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. 2021 Sep 13;17(9):e1009384. doi: 10.1371/journal.pcbi.1009384

Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2

Abhisek Dwivedy 1,#, Richard Mariadasse 2,#, Mohammed Ahmad 1,#, Sayan Chakraborty 1,#, Deepsikha Kar 1,#, Satish Tiwari 1, Sankar Bhattacharyya 3, Sudipta Sonar 3, Shailendra Mani 3, Prafullakumar Tailor 1, Tanmay Majumdar 1,*, Jeyaraman Jeyakanthan 2,*, Bichitra Kumar Biswal 1,*
Editor: Avner Schlessinger4
PMCID: PMC8478224  PMID: 34516563

Abstract

Apart from the canonical fingers, palm and thumb domains, the RNA dependent RNA polymerases (RdRp) from the viral order Nidovirales possess two additional domains. Of these, the function of the Nidovirus RdRp associated nucleotidyl transferase domain (NiRAN) remains unanswered. The elucidation of the 3D structure of RdRp from the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), provided the first ever insights into the domain organisation and possible functional characteristics of the NiRAN domain. Using in silico tools, we predict that the NiRAN domain assumes a kinase or phosphotransferase like fold and binds nucleoside triphosphates at its proposed active site. Additionally, using molecular docking we have predicted the binding of three widely used kinase inhibitors and five well characterized anti-microbial compounds at the NiRAN domain active site along with their drug-likeliness. For the first time ever, using basic biochemical tools, this study shows the presence of a kinase like activity exhibited by the SARS-CoV-2 RdRp. Interestingly, a well-known kinase inhibitor- Sorafenib showed a significant inhibition and dampened viral load in SARS-CoV-2 infected cells. In line with the current global COVID-19 pandemic urgency and the emergence of newer strains with significantly higher infectivity, this study provides a new anti-SARS-CoV-2 drug target and potential lead compounds for drug repurposing against SARS-CoV-2.

Author summary

The on-going coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is significantly affecting the world health. Unfortunately, over 180 million cases of COVID-19 resulting in nearly 4 million deaths have been reported till June, 2021. In this study, using a combination of bioinformatics, biochemical and mass spectrometry methods, we show that the Nidovirus RdRp associated Nucleotidyl transferase (NiRAN) domain of the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 exhibits a kinase like activity. Additionally, we also show that few broad spectrum anti-cancer and anti-microbial drugs dampen this kinase like activity. Of note, Sorafenib, an FDA approved anti-cancer kinase inhibiting drug significantly reduces the SARS-CoV-2 load in cell lines. Our study suggests that NiRAN domain of the SARS-CoV-2 RdRp is indispensible for the successful viral life cycle and shows that abolishing this enzymatic function of RdRp by small molecule inhibitors may open novel avenues for COVID-19 therapeutics.

Introduction

RNA dependent RNA polymerases (RdRp) are conserved across all RNA virus superfamilies harbouring a positive or negative sense RNA genome with the exception of retroviruses. RdRp catalyses the replication of RNA genomes from an RNA template, thus playing a key role in the viral life cycle and pathogenesis [1]. The structure of RdRp is broadly divided into three domains- fingers, palm and thumb, the shape resembling that of a right hand. This structural organization is conserved not only in RNA viruses, but also in the DNA polymerases across all kingdoms of life [1, 2]. However, the positive-stranded RNA (+RNA) viruses from the order Nidovirales present a conspicuous difference in the structural organization of their RdRp molecules [24]. The viruses in the order Nidovirales are known to infect a broad spectrum of hosts. While members of the families Arteriviridae and Coronaviridae infect vertebrates, members of Mesoniviridae and Roniviridae primarily infect invertebrates [24]. Despite a significant difference in the sizes of their genomes which ranges from 13 kb to 35 kb, the RdRp molecules encoded by each genome show a common structural organization [2].

Apart from the basic RdRp structural organisation comprised of the canonical palm, thumb and finger domains, the Nidovirus RdRp possesses two additional domains- the Nidovirus RdRp associated nucleotidyl transferase domain (NiRAN) and the interface domain [26]. The interface domain primarily serves as a connector between the NiRAN and canonical RdRp regions. However information on the functional aspects of the NiRAN domain remains limited. The first ever study that defines the NiRAN domain from the RdRp/Nsp9 of equine arteritis virus (EAV), demonstrates a manganese-dependent covalent binding of guanosine phosphate and uridine phosphate to an invariant lysine residue from the NiRAN domain [3]. The study proposes three possible molecular functions of the NiRAN domain: as a ligase, as a GTP dependent 5’ nucleotidyl transferase and as a UTP dependent protein priming function facilitating the initiation of RNA replication [2, 3]. Various studies from other RNA viruses have demonstrated the nucleotidyl transferase activities exhibited by the N-terminal regions of the respective RdRp molecules [79]. However these transferase activities have been attributed to both 5’-priming as well as terminal ribonucleotide addition functions. Moreover, RdRp enzymes are known to exhibit either a primer dependent or a primer independent initiation of RNA replication [1, 10]. Interestingly, nidovirus RdRp molecules have been experimentally demonstrated to possess both modes of initiation, thus hinting at a probable UTP mediated priming function of the NiRAN domain [11, 12].

An earlier cryo-EM structure of replicase polyprotein complex from SARS-CoV (PDB ID- 6NUR) had a significant portion of the NiRAN domain missing, thus failed to provide any functional association to this domain [5]. However, a recent study reporting the cryo-EM structure of the replicase polyprotein complex from SARS-CoV-2 (PDB ID- 7BTF, 6M71) provides the complete structural preview of the NiRAN domain [6]. Together, these studies suggest that the interface domain also serves as the binding partner for Nsp8 protein of the polyprotein complex. COVID-19, the disease caused by the nidovirus SARS-CoV-2 is an on-going global crisis that necessitates the exploration of viral protein functions in addition to the exploration for novel anti-coronavirus inhibitor scaffolds [1315]. In addition, the recent emergence of newer SARS-CoV-2 strains with significantly higher contagion [16] further necessitates the discovery of novel anti-viral targets and small molecule inhibitors targeting the life cycle and metabolism of the virus. In this study, utilizing a combination of in silico and biochemical tools, we propose that the NiRAN domain of SARS-CoV-2 possess a kinase like fold and is possibly involved in the catalysis of a kinase/phosphotransferase reaction. Moreover, we show that a number of previously known kinase and nucleotidyl transferase inhibitors dampen the activity of the NiRAN domain and of these; Sorafenib displayed anti-SARS-CoV-2 activity.

Results

Analysis of the NiRAN and Interface domains

As described in a recent study [6], the NiRAN and the interface domains span over residues 1–365 of the SARS-CoV-2 RdRp polypeptide sequence. These two domains form an arrow head like structure, which acts as a base for the RdRp region of protein (Fig 1A). Of these, amino acids 4–28 and 69–249 have been designated as the NiRAN domain that comprises of 7 α-helices (H1-H7) and 5-β strands (S1-S5), respectively. Two independent β-strands (B1, B2) form a hairpin like structure (residues 29–68) in the vicinity of NiRAN domain and are not considered integral to the NiRAN domain. The interface domain stretches from residue 250 to residue 365 and is comprised of a 6 α-helix bundle (h1-h6) followed by 3 antiparallel β strands (s1-s3). The overall topology suggests that the two distinct domains are connected by a small linker of 1 residue (Fig 1B). As proposed in the EAV- NiRAN study, several key residues such as K94, R124, S129, D132, D165 and F166 [3], were found conserved in the SARS-CoV-2-NiRAN as revealed in a pairwise alignment of the two sequences. The corresponding residues from SARS-CoV-2-NiRAN are K73, R116, T123, D126, D218 and F219. These residues have been predicted to be crucial for the enzymatic function of the NiRAN domain. A multiple sequence alignment of 17 RdRp polypeptide sequences from coronaviruses across multiple host species (human, bat, cow, pigs and rodents) revealed an absolute conservation of these residues (S1 Fig). Including the aforementioned residues, a total of 84 residues (45 in NiRAN and 39 in interface domains) were found strictly conserved in the RdRp molecules across all 17 viruses, hinting at a key role of these residues in the enzymatic and/or functional properties of NiRAN and Interface domains. A visualization of the conserved residues of the NiRAN domain shows that a significant majority of these residues are localized between the four stranded β-sheet and the following helix bundle (Fig 1B). A surface potential representation of the regions reveals the presence of five potential entry pockets suggesting that the active site of the NiRAN domain is possibly flanked by these conserved residues (S2A Fig). The 39 residues conserved in the interface domain are however spread all over the domain architecture (S2B Fig). The conservation of the residues across species suggests an important role of the NiRAN domain in RdRp mediated RNA replication in coronavirus, as suggested by the previous study on EAV-RdRp [3].

Fig 1. The CoV-2-RdRp NiRAN domain presents a kinase/phosphotransferase like structural organisation.

