infective therapy

Design of wide-spectrum inhibitors targeting coronavirus main proteases

The genome sequence of the SARS-associated coronavirus

Characterization of a novel coronavirus associated with severe acute respiratory syndrome, science

Characterization and complete genome sequence of a novel coronavirus, coronavirus HKU1, from patients with pneumonia

Identification of novel inhibitors of the SARS coronavirus main protease 3CLpro

SWISS-MODEL: an automated protein homology-modeling server

ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB

Shoichet, modeling, ZINC− a free database of commercially available compounds for virtual screening

a public web service for drug discovery

AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

Inhibition of Oncogenic Kinases: An In Vitro Validated Computational Approach Identified Potential Multi-Target Anticancer Compounds

In silico structural elucidation of RNA-dependent RNA polymerase towards the identification of potential Crimean-Congo Hemorrhagic Fever Virus inhibitors

Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations

Molecular dynamics investigation on a series of HIV protease inhibitors: assessing the performance of MM-PBSA and MM-GBSA approaches

Investigating interactions between HIV-1 gp41 and inhibitors by molecular dynamics simulation and MM-PBSA/GBSA calculations

Reversible unfolding of the severe acute respiratory syndrome coronavirus main protease in guanidinium chloride

Picornaviral polymerase structure, function, and fidelity modulation

Identification of four conserved motifs among the RNAdependent polymerase encoding elements

Structural basis for active site closure by the poliovirus RNA-dependent RNA polymerase

RNA-dependent RNA polymerase of Japanese encephalitis virus binds the initiator nucleotide GTP to form a mechanistically important preinitiation state

Pharmacoinformatics approach for investigation of alternative potential hepatitis C virus nonstructural protein 5B inhibitors, Drug design, development therapy

Integrated computational approach for virtual hit identification against ebola viral proteins VP35 and VP40

SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules

Mutational analysis of the conserved motifs of influenza A virus polymerase basic protein 1

Mutation analysis of the GDD sequence motif of a calicivirus RNA-dependent RNA polymerase

Mutational analysis of the SDD sequence motif of a PRRSV RNAdependent RNA polymerase

Structure of the RNA-dependent RNA polymerase from COVID-19 virus

Structural basis for RNA replication by the hepatitis C virus polymerase

Delicate structural coordination of the Severe Acute Respiratory Syndrome coronavirus Nsp13 upon ATP hydrolysis

Perspectives towards antiviral drug discovery against Ebola virus

Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods

Molecular targets for flavivirus drug discovery

Learning from the Past: Possible Urgent Prevention and Treatment Options for Severe Acute Respiratory Infections Caused by 2019-nCoV

3C-like proteinase from SARS coronavirus catalyzes substrate hydrolysis by a general base mechanism

pH-dependent conformational flexibility of the SARS-CoV main proteinase (Mpro) dimer: molecular dynamics simulations and multiple X-ray structure analyses

ADME Profiling in Drug Discovery and a New Path Paved on Silica, Drug Discovery and Development-New Advances

Prediction and optimization of pharmacokinetic and toxicity properties of the ligand

Strategies to address low drug solubility in discovery and development

Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation

Design and synthesis of a pan-Janus kinase inhibitor clinical candidate (PF-06263276) suitable for inhaled and topical delivery for the treatment of inflammatory diseases of the lungs and skin

The authors declared no conflict of interest

This article does not contain any study with human or animal subjects.