key: cord-0975851-2guewi2j
authors: Mondal, Sunil Kanti; Mukhoty, Samyabrata; Kundu, Himangsu; Ghosh, Subhajit; Sen, Madhab Kumar; Das, Suvankar; Brogi, Simone
title: In silico analysis of RNA-dependent RNA polymerase of the SARS-CoV-2 and therapeutic potential of existing antiviral drugs
date: 2021-06-23
journal: Comput Biol Med
DOI: 10.1016/j.compbiomed.2021.104591
sha: 15ba8d4e66f9f84b3c109e9377eaa5a703271367
doc_id: 975851
cord_uid: 2guewi2j

The continued sustained threat of the SARS-CoV-2 virus world-wide, urgently calls for far-reaching effective therapeutic strategies for treating this emerging infection. Accordingly, this study explores mode of action and therapeutic potential of existing antiviral drugs. Multiple sequence alignment and phylogenetic analyses indicate that the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 was mutable and similar to bat coronavirus RaTG13. Successive interactions between RdRp (nsp12 alone or in complex with cofactors nsp7-8) and viral RNA demonstrated that the binding affinity values remained the same, but the sites of interaction of RdRp (highly conserved for homologous sequences from different organisms) were altered in the presence of selected antiviral drugs such as Remdesivir, and Sofosbuvir. The antiviral drug Sofosbuvir reduced the number of hydrogen bonds formed between RdRp and RNA. Remdesivir bound more tightly to viral RNA than viral RdRp alone or the nsp12-7-8 hexadecameric complex, resulting in a significant number of hydrogen bonds being formed in the uracil-rich region. The interaction between nsp12-7-8 complex and RNA was mediated by specific interaction sites of nsp7-8. Therefore, the conserved nature of RdRp interaction sites, and alterations due to drug intervention indicate the therapeutic potential of the selected drugs. In this article, we provide additional focus on the interacting amino acids of the nsp7-8 complex and highlight crucial regions that could be targeted for precluding a correct recognition of subunits involved in the hexadecameric assembly, to rationally design molecules endowed with a significant antiviral profile.

Since its outbreak in December 2019, in Wuhan (Hubei Province in China), Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2 also known as 2019 novel coronavirus) has infected more than 150 million people and resulted in more than 3 million deaths across the globe (source: https://www.worldometers.info/coronavirus/). Fever, chills, and shortness of breath are the most common symptoms of SARS-CoV-2, while the lungs are the most affected organ. Additionally, there is a certain level of pathophysiological severity associated with conditions such as pneumonia and thrombosis [1] [2] [3] [4] [5] [6] .

SARS-CoV-2 belongs to a group of positive-sense ssRNA, enveloped viruses (60 nm -140 nm diameter), known as Coronaviruses. They acquired this name due to the presence of characteristic crown-like projections on their surfaces [7] [8] [9] . At present, only four families of these viruses have been identified, namely, α, β, γ, and δ. Among the human coronaviruses SARS-CoV and MERS-CoV fall in category β [10] [11] [12] [13] . The SARS-CoV-2 genome contains 14 functional open reading frames (ORFs) including replicase and protease genes, as well as spike (S), envelope (E), membrane (M), and nucleocapsid (N) genes (order of appearance: 5′ to 3′) [10, 14] . Replicase (ORF1a) and protease (ORF1b) genes can encode polyprotein1a (pp1a) and polyprotein1ab (pp1ab), which get further processed by Papain-like protease (PL pro ) and