Fig 1

(A) The NiRAN and the interface domains of the CoV-2-RdRp present an arrow head like structure (helices in royal blue, strands in peach and loops in green). (B) The overall topology of the NiRAN (brown background, helices as marked as H and strands are marked as S) and interface domain (grey background, helices as marked as h and strands are marked as s) along with β-hairpin structure (brick red background, strands are marked as B). (C) The NiRAN domain possess a topology (left panel) that borrows elements from the canonical kinase fold (centre panel) as well as the non-canonical kinase fold of TgBPK1 (right panel). (D-I) The structural superimpositions of the secondary structural elements of CoV-2-RdRp NiRAN with known kinases reveal significant alignment in the antiparallel β-sheet and in the helices that follow. (D) Lim 2 kinase domain. (E) Syk kinase domain (F) O-mannosyl kinase domain. (G) IRAK4 kinase domain. (H) FGFR2 kinase domain. (I) Insulin receptor kinase domain (The aforementioned kinases’ structural elements are shown in cyan, CoV-2-RdRp NiRAN structural elements shown in yellow).

Prediction of the plausible functions of the NiRAN domain

The understanding of the overall topology, localization of the conserved residues prompted an investigation on understanding the enzymatic function of the NiRAN domain. For this, two different approaches were considered with the Protein Data Bank as the target database. The first approach utilized the prediction of Hidden Markov Models (HHPred) [17] while the second approach predicted the presence of similar folds (ORION) [18]. The list of the top 15 hits retrieved for the first and second approaches are listed in S1 and S2 Tables, respectively. Notably, both approaches predicted a variety of kinase and kinase like transferase (phosphotransferase molecules). A previous report had evidenced at the similarity of the NiRAN domain to that of a known pseudokinase molecule SelO [5]; however further characterization was not feasible due to absence of the NiRAN 3D structure. We compared the topologies of the NiRAN domain with that of the canonical kinase fold. Similar to the canonical kinase fold, the NiRAN domain comprises an antiparallel β-sheet flanked by alpha helices. The canonical kinase domain exhibits a 5 stranded antiparallel β-sheet, which is flanked by two helices running parallel and one helix running perpendicular to the β-sheet (Fig 1C, middle panel) [19, 20]. However, the NiRAN domain shows a 4 stranded antiparallel β-sheet (S1-S4) flanked by one parallel (H2) and two perpendicular helices (H1 and H3) (Fig 1C, left panel). Further investigation into the available literature confirmed the presence of many non-canonical kinase folds, one of which presents a 4 stranded antiparallel β-sheet flanked by three parallel and one perpendicular helix (Fig 1C, right panel) [21]. Taken together, these results suggest that the NiRAN domain assumes a kinase like fold, possibly functioning either as a pseudokinase or a phosphotransferase.

To further investigate this proposition, a structural alignment of the NiRAN domain was performed against 8 randomly selected kinase molecules retrieved by the HHPred and ORION searches. The molecules Lim 2 kinase domain (PDB ID- 5NXD) (Figs 1D and S3A and S4A), Syk kinase domain (PDB ID- 4YJR) (Figs 1E and S3B and S4B), O-mannosyl kinase domain (PDB ID- 5GZ9) (Figs 1F and S3C and S4C) and IRAK4 kinase domain (PDB ID- 2NRU) (Figs 1G and S3D and S4D) aligned with the NiRAN domain with rmsd (root mean square deviation) values ranging from 0.6–4 Å and with alignment scores ≥ 0.5, suggesting that the kinase domains in these molecules share nearly similar fold with the NiRAN domain. As a proof of principle, two additional kinase molecules not listed in the aforementioned search results- FGFR2 kinase domain (PDB ID- 2PVF) (Figs 1H and S3E and S4E); and Insulin receptor kinase domain (PDB ID- 1GAG) (Figs 1I and S3F and S4F) were aligned with the NiRAN domain. Both these molecules displayed rmsd values ranging from 0.22–4 Å and alignment score of ~0.5, further highlighting the possible presence of a kinase like fold in the NiRAN domain. The results clearly exhibited the alignment of both the Cα backbone of the two molecules and the conservation of secondary structural elements. Of note, the alignments of the helix H2, helix H6, helix H8 and the antiparallel β-sheet (S1-S4) are strikingly evident. Of note, the previously mentioned pseudokinase molecule SelO (PDB ID- 6EAC) also aligned with the NiRAN domain. With rmsd values ranging from 2–8 Å and an alignment score of 0.42, the alignment suggests that though both the molecules roughly assume similar folds, the amino acid conservation differs significantly. Collectively, results of the alignments further highlight the presence of a non-canonical kinase/phosphotransferase like fold within the NiRAN domain.

Predicting the NiRAN domain active site

The earlier study with EAV-RdRp experimentally demonstrated the binding of GTP and UTP nucleotides to the NiRAN domain [3]. A docking analysis of these nucleotides within the NiRAN domain was performed to delineate the probable active site. Kinase domains in general possess an active site between the antiparallel β- sheet and the subsequent helix bundle [19, 22, 23]. ATP (Fig 2A and 2A’), GTP (Fig 2B and 2B’) and UTP (Fig 2C and 2C’) docked well within the probable active site region with binding energies of -8.726 kcal/mol, -9.84 kcal/mol and -6.59 kcal/mol, respectively. Besides, end-point binding free energy calculation with MMGBSA (Molecular Mechanics Generalized Born Surface Area) suggested a strong interaction between the nucleotides and the residues in the probable active site (-17.84, -15.77 and -17.67 kcal/mol for ATP, GTP and UTP, respectively). Examination of the molecular interactions suggests that the ATP forms both salt bridges and H-bonding with key NiRAN residues such as K73 and D208. GTP formed possible H-bonding with R116 and salt bridge interaction with K73. The UTP however only displayed a salt bridge interaction with K73. Using the above interactions and the critically conserved residues, we computationally predicted the active site of NiRAN domain. The predicted active site pocket is lined with the following residues: F35, D36, I37, Y38, N39, F48, L49, K50, T51, N52, R55, V71, K73, R74, H75, N79, E83, R116, L119, T120, K121, Y122, T123, V204, T206, D208, N209, Y217, D218, G220, D221, F222 and S236; the underlined residues being strictly conserved across coronavirus RdRp molecules. K73 has been predicted as one of the key residues in the NiRAN active site. The corresponding lysine from the EAV-RdRp (K94) has been deemed critical to the function of NiRAN domain, owing to its interactions with GTP and UTP. The study also demonstrated that mutating lysine to alanine results in complete loss of RdRp function [3]. An overview of the active site pocket depicting the electrostatic surface potential indicates the localization of charged residues at the entry points to the site, while the interior of the pocket remains lined with largely non polar residues (S2C Fig).

Fig 2. The active site of CoV-2-RdRp NiRAN domain binds ATP, GTP and UTP and exhibits kinase like motifs.

Fig 2

ATP, GTP and UTP bind at the probable active site of the NiRAN domain with notably low free binding energies. (A) ATP within the active site pocket. (B) GTP within the active site pocket. (C) UTP within the active site pocket (Blue indicates positively charged regions, red indicates negatively charged regions and green indicates neutral regions, grey indicates regions beyond GTP-binding pocket). (A’) ATP forms salt bridge with K73 and H-bonding with D208. (B’) GTP binding reveals salt bridge interaction with K73 and H-bonding with Asp 116. (C’) UTP binding exhibits salt bridge interaction with K73.

With the above results suggesting a kinase like fold and the active site showing possible GTP and UTP binding function, a motif search was performed using the complete sequence of the NiRAN, β-hairpin and interface domains. The results predicted the presence of kinase like motifs belonging to Protein kinase C family, Protein kinase A family and Src Kinase family [24]. Few sequences motifs belonging to unspecified kinase families were also predicted. Interestingly, no kinase like motif was predicted for the interface domain and the β-hairpin region. Of note, a myristoylation consensus sequence overlapping with an unspecified kinase consensus was also predicted. Host enzymes are known to interact with viral proteins inducing post translational modifications following host or virus mediated signals. In particular, host kinases are known to post translationally modify viral protein often resulting in enhanced virulence or induction of various metabolic pathways [2527]. A kinase site prediction suggested six different kinase phosphorylation sites with specificity for the eIF2 kinase family. A sequence based visualization of these motifs is presented in S5A Fig. These predictions hint at possible post translational modifications of viral proteins, mediated by the interplay of host–SARS-CoV-2, possibly aimed at regulating the host and viral metabolism.

In order to further explore the kinase like catalytic nature of NiRAN domain, three broad specificity kinase inhibitors- Sunitinib, Sorafenib and SU6656 were randomly selected and docked into the predicted active site of the NiRAN domain. All three kinase inhibitors show strong binding at the predicted active site as evident from the low free energy of binding (Fig 3A–3C and S3 Table). Interestingly, these inhibitors also demonstrate potential H-bond with residues lining the active site. While Sunitinib and Sorafenib primarily interact with aspartate residues, SU6656 exhibits H-bond interaction with lysine residue 73 (Fig 3A’, 3B’ and 3C’), which is the critical lysine residue predicted to be involved in NiRAN domain’s catalytic activity, as mentioned earlier. As a negative control the inactive analogs of two kinase inhibitors (Daidzein/PubChem ID- 5281708 and Geinstein/PubChem ID- 5280961) were docked into the putative NiRAN domain active site [28]. These compounds showed docking scores and binding energies lower than those of Sorafenib, Sunitinib and SU6656 (S5B and S5C Fig). In a nutshell, the above predictions further suggest that the NiRAN domain of coronavirus RdRp has a kinase/phosphotransferase like catalytic activity.

Fig 3. The active site of CoV-2-RdRp NiRAN domain binds kinase inhibitors.

Fig 3

(A, C and E) Broad specificity kinase inhibitors bind within the predicted NiRAN active site with significantly low free binding energies. (Blue indicates positively charged regions, red indicates negatively charged regions and green indicates neutral regions, grey indicates regions beyond GTP-binding pocket): (A) Sunitinib within the active site pocket; (B) Sorafenib within the active site pocket; and (C) SU6656 within the active site pocket. The kinases inhibitors demonstrate H-bond interactions between with the enzymatically critical aspartate and lysine residues lining the active site- (A’) Sunitinib; (B’) Sorafenib; and (C’) SU6656.

Prediction of inhibitors targeting the NiRAN domain active site

As mentioned earlier, this domain might be involved in GTP induced protein phosphorylation, thus enabling a primer independent RNA replication (G-capping) [3]. Also, the domain may be involved in phosphorylation of UTP, thus functioning as a terminal nucleotidyl transferase. A wide range of viruses, both with DNA and RNA genomes are known to possess either multifunctional or dedicated proteins exhibiting the aforementioned activities [7, 29]. Interestingly, many pathogenic bacteria also encode for proteins that possess G-capping and/or terminal nucleotidyl transferase activities [30, 31]. Years of research have also presented a plethora of inhibitor molecules that target these essential functions in pathogens that cause diseases in human and non-human mammals [29]. After careful examination, a list of 77 compounds with experimentally demonstrated inhibitory potential against members of Flaviviridae, Togaviridae; Human cytomegalovirus, Herpes simplex virus, and few gram negative bacterial species were selected for docking against the CoV-2-RdRp NiRAN domain active site [29, 3238]. The list of the selected compounds is presented in S4 Table.

Further, this study will discuss the best five inhibitors based on the docking analysis performed on the aforementioned 77 compounds. The five inhibitors with the best docking scores in a decreasing order are- 65482, 122108, 135659024, 4534, and 23673624 (numbers represent the PubChem IDs). The results of the docking analysis are presented in S5 Table. All these five inhibitors occupy varying regions within the active site pocket in a manner that their aromatic rings align with the uncharged/non-polar regions, while the charged moieties fit in the extremities of the active site pocket (Fig 4A–4E). All the five inhibitors exhibit H-bonding interactions with the active site residues. Interestingly all the five inhibitors present potential salt bridges with active site residues and also exhibit interactions with enzymatically critical residue K73, either via H-bonding or salt bridges. In addition to the above interactions, Compound 65482 also exhibits the pi-pi interactions between its own purine ring and residues F35 and F48, as is evident from its best docking score. The molecular interactions of these inhibitors with the CoV-2-RdRp NiRAN domain active site are presented in Fig 4A’, 4B’, 4C’, 4D’ and 4E’. In order to estimate the drug-likeliness of the aforementioned inhibitors, an ADME/T analysis was performed. The ADME/T analysis failed to provide any results for the compound 135659024. The ADME/T properties of the other four molecules were within the acceptable range in terms of Lipinski’s rule of five [39] and related pharmacokinetic criteria such as H-bonding atoms probability, human oral absorption and the IC50 values for blockage of human Ether-a-go-go-Related Gene (hERG) K+. The results of this analysis are listed in S6 Table.

Fig 4. The binding and molecular interactions of the best five predicted nucleotidyl transferase inhibitors at the active site of CoV-2-RdRp NiRAN.

Fig 4

The computationally directed binding of- (A) 65482; (B) 122108; (C) 135659024; (D) 4534; and (E) 23673624; within the active site pocket. (Blue indicates positively charged regions, red indicates negatively charged regions and green indicates neutral regions, grey indicates regions beyond GTP-binding pocket). The molecular interactions between the inhibitors and the active site pocket reveal H-bonds, salt bridges and pi-pi interactions- (A’) 65482; (B’) 122108; (C’) 135659024; (D’) 4534; (E’) 23673624. Of note, the best predicted inhibitor- 65482 presents all the aforementioned molecular interactions.

The NiRAN domain of SARS-CoV-2 RdRp exhibits a kinase/phosphotransferase like activity

In order to determine any putative kinase like activity being harboured by the CoV-2 RdRp, the protein was overexpressed, purified (S6A and S6B Fig) and its identity was confirmed by mass spectrometry (S6C Fig and S7 Table). The absence of any known kinase/phosphotransferase substrate for CoV2-RdRp posed a different challenge. Most kinases are specific and rarely phosphorylate other targets [40]. In addition, in the absence of any substrate, kinases have been shown to exhibit a residual intrinsic ATPase/GTPase like activity [4144]. Here, the enzyme enzymatically cleaves the nucleoside triphosphate molecule and transfers the gamma phosphoryl group to a water molecule in the microenvironment [44]. Also, majority of the known kinase inhibitors bind to the ATP binding site, thus abrogating the reaction [45]. An ADP-Glo Kinase assay kit [46] was utilized to determine the kinase activity of the CoV-2 RdRp. The efficiency of the assay in accurately determining a kinase activity was verified using a known kinase–human Akt2. The enzyme exhibited significant activity with a Km value of ~300 μM for ATP (Fig 5A), which is very similar to the Km values (~ 350 μM) determined in previously reported studies [47]. Also, Bovine Serum Albumin, a protein that binds ATP [48] exhibited negligible activity (Fig 5A), further verifying the specificity and selectivity of the protocol. Notably, incubation of the CoV-2 RdRp with varying concentrations of ATP exhibited significant activity akin to that of the human Akt2, with a Km of ~500 μM (Fig 5A). To further ascertain that the observed kinase/phosphotransferase like activity is primarily exhibited by the NiRAN domain, mutant proteins were generated where two key residues of the proposed NiRAN active site (K73 and D218) were mutated to alanines. A notable decline in the Vmax values of K73A and D218A mutants was observed (Fig 5A). However a double mutant for the key aspartate dyad of the RdRp replicase active site (D760 and D761 [49]) showed activity similar to that of the wild type enzyme (Fig 5A). Fluorescence spectrometry suggested that these mutations had no effects on the 3D structural integrity of the enzyme, suggesting that the loss of activity observed in K73A and D218A mutants are largely due to their role in the kinase/phosphotransferase type activity (S6D Fig). Together, these results present the first ever evidence of an intrinsic kinase/phosphotransferase like activity exhibited by the NiRAN domain of an RdRp molecule from coronaviruses.

Fig 5. SARS-CoV-2 RdRp exhibits a kinase/phosphotransferase like activity.

Fig 5

(A) The CoV-2 RdRp exhibits a kinase like activity akin to that of purified human Akt2. While mutations in the probable NiRAN active site (K73A, D218A) cause decline in the kinase like catalytic activity of the SARS-CoV-2 RdRp, mutating the RdRp replication active site (D760A+D761A) has negligible effect on the same. The ATP binding protein Bovine Serum albumin serves as a negative control (Data points show mean and standard error. The connecting curves represent non-linear regressions). (B) MS-MS spectra profile for peptide KSLVSKGTLVQTK from Histone H1 treated with SARS-CoV-2 RdRp in presence of ATP and Mg2+ shows the phosphorylation at two serine residues. (C) MS-MS spectra profile for the same peptide from Histone H1 treated with human Akt2 in presence of ATP and Mg2+ shows the phosphorylation at a single threonine residue. (D) MS-MS spectra profile for the aforementioned peptide from Histone H1 treated with SARS-CoV-2 RdRp in the presence of only Mg2+ shows no phosphorylation, confirming the phosphotransferase activity of SARS-CoV-2 RdRp NiRAN domain (Further details are presented in S7 and S8 Figs and S8 Table).

To assess the efficiency of a phosphor-transfer reaction, dephosphorylated human histone H1 was treated with SARS-CoV-2 RdRp under appropriate conditions with appropriate controls. Mass spectrometry analysis of the trypsin digested histone H1 detected the presence of a phosphorylated peptide: 85- KS*LVS*KGTLVQTK-97 (phosphorylated at S86 and S89) following treatment with SARS-CoV-2 RdRp in presence of ATP and Mg2+ (Figs 5B and S7A and S8A and S8 Table). Concurrently, the analysis of the histone H1 tryptic peptides detected the presence the same peptide phosphorylated at T92: 85- KSLVSKGT*LVQTK-97; following treatment with human Akt2 in the presence of ATP and Mg2+ (Figs 5C and S7B and S8B and S8 Table). However, the same peptide from Histone H1 treated with RdRp or Akt2 in the absence of ATP; Histone H1 treated with ATP and Mg2+ in the absence of RdRp or Akt2; and Histone H1 treated with only ATP and Mg2+ had no phosphorylation in any of the serine and threonine residues (Figs 5D and S7C and S8C and S8 Table). These observations further suggest that the NiRAN domain of the SARS-CoV-2 RdRp has a serine-threonine like kinase activity.