Chymotrypsin-like protease (3CL pro ) to yield sixteen individual nonstructural proteins (nsp) [10, 15] . Crucial to the coronavirus infection, trimeric spike glycoprotein (S protein) neutralizes antibodies, binds to the host cell surface, mediates membrane fusion, and finally, the viral particles enter the host cells. The N-terminal or C-terminal domain of the S protein can serve as the receptor-binding domain, depending on the type of virus. Most coronaviruses use their Cterminal domain to bind to receptors [16, 17] . SARS-CoV-2 has used the human angiotensinconverting enzyme 2 (hACE2) as a receptor to enter human cells [18] . As a result, hACE2 was also suggested as a potential drug target for developing anti-CoVid-19 agents [19] . However, the replication of viral RNA within host human cells is catalyzed by a special class of enzymes known as RNA-dependent RNA polymerase (RdRp or RNA replicase). Although, in general, RdRps share structural similarities with DNA-dependent DNA polymerases (DdDps) and reverse transcriptases, the error rate during the transcription process is higher. This higher error rate leads to genomic variations within the viral populations. Because of the process of RNA recombination, viruses can repair these mutations to acquire new genes and result in selective J o u r n a l P r e -p r o o f benefits to the viral population [20] . CoVs replication and transcription processes are primarily facilitated by a set of non-structural proteins (products of viral polyproteins cleavage) and the RdRp. Non-structural proteins 7 and 8 (nsp7 and nsp8) act as cofactors for the SARS-CoV-2-RdRp (also known as nsp12) and play an important role in the replication and transcription cycle of these viruses [21] . In brief, the structure of the SARS-CoV-2-RdRp consists of a polymerase domain (RdRp domain) and a unique N-terminal domain that forms architecture similar to nidovirus RdRp-associated nucleotidyltransferase (NiRAN) [22, 23] . In addition to this conformation, a cryo-EM map reveals that an interface domain connects the polymerase domain with the NiRAN domain. Further details regarding the structure of SARS-CoV-2-RdRp are available in the article by Gao and colleagues [24] . Several epidemiological studies describe the molecular pathogenesis of SARS-CoV-2 [10, [24] [25] [26] .

The alarming increase in the number of SARS-CoV-2 cases world-wide, urgently calls for effective and life-saving strategies, including effective vaccines and drugs for treating emerging and re-emerging diseases. This study examined the potential of existing antiviral drugs to be used as therapeutics and to acquire information about their mode of action. Furthermore, this work delineates the effects of selected existing antiviral drugs on the interaction between RdRp and RNA of SARS-CoV-2 in the presence or absence of the cofactor nsp7-8 hexadecameric complex. We chose the drugs based on the previous available reports on the polymerase protein of several different RNA viruses, in which these antiviral drugs were found to be effective.

However, this work is one of the first reports that considers the nsp12-7-8 hexadecameric complex by investigating its role in the presence of potential antiviral drugs. The systematic study reveals the conserved nature of the interaction sites of RdRp, and the alteration of these sites in presence of the selected antiviral drugs, proving their therapeutic potential. The identified interaction sites of cofactors can be further explored for designing effective drugs against SARS-CoV-2.

All links enclosed in the manuscript were accessed on 03 rd May 2020.

The database from Zhang Lab (available online https://zhanglab.ccmb.med.umich.edu/COVID-J o u r n a l P r e -p r o o f 19/) was examined to identify the amino acid sequence of RdRp of SARS-CoV-2. After that, its homologous sequences were retrieved using the online tool BLASTP 2.2.32 (https://blast.ncbi.nlm.nih.gov/Blast.cgi) [27] . In total, ORF1ab polyprotein from SARS-CoV-2 and 28 organisms (selection criteria: E-value < 0.01, in BLASTP search) were selected for further analyses. The 28 strains are selected on the basis of E-value. E-value meaning changes in the equivalent position due to chance only. The phylogenetic tree was generated by randomly bootstrapping the best E-value.