Inhibiting the NiRAN domain reduces viral load in ACE2 expressing cell lines

To further ascertain the possible kinase like activity of CoV-2 RdRp, both CoV-2 RdRp and human Akt2 were incubated with excess of ATP and treated with 500 nM of the each of the three kinase inhibitors mentioned in this study- Sorafenib, Sunitinib and SU6656. Interestingly, all the three kinases inhibitors significantly abrogated the kinase like activity of CoV-2 RdRp (Fig 6A). For human Akt2, Sorafenib and SU6656 significantly inhibited its kinase activity, while Sunitinib treatment demonstrated a mild inhibition (Fig 6A). This provides a key insight into drug re-purposing for COVID-19, as all the three aforementioned compounds are well approved drugs for human usage with high tolerance and without any significant toxicity. As the NiRAN domain of CoV-2 RdRp has been annotated as nucleotidyl transferase, we sought to determine any inhibitory efficacy of the top five compounds predicted through in silico approaches. We were unable to procure the compound 23673624 commercially, thus we used the four remaining compounds- 135659024, 122108, 65482 and 4534. We observed very little effects of the first three compounds on the kinase like activity of CoV-2 RdRp at a concentration of 500 nM (Fig 6B). However, these compounds which are nucleoside analogs/derivatives exhibited conspicuous inhibitions at a concentration of 1000 nM (Fig 5C). The fourth compound 4534, a catechol derivative failed to inhibit the CoV-2 RdRp kinase like activity at any of the two concentrations (Fig 6B). This suggests that the three inhibitory compounds might be involved in blocking the binding of ATP to its respective binding site, in a manner similar to the specific kinase inhibitors.

Fig 6. Impeding the activity of the SARS-CoV-2 RdRp NiRAN domain reduces viral load in infected cells.

Fig 6

(A) While treatment with all the kinase inhibitors abrogate the kinase like activity of CoV-2 RdRp, the activity human Akt2 is majorly inhibited by Sorafenib and SU6656 with Sunitinib only exhibiting mild inhibition. (B) Treatment of CoV2-RdRp with nucleotidyl transferase inhibitors 135659024, 122108 and 65482 exhibit conspicuous inhibition of the kinase activity in micromolar concentrations. The compound 4534 however fails to exhibit any inhibitory potential. (C) 5 μM Sorafenib effectively reduces viral replication in SARS-CoV-2 infected Vero E6 cells. In addition, a combination of Sorafenib with 1 μM Remdesivir completely neutralizes SARS-CoV-2 as evident by a Ct value similar to that of uninfected cells (The bars represent mean and standard error. The symbols “*” and “**” represent significance for p-value less than 0.05 and 0.005, respectively. The symbol “ns” represents non-significance).

In order to determine if inhibiting the activity of the NiRAN domain has any significant effect on the viral cycle of SARS-CoV-2, Vero E6 cells infected with SARS-CoV-2 were treated with the three broad spectrum kinase inhibitors at varying concentrations. Sunitinib and SU6656 failed to control the viral multiplication at the experimental concentrations. However, Sorafenib impeded the viral replication at concentration of above 2 μM, with efficiency similar to that of the known anti-viral drug, Remdesivir (at 1 μM) (Fig 6C). We observed an inhibition of viral growth at 5 μM of Sorafenib which is the minimum concentration of the drug that exhibited the maximum anti-viral efficacy. Sorafenib with 25 μM and 50 μM also encumbered viral multiplication, although there were no significant difference in viral load amongst the 5 μM, 25 μM and 50 μM concentration of the drug.

These results demonstrate that Sorafenib impedes the activity of NiRAN domain and thus hinders viral replication. Previous studies have shown that remdesivir abrogates the canonical replicase activity of RdRp [50, 51]. Notably, both palm and NiRAN domains amino acid sequences are highly conserved among various variants of concerns identified for SARS-CoV-2 [52, 53]. We hypothesized that a combinatorial therapy of remdesivir and sorafenib may show synergistic effect to abolish the dual enzymatic activities of RdRp. Furthermore, a combinational treatment of 5 μM Sorafenib and 1 μM Remdesivir shows a synergetic effect in neutralizing the virus (Fig 6C). Notably, Vero E6 cells exhibited no apoptosis when treated with Sorafenib at concentrations of 50, 25 and 5 μM and Remdesivir at concentrations of 25, 5 and 1 μM. These results suggest that Sorafenib alone or in combination with Remdesivir can prove effectively in clearing SARS-CoV-2 infections.

Discussion

SARS-CoV-2, the causative agent of the on-going global pandemic COVID-19, is a recently emerged pathogen that has infected over 180 million and caused over 4 million deaths as of 29th June, 2021 [54]. With a basic reproduction number ranging from 1.4 to 3.9, the disease has quickly disseminated across the globe within the past year [55]. The situation demands urgent attention from researchers worldwide in order to develop a better understanding of the viral pathogenesis, clinical presentations and biology of the disease in order to develop therapeutics such as vaccines and small molecule inhibitors targeting the viral proteins. Prevalent hypotheses suggest that multiple genome level recombination and zoonotic events between coronaviruses affecting human and bat host have resulted in the evolution of SARS-CoV-2 [15]. However it is worth noticing that the RdRp molecule of SARS-CoV-2 remains largely unchanged at the protein sequence level when compared to previous human coronaviruses such as SARS-CoV, MERS-CoV, SARS-Hku1 as well as non-human coronaviruses like Bat-CoV-Hku4 and Bat-CoV-ZC45, to name a few [56].

Despite being a well-known pathogen, following the SARS-CoV outbreak in 2002, the functional aspects of the RdRp molecule from coronaviruses remains unclear [5, 6, 11]. In addition, even less information is available on the peculiar NiRAN and interface domains that are specific to the RdRp molecules of viruses of the order Nidovirales [2, 3]. In this study, we propose that the NiRAN domain harbors an atypical kinase/phosphotransferase like fold, with nucleoside triphosphate binding activity. The binding of the wide specificity kinase inhibitors at the predicted active site, further suggest the possible enzymatic action of the NiRAN domain. Interestingly, a recent report has suggested the possibility of kinase inhibitors in management of COVID-19 [57]. In line with the previous study on EAV-RdRp, this study delineates the possible catalytic residues at the NiRAN active site- F35, D36, F48, K73, R116, D218 and D221. In addition, the results also suggest that NiRAN domain of SARS-CoV-2 RdRp demonstrates a putative kinase/phosphotransferase like activity comparable to that of a well-established human kinase- Akt-1.

Using computational docking and simulation, this study predicts possible inhibitor compounds against the NiRAN domain. Interestingly, the aforementioned kinase like activity of the RdRp is significantly inhibited in the presence of these inhibitors in nanomolar concentrations. The compound Sunitinib is an inhibitor of the tyrosine family kinases [58]; Sorafenib inhibits activities of both serine/threonine and tyrosine family kinases [59, 60]; while SU6656 inhibits the Src family kinases [60, 61]. While Sorafenib and Sunitinib are approved for medical use in cases of renal, hepatocellular and gastro-intestinal cancers, the compound SU6656 is an experimental molecule used to study the role of Src kinases in cell cycle [61, 62]. In addition to the kinase inhibitors, the compound 65482 (Sinefungin), is broad specificity microbial nucleotidyl transferase inhibitor, and is known to inhibit RNA replication in flaviviruses and herpes viruses [63, 64]. The compound 122108 (Ribavirin 5’-triphosphate), inhibits the formation of g-capping of RNA in a wide range of viruses, such as Dengue virus, Hantaan virus and Hepatitis C virus [8, 65, 66]. Officially known as m7GTP, the compound with the PubChem Id 135659024, interferes with the RNA/DNA g-capping activity in many viral pathogens such as Rift valley fever virus, influenza virus, Zika virus and dengue virus, to name a few [6769]. Given the unavailability of SARS-CoV-2 specific therapies and the emergence of newer strains [16], drug repurposing might prove crucial in combating the on-going epidemic while simultaneously being cost and time effective. This study examined the anti-SARS-CoV-2 activity of a well-studied drug, Sorafenib, which may prove effective in containing the diseases in moderate and severe cases of COVID-19. Other recent studies have hinted at the versatile nature of the NiRAN domain. Its catalytic functions include the NMPylation of nsp9 resulting in the formation of the replication transcription complex, essential for the viral replication [70]. Notably this NMPylation activity is specifically observed in the presence of Mn2+, whereas the kinase/phosphotransferase activity presented in our study in observed only in the presence of Mg2+ ions. In addition, another study has shown the role of NiRAN domain in formation of a cap core structure [71]. In addition, the NiRAN domains of the RdRp molecules from the various variants of SARS-CoV-2, including the variants of concern, exhibit high degree of conservation, especially in the putative active site residues such as K73 and D218 [52, 53]. Together our report and these recent studies hint at the indispensible nature of RdRp NiRAN domain for a successful viral replication in Nidoviruses, thus it is pertinent to explore in vivo anti-viral efficacies of compounds targeting the NiRAN catalytic functions.