The identification of the corresponding homologous regions among many input sequences revealed biological relationships among the sequences of interest. The sequence alignment profile of the selected sequences was performed using Clustal Omega tool (https://www.ebi.ac.uk/Tools/msa/clustalo/). JalVeiw option was used to obtain a well-defined representation of the sequence logos [28, 29] . In addition to the sequence alignment, MEGAX (Molecular Evolutionary Genetic Analysis X) program was used to generate maximum-likelihood phylogenetic trees (bootstrap value: 1000; method: Jones-Taylor-Thornton (JTT) model) [30, 31] . [36] [37] [38] . Furthermore, MolProbity was employed to assess the quality of the secondary structure, including phi/psi dihedral angles, of each subunit composing the hexadecameric complex [39] , before starting the assembly of the mentioned arrangement. The analysis revealed that the residues of proteins were in the allowed regions, with no residues in the disallowed regions ( Figure S1 -S3, for nsp7, nsp8, and nsp12, respectively). All residues of the refined subunits reside in acceptable regions of the Ramachandran plot. This value was more than the cut-off value (96.1%) defined for the most reliable models [40] . Consequently, protein quality was satisfactory, and they could be used for further computational studies. Molecular docking studies were conducted through HDOCK webserver (http://hdock.phys.hust.edu.cn/) [41] . The server performed protein-protein and protein-DNA/RNA docking automatically and can predict interactions by employing a hybrid algorithm of template-based and template-free docking. Possible binding sites were not specified, resulting in a blind docking calculation. For accomplishing all docking calculations in this study (blind docking, protein-protein docking, and RNA-protein docking), we used the same program, HDOCK web-server, to treat all components of a given system in the same way, limiting the uncertain. In particular, HDOCK server works in a four-step manner. This server can predict the binding complexes between two molecules (e.g. proteins and nucleic acids) by using a hybrid docking strategy. After the data input for receptor/ligand molecules, a sequence similarity search was conducted against the PDB sequence database in search of the homologous sequences for both the receptor and ligand molecules. The HHSuite package was used to find the homologous sequence for an input protein and the FASTA program was used for nucleic acids. This yielded two sets of homologous templates, one for the receptor and another for the ligand molecule. Next, the two sets of the templates obtained were compared to check whether they have common records with the same PDB codes. If such PDB codes were found, the server selected a common template for both the receptor and the ligand molecules. However, if multiple templates were J o u r n a l P r e -p r o o f available, the server selected the template with the highest sequence convergence, the highest sequence similarity and with the highest resolution. Then, models were built with the selected templates by using MODELLER (https://salilab.org/modeller/), in which the sequence alignment was conducted using ClustalW. For the docking process, a fast Fourier transform (FFT)-based docking program was used to calculate the interaction energy of two rigid macro-molecular bodies as a sum of correlation functions and then evaluate the putative interactions on a grid. The improved shape-based pairwise scoring function was used. The score for a ligand grid was based on the contribution from its nearest receptor grids and from the other receptor grids, with an angle interval of 15 degrees for rotational sampling, using a spacing of 1.2 Å in this FFT-based method.

The ranked binding modes were clustered with a root-mean-square deviation (RMSD) cut off of 5 Desmond system builder solvated the complexes into a cubic box filled with water, simulated by TIP3P model [38, 46] . OPLS force field [47] was used for MD calculations. OPLS-aa (all atom) J o u r n a l P r e -p r o o f included every atom explicitly with specific functional groups and types of molecules, including several bio-macromolecules [36, 38, 48, 49] . Na + and Cl − ions were added to provide a final salt concentration of 0.15 M to simulate physiological concentration of monovalent ions. Constant temperature (300 K) and pressure (1.01325 bar) was employed with the NPT (constant number of particles, pressure and temperature) as an ensemble class. RESPA integrator [50] was used for integrating the equations of motion, with an inner time step of 2.0 fs for bonded and non-bonded interactions within the short-range cutoff. Nose-Hoover thermostats [51] were employed for keeping a constant simulation temperature, and the Martyna-Tobias-Klein method [52] was used to control the pressure. Long-range electrostatic interactions were calculated by particle-mesh

Ewald method (PME) [53] . The cutoff for van der Waals and short-range electrostatic interactions was set at 9.0 Å. The equilibration of the system was performed using the default protocol provided in Desmond, which consisted of a series of restrained minimization and MD simulations used to slowly relax the system. Consequently, one individual trajectory for each complex of 100 ns was calculated. The trajectory files were analyzed using the tools implemented in the Desmond package. The same application was used to generate all plots concerning MD simulations performed in this study. Accordingly, the RMSD was calculated using the following equation:

Viruses are incapable of self-maintenance and self-replication [54] . Rapid globalization in the 21 st century has simultaneously forced pathogens to also adapt to new environments. Aggressive environmental threats have also left, humans more exposed to wildlife (e.g. bat), compounding the chances of viral infections. Indeed, severe deforestation and other environmental pressures have increased threats to humans. Furthermore, even among concurrent strains, the evolution of host immune responses induced selective pressure, resulting in unbalanced survival abilities.

These have broadened the field of "phylodynamics" research [55, 56] .

Phylogenetic and sequence alignment analyses were conducted to explore the relationships between the selected taxa. Longer the branch length corresponds with greater mutations acquired by the organism. In all cases, a close relationship between the bat coronavirus RaTG13 and SARS-CoV-2 was observed. A similar relationship was also found by various researchers, leading to the conclusion that SARS-CoV-2 is genetically similar to RaTG13 (isolated from bat in Yunnan in 2013) [57, 58] . Based on the whole-length phylogenetic tree of the polyprotein ORF1ab, SARS-CoV-2 was observed to be homologous to the coronavirus RaTG13 in bats. The branch length of the coronavirus RaTG13 is slightly longer than that of SARS-CoV-2; however, for other phylogenetic trees, the branches of RaTG13 coronavirus and SARS-CoV-2 were reversed ( Figure 1A -C). These findings support the conclusion that slightly more mutations were acquired in RaTG13 coronavirus in bats than in SARS-CoV-2 over the length of ORF1ab polyprotein.

The output of multiple sequence analysis showed the differences in amino acids at 12 diverse J o u r n a l P r e -p r o o f

The current study aimed to identify the interacting sites of RdRp or its complex with viral RNA, as well as the behavior of RdRp in presence of antiviral drugs. To achieve this goal, we conducted multiple molecular docking studies with SARS-CoV-2-nsp12. The activity of SARS-CoV-2-nsp12 polymerase is stimulated by nsp7 and nsp8. To mimic the in vivo situation, molecular docking calculations were performed to investigate the RdRp activity of SARS-CoV-2-nsp12 using a complex containing nsp7 and nsp8 in a hexadecameric arrangement. Our findings revealed that the RNA has a higher affinity for the nsp7 and nsp8 complexes than for SARS-CoV-2-nsp12 within the SARS-CoV-2-nsp7-8-12 complex. According to previous reports, nsp7 participates in the polymerase activity, and nsp8 has a non-canonical RdRp activity [59, 60] . These findings imply that nsp7 and nsp8 in this complex must contain an RNA binding domain. The ribonucleotides (NTPs) entrance channel within the nsp12 (formed by the basic residues such as Lys545, Arg553, and Arg555 from Motif F), facilitate the entry of incoming NTPs [61] . After the initial binding of the template or parental RNA with nsp7, the RNA is expected to mediate its entry into the active site of the nsp12 polymerase domain (formed by

Motifs A and C) and form a new RNA strand [22] . Furthermore, the nsp7/nsp8 complex interacts with nsp12, targeting the following residues located in the polymerase domain: Thr409, Lys411, Trp509, Gly510, Arg513, Gly897, and Met899. Additionally, Asn104 and Asn136 of nsp8 (from the hexadecameric structure nsp7/nsp8) form two hydrogen bonds with nsp12 targeting Trp509 and Thr409 (Figure 3 and Figure S4 , Table 1 ).

For improving the reliability of the docking calculation, we investigated the dynamics of the system by performing a MD simulation study. The nsp12 was subjected to a simulation of 100 ns to better understand the behavior of interacting residues. The outcome of this computational investigation ( Figure S4 ) highlighted a general stability of the system indicated by calculating RMSD and RMSF (also visible in Figure 2 ). Furthermore, 100 ns of simulation of the system did not alter the interface exposure, and the identified interacting residues (Table 1) can still interact with nsp7 and nsp8 since no relevant conformational changes were observed in this interacting domain. This event is confirmed by a further docking calculation achieving the assembly of the nsp12 with nsp7 and nsp8. The calculation output using the structure of nsp12 after 100 ns as a starting point, is comparable to that reported in Figure 2B with only minor changes in interaction J o u r n a l P r e -p r o o f sites ( Figure S4 ). The main residues of nsp12, driving the recognition between the latter and its cofactors, were confirmed to establish the main contacts with nsp7 and nsp8. We observed only few additional contacts stabilizing the binding mode. Indeed, Lys411 is involved in a H-bond with Asp134 (nsp8), while Thr409 can establish an additional H-bond with Asn140 (nsp8).

Finally, we observed that Lys508 can further stabilize the contacts of the loop by interacting with Asp99 (nsp8) ( Figure S4 ).

Therefore, the nsp7/nsp8 complex might also occupy the nsp12 polymerase domain, making H-bind the viral RNA before the inclusion of drug molecules ( Table 2) . When we analysed the interaction between nsp12 and viral RNA after the incorporation of drug molecules with the nsp12 prior to viral RNA binding, interacting amino acids were altered;

although the binding affinity between nsp12 and the viral RNA was not significantly altered.