Materials and methods

Ethics statement

All the experimental procedures were performed a minimum of three times with independently acquired proteins and cells lines. All experimental protocols were approved by the Institutional Bio-Safety Committees: IBSC#388/20 (approved for BKB by the National Institute of Immunology, India); IBSC#298/2021 (approved for SM by Translational Health Science and Technology Institute, India); and No.BT/Bs/17/458/2011-PID (approved for SM by Review Committee on Genetic Manipulation, Department of Biotechnology, India).

Characterization of NiRAN and Interface domains of CoV-2-RdRp

The coordinates of the 3D structure of SARS-CoV-2-RdRp were retrieved from the Protein Data Bank (PDB IDs- 7BTF and 6M71) [6]. The dataset 7BTF was used for subsequent analysis as it provided information on all amino acid residues of CoV-2-RdRp. The coordinate data within the file was trimmed to amino acids 1–365 (sequence for NiRAN and Interface domains). This file was used for computational characterization of NiRAN and Interface domains. For sequence analysis, all the coronavirus RdRp sequences were retrieved from the NCBI database and subjected to multiple sequence alignment using the Clustal Omega [72] and Multalin [73] servers. The sequences alignment visualization was generated using the ESPript 3.0 web-tool [74]. Functional analyses were performed using the MPI Bioinformatics Toolkit [17], the DALI server [75] and the DSIMB server [18, 76]. The coordinate files for the kinases were retrieved from the Protein Data Bank (PDB IDs- 1CSN, 1GAG, 2NRU, 2PVF, 3Q60 and 6EAC) for structural alignment with the NiRAN and Interface domains of CoV-2-RdRp. The alignments were performed using the flexible “jFATCAT” algorithm in the Java application “strucalign” available at the Protein Data Bank [77]. The default alignments parameters were used (RMSD cut off- 3 Å, AFP distance cut off- 5, Maximum number of twists- 5, and Fragment length- 8). All visualization were performed in Pymol [78]. Motif prediction and kinase functional prediction were performed using the web servers- ELM [79], PSIPRED [80], CDD [81], MyHits [82], and PhosphoPredict [83].

In silico ligand preparation, active site pocket prediction and molecular docking

The coordinate files for all the inhibitors were retrieved from the PubChem Database and/or from Protein Data Bank. All the inhibitors were prepared by assigning appropriate geometries, bond orders, tautomers and ionization states using LigPrep module implemented in the “Schrodinger Suite 2019” [84]. The coordinate file for the NiRAN and Interface domains was used to predict the probable ligand binding pockets using the SiteMap module of the “Schrodinger Suite 2019”. The accuracy of the sites were verified using the Phyre [85] and CASTp servers [86] and the results were compared. These sites were used to generate a Grid for molecular docking of the inhibitors. The prepared inhibitors were docked onto the predicted binding sites using Glide XP (extra Precision) module of the “Schrodinger Suite 2019”.

MMGBSA Calculation

The free energies of binding for the inhibitor-domain complexes (NiRAN and Interface domains with inhibitors) were analysed by MMGBSA (Molecular Mechanics Generalized Born Surface Area) calculation [87]. The calculation was executed using the following equation:

G=ΔEMM+ΔGSGB+ΔGSA

(ΔEMM represents the minimized molecular energy changes in gas phase; GSGB represents the surface calculation using the GB model; and GSA represents the accessible surface area of the complexes) [88, 89].

The molecular docking and MMGBSA calculation protocols were validated by comparing with the available co-crystal structure of Zika Virus methyl-transferase bound to the nucleotidyl-transferase inhibitor Sinefungin (PDB ID- 5MRK).

ADME/T properties prediction

The top 5 inhibitors with the highest docking scores and minimum binding energies were analysed for their pharmacokinetic properties such ADME (Absorption, Distribution, Metabolism, Elimination or Toxicity) and drug likeliness [90, 91]. The QikProp module of the “Schrodinger Suite 2019” was utilized to evaluate the drug likeliness by employing the Lipinski’s rule of five [39] and various pharmacokinetic properties such as probable Hydrogen bonding atoms; Human Oral Absorption (<25%: poor; >above 80%: good); QP LogS (Predicted aqueous solubility of the compounds, acceptable range is -6.0 to -0.5) and the IC50 values for blockage of the human Ether-a-go-go-Related Gene (hERG) K+ channels (< -5: satisfactory)[92].

SARS-CoV-2 RdRp native and mutant proteins generation

The ORF encoding for the SARS-CoV-2 RdRp was PCR amplified using gene specific primers (mentioned at the end of this section) and using the plasmid pDONR223 SARS-CoV-2 NSP12 as the template DNA (Addgene, USA). Codons encoding for a deca-histidine tag was incorporated into the forward primer in order to obtain the recombinant protein with an N-terminal deca-histidine tag. An entry cloning site (CACC), a recognition site for the restriction endonuclease NdeI (CATATG) and a start codon were also incorporated into the forward primer. The reverse primer included a stop codon and the recognition site for the restriction endonuclease HindIII (AAGCTT). The primers used are listed at the end of this paragraph. The PCR amplified product was ligated into the entry vector pENTR-D-TOPO using appropriate protocol (Qiagen, USA). The ligated product was transformed into chemically competent Escherichia coli strain DH5α and grown on LB agar medium containing 50 μg/ml kanamycin for selection at 310 K. Positive colonies were screened using colony PCR and recombinant plasmid pENTR-D-TOPO-RdRp was extracted by plasmid mini prep using appropriate protocol. The isolated plasmid was subjected to restriction digestion with the enzymes NdeI and HindIII using appropriate protocol (New England Biolabs, UK). The expression vector pET-28b (+) was linearized by restriction digestion with enzymes NdeI and HindIII. The digested fragment containing the ORF for RdRp and the linearized expression vector were ligated by T4 DNA ligase employing the appropriate protocol (Qiagen, USA). The ligated product was transformed into chemically competent Escherichia coli strain DH5α and grown on LB agar medium containing 50 μg/ml kanamycin for selection at 310 K. Positive colonies were screened using colony PCR and recombinant plasmid pET-28b-RdRp was extracted by plasmid mini prep using appropriate protocol. The plasmids were verified by restriction digestion with enzymes NdeI and HindIII and by DNA sequencing (BioServe, India). Single codon substitustions for K73A and D218A and double codon substitution for D760A+D761A were performed using a nested PCR based site directed mutagenesis protocol described earlier [93] using appropriate primers (mentioned at the end of this section). The mutant plasmids were confirmed by DNA sequencing (BioServe, India). The plasmids pET-28b-RdRp (native and mutants) were then into transformed into chemically competent Escherichia coli strain BL21-DE3 and grown on LB agar medium containing 50 μg/ml kanamycin for selection at 310 K.

A single colony was picked from the agar medium and inoculated into LB liquid medium containing 50 μg/ml kanamycin and grown at 310 K. Large scale liquid cultures were further inoculated from the aforementioned culture and were grown at 310 K. These cultures were induced with 0.5 mM of IPTG at an A600 of 0.8. The cultures were maintained for 3 hours post induction at a temperature of 301 K. The cells were harvested by centrifugation of the cultures at 10000 g and were re-suspended in the lysis buffer (50 mM Tris, 500 mM NaCl, 30 mM Imidazole, 2.5 mM DTT, 10% glycerol, PIC 1 tablet, 10 mM PMSF, 0.1% Nadeoxycholate, 0.3 mg/ml lysozyme at pH 8.0). The cells were lysed using a CF Cell Disruptor (Constant Systems, UK). The lysate was centrifuged at 12000 g for one hour and the supernatant was utilized for protein purification. The protein was purified using the fast performance liquid chromatography system AKTA Pure (GE Healthcare, USA). The protein was purified using an affinity chromatography (HisTrap-FF column; GE Healthcare, USA), followed by a size exclusion chromatography (HiLoad 16/600 Superdex 200 PG column, GE Healthcare, USA). In affinity chromatography the recombinant protein was eluted in the aforementioned buffer containing 300 mM imidazole (gradient 1 to 500 mM). In ion exchange chromatography the protein eluted in the aforementioned buffer containing an additional 210 mM NaCl (gradient 1 to 1000 mM). In size exclusion chromatography, the protein eluted at a flow volume of ~65 ml. The complete purification process was maintained at a temperature of 277 K. The purity of the recombinant protein was analysed on SDS-PAGE and the identity of the protein was confirmed using liquid chromatography- tandem mass spectrometry (Ultra-High Resolution Nano LC-MS/MS using C18 column and Q Exactive Orbitrap Mass Spectrometer, ThermoScientific, USA) at a commercial facility (VProteomics, New Delhi, India). The purified protein was concentrated to 1 mg/ml using a 50 kDa membrane centrifugal unit (Millipore, USA) and stored for further use. The native and the mutant RdRp proteins were over-expressed and purified using the same aforementioned protocol. Fluorescence spectra of the native and mutant RdRp proteins were acquired at 30°C using a Fluorescence Spectrophotometer (Horiba Fluromax4, Japan) with an excitation wavelength of 280 nm, and the emission spectra of protein samples were recorded from 300 to 400 nm. All the spectra were corrected for buffer absorption and the proteins were diluted to a concentration of 5 μM.

Primers
Native RdRp
Forward Primer 5’-CACCCATATGAUGCACCATCACCATCACCATCACCACCCAA
CTTTGTACAAAAAAGTT-3’
Reverse Primer 5’-TATAAGCTTTTACTGCAGCACGGTGTGAGGGGTGTA-3’
RdRp K73A mutant
Forward Primer 5’- ATCCTGTCTGCCGCCGCGGTGGTG-3’
Reverse Primer 5’- CACCACCGCGGCGGCAGACAGGAT -3’
RdRp D218A mutant
Forward Primer 5’- TTCGTGGTGGCGAGGCACACC-3’
Reverse Primer 5’- GGTGTGCCTCGCCACCACGAA -3’
RdRp D760A+D761A double mutant
Forward Primer 5’- AACTGGTACGCCTTCGGAGA -3’
Reverse Primer 5’- GTCTCCGAAGGCGTACCAGTT -3’

Biochemical Assays of SARS-CoV-2 RdRp native and mutant proteins

The ADP-Glo Kinase Assay system (Promega, USA) was utilized for all biochemical analysis using purified recombinant RdRp [46]. The enzyme concentration used for all biochemical assays was 100 nM. The buffer used for biochemical assay contained 20 mM Tris-Cl, 300 mM NaCl, 7.5 mM MgCl2, 5 mM 2-mercaptoethanol and 10% v/v glycerol. Varying concentration of ATP (250, 500, 750 and 1000 μM) were utilized to determine the enzymatic activity of the recombinant RdRp at 310 K. The readouts were measured at 0, 5, 20, 35 and 50 minutes post initiation of the reaction using a luminometer (Berthold Technologies, Germany). The same protocol was utilized for the biochemical assays of mutants K73A, D218A and D760A+D761A. Purified Human Akt2 (Sigma Aldrich, USA) at 100 nM and Bovine Serum Albumin at 100 μM (HiMedia, India) concentrations were used as positive and negative controls for Kinase activity, respectively.

The kinase inhibitors Sorafenib, Sunitinib and SU6656 (Sigma Aldrich, USA) were dissolved in 100% v/v DMSO (Sigma Aldrich, USA) and used at a concentration of 500 nM. The predicted nucleotidyl transferase inhibitors 135659024, 122108, 65482 and 4534 (Sigma Aldrich, USA) were dissolved in 100% v/v DMSO and used at two different concentrations- 500 and 1000 nM. For all inhibition studies, the ATP concentration was maintained at 100 mM. The graphs were plotted using GraphPad Prism 7.0. Non-linear regressions of the enzymatic activities were performed for obtaining the Michaelis-Menten kinetics. Statistical significance for the inhibitory potential of the compounds was determined using student’s t-test.

Mass Spectrometry analysis of the Kinase/Phosphotransferase activity of SARS-CoV-2 RdRp NiRAN domain

De-phosphorylated Histone H1 (Sigma Aldrich, USA) was treated with different combinations of SARS-CoV-2 RdRp or human Akt2, 1000 μM ATP and 7.5 mM MgCl2; in a buffer containing 20 mM Tris-CL, 300 mM NaCl, 5 mM 2-mercaptoethanol and 10% v/v glycerol. The six reaction mixtures were set up: (1) Histone H1 + RdRp + ATP + Mg2+; (2) Histone H1 + Akt2 + ATP + Mg2+; (3) Histone H1 + BSA + ATP + Mg2+; (4) Histone H1 + RdRp + Mg2+; (5) Histone H1 + Akt2 + Mg2+; and (6) Histone H1 + ATP + Mg2+. The samples were incubated at 310 K for 1 h and the proteins were separated on SDS-PAGE. The subsequent protocols were carried out at commercial facility (VProteomics, New Delhi). Briefly, the bands of interest, corresponding to the size of Histone H1 were excised from the gel and were treated 4 mM of Tris(2-carboxyethyl)phosphine (Sigma Aldrich, USA) 8 mM iodoacetamide (Sigma Aldrich, USA). In-gel digestion was performed with uHPLC grade trypsin (Sigma Aldrich, USA) in 50 mM ammonium bicarbonate (Sigma Aldrich, USA) at 310 K for 12 h. Digests were cleaned using a C18 silica cartridge to remove the salt and dried using a speed vac. The dried pellet was resuspended in 5% acetonitrile (Sigma Aldrich, USA) and 0.1% formic acid (Sigma Aldrich, USA). Liquid chromatography tandem mass spectrometry was performed on an Ultimate 3000 RSLCnano system coupled with a Thermo Q-Exactive Plus. 1ug of sample was loaded on a C18- 50 cm, 3.0μm Easy-spray column (Thermo Fisher Scientific). Peptides were eluted with a 0–40% gradient of 80% acetonitrile, 0.1% formic acid; at a flow rate 5 nls-1 and injected for MS analysis. LC gradient was run for 100 minutes. The mass spectrometer was driven in data-dependent acquisition mode using the Thermo Xcalibur 2.1 software for a full spectrum scan ranging from 150-1200m/z. MS1 spectra were acquired in the Orbitrap at 70k resolution. Dynamic exclusion was employed for 10 s excluding all charge states for a given precursor. MS2 spectra were acquired at 17500 resolutions. The data was analysed using the Proteome Discoverer 2.2 software and the spectra were searched against the NCBI protein database using the SEQUEST search engine [94]. The precursor and fragment mass tolerances were set at 10 ppm and 0.02 Da, respectively. The protease used to generate peptides, i.e. enzyme specificity was set for trypsin/P (cleavage at the C terminus of “K/R: unless followed by “P”) along with a maximum missed cleavages value of two. Carbamidomethylation on cysteine was considered as fixed modification while oxidation of methionine and phosphorylation on serine, threonine and tyrosine were considered as variable modifications for database search. Peptide spectrum match and protein false discovery rate were set to 0.01 FDR.

Determination of the efficacy of inhibitor(s) in curbing ex vivo SARS-CoV-2 infection

Vero E6 cells, considered ideal for SARS-CoV-2 infection [95], were maintained in DMEM supplemented with 10% FBS. The cells were infected with SARS-CoV-2 (Isolate USA-WA1/2020) in a biosafety containment level 3 facility. Post infection, cells were washed with phosphate buffer saline and maintained in DMEM supplemented with 2% FBS. Post 1 h infection at 400 TCID50 in 24 well plate, cells were washed with serum free media and added 500 μl of DMEM supplemented with 2% FBS containing the varying concentrations and combinations of Sorafenib, Sunitinib, SU6656 and Remdesivir in respective wells. 48 h post infection, the supernatants were collected and a quantitative RT-PCR was performed using primers of nucleocapsid gene of SARS-CoV-2 based on CDC guidelines [96]. Uninfected cells and untreated infected cells were used as negative and positive controls, respectively. The Ct values were utilized as a marker for viral replication. Statistical significance was determined using student’s t-test.

Supporting information

S1 Fig. A multiple protein sequence alignment of NiRAN and interface domains from the RdRp molecules of coronaviruses affect various vertebrate hosts.

(TIF)

S2 Fig. Organization and conservation of the NiRAN Domain.

(A) Organization of the entry pockets at CoV-2-RdRp NiRAN domain lined with the strictly conserved residues. (B) While the conserved residues in the interface domain are scattered across the structural elements, the majority of the conserved residues in NiRAN domain lie between the antiparallel β-sheet and the immediately following helix bundle, possibly hinting at the NiRAN domain active site. (C) The predicted active site of the NiRAN domain possess both charged and uncharged residues, where in the charged residues primarily line the entry points of the pocket and the uncharged residues line in the deeper sections (Blue indicates positively charged regions, red indicates negatively charged regions and green indicates neutral regions, grey indicates regions beyond GTP-binding pocket).

(TIF)

S3 Fig. Pairwise alignments corresponding to the alignment of the structural elements of CoV-2-RdRp NiRAN with known Kinases.

(A) Lim 2 kinase domain. (B) Syk kinase domain (C) O-mannosyl kinase domain. (D) IRAK4 kinase domain. (E) FGFR2 kinase domain. (F) Insulin receptor kinase domain. (Colour codes- Block 1: orange-cyan; Block 2: yellow-turquoise; Block 3: lime- deep blue; Block 4: green- deep blue; Block 5: green- purple).