Another striking observation is that, while different drugs interact with different amino acid J o u r n a l P r e -p r o o f residues of nsp12 (Supplementary Table 1) , with few exceptions, nsp12 interacts with the template RNA through identical residues (Asp499, Tyr521, Ser814, Ser861, and Tyr903).A further interacting residue (Gln492) was observed for nsp12 complexed with Ribavirin. In contrast, Setrobuvir interacted with nsp12 by establishing hydrogen bonds targeting Tyr38, Asp40, Ser78, Asn79, Gly220, Asn722, and Asn734 (Table 1) . As a result, it is possible to conclude that the drug Setrobuvir had not effect on the interaction of nsp12 and viral RNA. This means that it can no longer be considered a potential viral RdRp inhibitor. In contrast, when

Sofosbuvir was added to nsp12 prior to RNA binding, the total number of amino acids involved in the interaction with viral RNA decreased. Based on these observations, it is possible to conclude that, Sofosbuvir can effectively act as a potential RdRp inhibitor.

Subsequent molecular docking calculation was performed on nsp12 bound with its cofactors nsp7 and nsp8, in hexadecameric structure. The goal of this docking study was to identify the amino acid residues of the nsp12-7-8 hexadecameric complex that interact with viral RNA. We observed that, rather than binding with nsp12, the template RNA established three H-bonds with the basic residues Arg21 and Lys27 of nsp7. Alternatively, the template RNA formed hydrogen bonds with the basic amino acid arginine located at positions 75 and 80 of nsp8 (Table 3) .

J o u r n a l P r e -p r o o f It has also been observed that the nsp7-8 cofactors provide some level of protection to nsp12, preventing drugs from gaining access to viral RdRp. Although some of the interacting sites of nsp7-8-12 hexadecameric structure could be altered after the inclusion of the selected drugs into nsp12 (Figures 5 and 6 ) and before its binding with the cofactors, the viral RNA could still bind nsp7-8 cofactors. An exception is represented by the nsp12 complexed with Sofosbuvir prior to the binding with the nsp7-8 cofactors. After the inclusion of Sofosbuvir into nsp12, which is then complexed with nsp7-8 in a hexadecameric structure, the total number of hydrogen bondforming amino acids was reduced. Furthermore, rather than the nsp7-8 cofactors, the template RNA interacts with the acidic residue Asp499, aromatic residue Tyr521 and Tyr903, and with the polar uncharged residue Ser814 of nsp12. Sofosbuvir is also more effective in this instance, as the total number of interacting amino acids reduces and the interaction sites become drastically altered.

J o u r n a l P r e -p r o o f In order to mimic the in vivo situation, we performed a series of molecular docking calculations with the nsp12-7-8 hexadecameric complex and each chosen drug. This calculation was useful to determine whether the hexadecameric complex residues responsible for viral RNA interactions had changed after the inclusion of the selected drugs. The viral RNA mostly maintained the interactions with nsp7/nsp8 cofactors of the nsp12-7-8 complex as detected considering the nsp12-7-8 complex and template RNA in the absence of drugs (Table 4 ). 

The target protein showed reasonably stable structure lacking any major expansion/contraction, after the binding of these ligands throughout the simulation period. In Figures S5-S12 are reported details about the main contacts and the type of interaction found for each selected drug.

Regarding IDX_184 (Figure S5 ), the main contacts (Table S2) found by docking, were maintained (Thr817, Leu819, Tyr831, and His872), although we observed that the interaction with Tyr877 was lost and became sporadic. The IDX_184 could stabilize its binding by establishing relevant contact with Gly808 and His810. Remdesivir ( Figure S6 ) maintained the main contacts (Lys50, Asn52, Cys54, and Asp218) except the interaction with Arg116 replaced with polar contacts with Lys74. Analyzing the output of Galidesivir ( Figure S7 ), we observed additional contacts (Arg33, Lys50, and Thr51) with respect to those found by docking calculation (Asn52, Arg116, Lys121, Thr217, and Asp218). Ribavirin was found to maintain all the contacts identified in docking studies during the simulation (Ser343, Asn356, Asn360, Glu370, Val373, Tyr374, Asp377, and Tyr530), although the interaction with Val373 became infrequent ( Figure S8 ). The drug Setrobuvir maintained contacts with Ser835 and Tyr877 during MD experiment, and additionally we observed contacts with Lys807, although mainly watermediated ( Figure S9 ). Regarding the drug Sofosbuvir by observing the trajectory of MD simulation in addition to the identified contacts (Asn911, Arg914, Tyr915, and Glu919, the latter became mainly water-mediated), we detect additional polar contacts with Glu919 ( Figure S10 ).