(TIF)

S4 Fig. The structural superimposition of the Cα chains of CoV-2-RdRp NiRAN with known Kinases reveal significant alignment of the polypeptide chains.

(A) Lim 2 kinase domain. (B) Syk kinase domain (C) O-mannosyl kinase domain. (D) IRAK4 kinase domain. (E) FGFR2 kinase domain. (F) Insulin receptor kinase domain. (The aforementioned kinases’ Cα chains are shown in cyan, CoV-2-RdRp NiRAN Cα chains are shown in yellow.)

(TIF)

S5 Fig. The prediction of kinase like motifs reveals the presence of sequence motifs belonging to kinase families PkA, PkC and Src.

(A) Kinase consensus site search prediction also predicts multiple phosphorylation sites. (Bold- NiRAN domain; Italics- Interface domain; Underlines: Red- Kinase consensus sequence, Blue- PkC like motif, purple- PkA like motif, Green- Src kinase like motif, Grey- Unspecified Kinase like motifs, Yellow- Myristoylation site consensus sequence). (B) An inactive analog of Daidzein docked into the NiRAN domain putative active site. (C) An inactive analog of Geinstein docked into the NiRAN domain putative active site.

(TIF)

S6 Fig. Purification of SARS-CoV2-RdRp.

A) Size exclusion chromatogram of recombinant SARS-CoV-2 RdRp (The peak indicated with a blue arrow represents the purified protein sample). (B) SDS-PAGE profile of the purified SARS-CoV-2 RdRp (The band indicated with a blue arrow represents the purified protein sample and the molecular weight markers are indicated in red arrows). (C) Fluorescence spectra for native and mutant SARS-CoV-2 RdRp suggest that the incorporated mutations have negligible effect on the protein structural integrity.

(TIF)

S7 Fig. MS-MS Spectra for the peptide KSLVSKGTLVQTK from Histone H1.

(A) Histone H1 treated with SARS-CoV-2 RdRp in presence of ATP and Mg2+. (B) Histone H1 treated with human Akt2 in presence of ATP and Mg2+. (C) Histone H1 treated with SARS-CoV-2 RdRp in the presence of Mg2+ only (The b and y ions are shown in red and blue, respectively).

(TIF)

S8 Fig. Ion series detected in MS-MS for the peptide KSLVSKGTLVQTK from Histone H1.

(A) Histone H1 treated with SARS-CoV-2 RdRp in presence of ATP and Mg2+. (B) Histone H1 treated with human Akt2 in presence of ATP and Mg2+. (C) Histone H1 treated with SARS-CoV-2 RdRp in the presence of Mg2+ only.

(TIF)

S1 Table. Top 15 molecules with structurally similar fold(s) predicted by HHPred analysis.

(XLSX)

S2 Table. Top 15 molecules with structurally similar fold(s) predicted by ORION_DSIMB analysis.

(XLSX)

S3 Table. Docking analysis of kinase inhibitors at the proposed active site of NiRAN domain.

(XLSX)

S4 Table. The complete list of compounds selected for docking at the predicted active site of CoV-2-RdRp NiRAN domain.

(XLSX)

S5 Table. Docking analysis of best 5 proposed inhibitors at the proposed active site of NiRAN domain.

(XLSX)

S6 Table. The predicted ADME/T properties of best 5 proposed inhibitors.

(XLSX)

S7 Table. LC-MS/MS verification of the SARS-CoV-2 RdRp.

(XLSX)

S8 Table. Phosphorylated peptide fragment of protein Histone H1 (K88-K100) detected by mass spectrometry.

(XLSX)

S1 Data. Raw data points for the graphs presented in Figs 5A, 6A, 6B and 6C; and the raw reads for the real-time PCR analysis.

(XLSX)

Acknowledgments

JJ gratefully acknowledges MHRD-RUSA 2.0 [F.24/51/2014-U, Policy (TNMulti-Gen), Dept. of Edn., Govt. of India] for the infrastructure facilities provided to the Department of Bioinformatics, Alagappa University. The following reagent was deposited by the Centers for Disease Control and Prevention and obtained through BEI Resources, NIAID, NIH: SARS-Related Coronavirus 2, Isolate USA-WA1/2020, NR-52281. We thank Dr. Subeer S. Majumdar for his encouragement and support.

Data Availability

The raw data points for the graphs presented in Figs 5A, 6A, 6B and 6C; and the raw reads for the real-time PCR analysis are provided in the S1 Data file. The mass spectrometry raw data files are submitted to the OSF repository at- “https://osf.io/rt6aw/?view_only=815070ca377a4a6cb4aac2e56990152e”. The results for the multiple sequence alignment, structural alignment, structural fold searches and small molecule dockings are submitted to the OSF repository at- “https://osf.io/bvcq2/?view_only=1a002bc15cf94bb884df06bc7d7601bc”.