Tenofovir maintained proficient interactions with Thr120 and Thr123, while the contact with Asp208 became sporadic. We observed two relevant additional contacts with Lys50 and Lys73

( Figure S11 ). Finally, YAK established a contact with Ala34 that became mainly water-mediated during the simulation. Two additional contacts were observed with Arg33 and Asp208 ( Figure   S12 ). In summary, MD simulation studies confirmed the possible binding mode identified for the selected drugs by molecular docking calculation, with only small differences.

Finally, we docked the viral RNA with the selected drug molecules to observe if any of these drugs could bind more tightly to the template RNA strand than that the nsp12-7-8 complex. We organisms have glutamic acid. Interestingly, both amino acids belonging to the same group of amino acids (acidic and charged). Because these interacting sites are highly conserved, they can be used to design effective drugs or drug-like molecules in the future. A similar conserved nature of the interacting sites has also been recently described [64] . 

These systematic studies demonstrate that SARS-CoV-2 RdRp is more mutable than homologous sequences and evolutionarily close to the bat coronavirus RaTG13, but the sites responsible for the interaction with the cofactor nsp7-8 or with the viral RNA are occupied by identical amino acids. The interactions between RdRp and viral RNA were altered after the drug molecules were incorporated into nsp12, due to the changes in the positions and physicochemical properties of the interacting amino acids of nsp12. Among the selected existing antiviral drugs, Sofosbuvir was found to be most effective in altering the physico-chemical nature of the interacting amino acids as well as their positions within the RdRp prior to RNA binding. However, when the nsp12 forms a hexadecameric complex with its cofactors, nsp7 and nsp8, none of the drugs affected the physico-chemical nature of the amino acids responsible for interacting with viral RNA or their locations within the nsp12-7-8 complex. Consequently, the selected drugs were unable to bind to the same amino acids of nsp12 when alone. The polymerization activity of the RdRp in SARS-CoV-2 was not hampered, primarily due to the role of cofactors that support the activity of the complex. These findings indicate that special attention must be given to the design of far-reaching drug molecules to nsp12-7-8 hexadecameric structure. Notably, the nucleotide (adenine) analog Remdesivir was more capable to bind with the viral RNA's uracil-rich region than RdRp or to its complex, and thus could prevent RNA chain elongation.

As a result, developing inhibitors that act specifically to reduce viral RNA binding affinity for nsp12 should be prioritized in developing effective antiviral agents against SARS-CoV-2.

Furthermore, specific drug molecules with the ability to target residues of the nsp7-8 complex involved in the interaction with nsp12 can be designed to preclude the correct formation of the hexadecameric complex, and thus, reduce the efficiency of RdRp. We have found that Asn69 of nsp7 interacts with Gly897 of nsp12, Cys72 of nsp7 interacts with Gly510 of nsp12, and Glu73 of nsp7 interacts with Arg513 of nsp12. Also, Arg96, Arg111, Asn136, and Met174 of nsp8 interact with Trp509, Leu900, Lys411, and Thr409 of nsp12, respectively, during the formation of the nsp12-7-8 complex. Moreover, two hydrogen bonds were detected between Asn104, and Asn136 of nsp8 and Trp509, and Thr409 of nsp12, respectively. Therefore, blocking these sites of the nsp7/nsp8 complex by specific drug molecules design could change the binding affinity of the nsp7/nsp8 complex to nsp12. Furthermore, drug design targeting the specific sites of the Compliance with Ethical Standards: This article does not contain any studies with animals.

There is no conflict of interest.

Funding statement: No funding has been received for this work by any author.

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The authors acknowledge the combined efforts of all scientists in world-wide who are working