Funding Statement

BKB was supported by the core funding from the National Institute of Immunology, Department of Biotechnology, New Delhi, India. JJ gratefully acknowledges Tamil Nadu State Council for Higher Education (File. No. RGP/2019-20/ALU/HECP-0049) for the financial support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Venkataraman S, Prasad BVLS, Selvarajan R. RNA dependent RNA polymerases: Insights from structure, function and evolution. Viruses. 2018. doi: 10.3390/v10020076 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Posthuma CC, te Velthuis AJW, Snijder EJ. Nidovirus RNA polymerases: Complex enzymes handling exceptional RNA genomes. Virus Research. 2017. pp. 58–73. doi: 10.1016/j.virusres.2017.01.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Lehmann KC, Gulyaeva A, Zevenhoven-Dobbe JC, Janssen GMC, Ruben M, Overkleeft HS, et al. Discovery of an essential nucleotidylating activity associated with a newly delineated conserved domain in the RNA polymerase-containing protein of all nidoviruses. Nucleic Acids Res. 2015;43: 8416–8434. doi: 10.1093/nar/gkv838 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Snijder EJ, Decroly E, Ziebuhr J. The Nonstructural Proteins Directing Coronavirus RNA Synthesis and Processing. Advances in Virus Research. 2016. pp. 59–126. doi: 10.1016/bs.aivir.2016.08.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Kirchdoerfer RN, Ward AB. Structure of the SARS-CoV nsp12 polymerase bound to nsp7 and nsp8 co-factors. Nat Commun. 2019;10. doi: 10.1038/s41467-019-10280-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Gao Y, Yan L, Huang Y, Liu F, Zhao Y, Cao L, et al. Structure of the RNA-dependent RNA polymerase from COVID-19 virus. Science. 2020. doi: 10.1126/science.abb7498 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Ranjith-Kumar CT, Gajewski J, Gutshall L, Maley D, Sarisky RT, Kao CC. Terminal Nucleotidyl Transferase Activity of Recombinant Flaviviridae RNA-Dependent RNA Polymerases: Implication for Viral RNA Synthesis. J Virol. 2001;75: 8615–8623. doi: 10.1128/jvi.75.18.8615-8623.2001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Benarroch D, Egloff MP, Mulard L, Guerreiro C, Romette JL, Canard B. A structural basis for the inhibition of the NS5 dengue virus mRNA 2′-O-methyltransferase domain by ribavirin 5′-triphosphate. J Biol Chem. 2004;279: 35638–35643. doi: 10.1074/jbc.M400460200 [DOI] [PubMed] [Google Scholar]
  • 9.Yap TL, Xu T, Chen Y-L, Malet H, Egloff M-P, Canard B, et al. Crystal Structure of the Dengue Virus RNA-Dependent RNA Polymerase Catalytic Domain at 1.85-Angstrom Resolution. J Virol. 2007;81: 4753–4765. doi: 10.1128/JVI.02283-06 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Appleby TC, Perry JK, Murakami E, Barauskas O, Feng J, Cho A, et al. Structural basis for RNA replication by the hepatitis C virus polymerase. Science (80-). 2015;347: 771–775. doi: 10.1126/science.1259210 [DOI] [PubMed] [Google Scholar]
  • 11.Ziebuhr J. The coronavirus replicase. Current Topics in Microbiology and Immunology. 2005. pp. 57–94. doi: 10.1007/3-540-26765-4_3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Ulferts R, Ziebuhr J. Nidovirus ribonucleases: Structures and functions in viral replication. RNA Biology. 2011. doi: 10.4161/rna.8.2.15196 [DOI] [PubMed] [Google Scholar]
  • 13.He F, Deng Y, Li W. Coronavirus Disease 2019 (COVID-19): What we know? J Med Virol. 2020;n/a. doi: 10.1002/jmv.25766 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Sah R, Rodriguez-Morales AJ, Jha R, Chu DKW, Gu H, Peiris M, et al. Complete Genome Sequence of a 2019 Novel Coronavirus (SARS-CoV-2) Strain Isolated in Nepal. Roux S, editor. Microbiol Resour Announc. 2020;9: e00169–20. doi: 10.1128/MRA.00169-20 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Andersen KG, Rambaut A, Lipkin WI, Holmes EC, Garry RF. The proximal origin of SARS-CoV-2. Nat Med. 2020. doi: 10.1038/s41591-020-0820-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Wise J. Covid-19: New coronavirus variant is identified in UK. BMJ. 2020;371: m4857. doi: 10.1136/bmj.m4857 [DOI] [PubMed] [Google Scholar]
  • 17.Zimmermann L, Stephens A, Nam SZ, Rau D, Kübler J, Lozajic M, et al. A Completely Reimplemented MPI Bioinformatics Toolkit with a New HHpred Server at its Core. J Mol Biol. 2018;430: 2237–2243. doi: 10.1016/j.jmb.2017.12.007 [DOI] [PubMed] [Google Scholar]
  • 18.Ghouzam Y, Postic G, Guerin PE, De Brevern AG, Gelly JC. ORION: A web server for protein fold recognition and structure prediction using evolutionary hybrid profiles. Sci Rep. 2016;6. doi: 10.1038/srep28268 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Nolen B, Taylor S, Ghosh G. Regulation of protein kinases: Controlling activity through activation segment conformation. Molecular Cell. 2004. pp. 661–675. doi: 10.1016/j.molcel.2004.08.024 [DOI] [PubMed] [Google Scholar]
  • 20.Modi V, Dunbrack RL. Defining a new nomenclature for the structures of active and inactive kinases. Proc Natl Acad Sci U S A. 2019;116: 6818–6827. doi: 10.1073/pnas.1814279116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Beraki T, Hu X, Broncel M, Young JC, O’Shaughnessy WJ, Borek D, et al. Divergent kinase regulates membrane ultrastructure of the Toxoplasma parasitophorous vacuole. Proc Natl Acad Sci U S A. 2019;116: 6361–6370. doi: 10.1073/pnas.1816161116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Wang Z, Cole PA. Catalytic mechanisms and regulation of protein kinases. Methods in Enzymology. 2014. pp. 1–21. doi: 10.1016/B978-0-12-397918-6.00001-X [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Manning G, Plowman GD, Hunter T, Sudarsanam S. Evolution of protein kinase signaling from yeast to man. Trends in Biochemical Sciences. 2002. pp. 514–520. doi: 10.1016/s0968-0004(02)02179-5 [DOI] [PubMed] [Google Scholar]
  • 24.Hanks SK, Hunter T. The eukaryotic protein kinase superfamily: kinase (catalytic) domain structure and classification 1. FASEB J. 1995;9: 576–596. doi: 10.1096/fasebj.9.8.7768349 [DOI] [PubMed] [Google Scholar]
  • 25.Jacob T, Van den Broeke C, Favoreel HW. Viral Serine/Threonine Protein Kinases. J Virol. 2011;85: 1158–1173. doi: 10.1128/JVI.01369-10 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Garcia MA, Gil J, Ventoso I, Guerra S, Domingo E, Rivas C, et al. Impact of Protein Kinase PKR in Cell Biology: from Antiviral to Antiproliferative Action. Microbiol Mol Biol Rev. 2006;70: 1032–1060. doi: 10.1128/MMBR.00027-06 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Dar AC, Dever TE, Sicheri F. Higher-order substrate recognition of eIF2α by the RNA-dependent protein kinase PKR. Cell. 2005;122: 887–900. doi: 10.1016/j.cell.2005.06.044 [DOI] [PubMed] [Google Scholar]
  • 28.Dubey DK, Chaubey KA, Parveen A, Ojha PR. Comparative study of inhibition of drug potencies of c- Abl human kinase inhibitors: A computational and molecular docking study. J Biophys Struct Biol. 2010;2. [Google Scholar]
  • 29.Decroly E, Canard B. Biochemical principles and inhibitors to interfere with viral capping pathways. Current Opinion in Virology. 2017. pp. 87–96. doi: 10.1016/j.coviro.2017.04.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Fabrega C, Shen V, Shuman S, Lima CD. Structure of an mRNA capping enzyme bound to the phosphorylated carboxy-terminal domain of RNA polymerase II. Mol Cell. 2003;11: 1549–1561. doi: 10.1016/s1097-2765(03)00187-4 [DOI] [PubMed] [Google Scholar]
  • 31.Lasa I, Toledo-Arana A, Dobin A, Villanueva M, De Los Mozos IR, Vergara-Irigaray M, et al. Genome-wide antisense transcription drives mRNA processing in bacteria. Proc Natl Acad Sci U S A. 2011;108: 20172–20177. doi: 10.1073/pnas.1113521108 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Ireland PJ, Tavis JE, D’Erasmo MP, Hirsch DR, Murelli RP, Cadiz MM, et al. Synthetic α-hydroxytropolones inhibit replication of wild-type and acyclovir-resistant Herpes simplex viruses. Antimicrob Agents Chemother. 2016;60: 2140–2149. doi: 10.1128/AAC.02675-15 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Tavis JE, Zoidis G, Meyers MJ, Murelli RP. Chemical Approaches to Inhibiting the Hepatitis B Virus Ribonuclease H. ACS Infect Dis. 2019. doi: 10.1021/acsinfecdis.8b00045 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Edwards TC, Lomonosova E, Patel JA, Li Q, Villa JA, Gupta AK, et al. Inhibition of hepatitis B virus replication by N-hydroxyisoquinolinediones and related polyoxygenated heterocycles. Antiviral Res. 2017;143: 205–217. doi: 10.1016/j.antiviral.2017.04.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Tavis JE, Wang H, Tollefson AE, Ying B, Korom M, Cheng X, et al. Inhibitors of nucleotidyltransferase superfamily enzymes suppress herpes simplex virus replication. Antimicrob Agents Chemother. 2014;58: 7451–7461. doi: 10.1128/AAC.03875-14 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Dehghanpir SD, Birkenheuer CH, Yang K, Murelli RP, Morrison LA, Le Grice SFJ, et al. Broad anti-herpesviral activity of α-hydroxytropolones. Vet Microbiol. 2018;214: 125–131. doi: 10.1016/j.vetmic.2017.12.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Wang Y, Tang J, Wang Z, Geraghty RJ. Metal-chelating 3-hydroxypyrimidine-2,4-diones inhibit human cytomegalovirus pUL89 endonuclease activity and virus replication. Antiviral Res. 2018;152: 10–17. doi: 10.1016/j.antiviral.2018.01.015 [DOI] [PubMed] [Google Scholar]
  • 38.Kim S, Jo S, Kim M-S, Shin DH. A Study of a Potent Inhibitor Against a GDP-6-Deoxy-α-d-Manno-Heptose Biosynthesis Pathway as Antibiotic Candidates. Microb Drug Resist. 2019;26: 385–390. doi: 10.1089/mdr.2019.0144 [DOI] [PubMed] [Google Scholar]
  • 39.Lipinski CA. Lead- and drug-like compounds: The rule-of-five revolution. Drug Discovery Today: Technologies. 2004. pp. 337–341. doi: 10.1016/j.ddtec.2004.11.007 [DOI] [PubMed] [Google Scholar]
  • 40.Kobe B, Kampmann T, Forwood JK, Listwan P, Brinkworth RI. Substrate specificity of protein kinases and computational prediction of substrates. Biochimica et Biophysica Acta—Proteins and Proteomics. 2005. pp. 200–209. doi: 10.1016/j.bbapap.2005.07.036 [DOI] [PubMed] [Google Scholar]
  • 41.Barret JM, Ernould AP, Rouillon MH, Ferry G, Genton A, Boutin JA. Studies of the potency of protein kinase inhibitors on ATPase activities. Chem Biol Interact. 1993;86: 17–27. doi: 10.1016/0009-2797(93)90108-b [DOI] [PubMed] [Google Scholar]
  • 42.Enke DA, Kaldis P, Solomon MJ. Kinetic analysis of the cyclin-dependent kinase-activating kinase (Cak1p) from budding yeast. J Biol Chem. 2000;275: 33267–33271. doi: 10.1074/jbc.M004748200 [DOI] [PubMed] [Google Scholar]
  • 43.Ward NE, ƠBrian CA. The Intrinsic ATPase Activity of Protein Kinase C Is Catalyzed at the Active Site of the Enzyme. Biochemistry. 1992;31: 5905–5911. doi: 10.1021/bi00140a029 [DOI] [PubMed] [Google Scholar]
  • 44.Kashem MA, Nelson RM, Yingling JD, Pullen SS, Prokopowicz AS, Jones JW, et al. Three mechanistically distinct kinase assays compared: Measurement of intrinsic ATPase activity identified the most comprehensive set of ITK inhibitors. J Biomol Screen. 2007;12: 70–83. doi: 10.1177/1087057106296047 [DOI] [PubMed] [Google Scholar]
  • 45.Hanson SM, Georghiou G, Thakur MK, Miller WT, Rest JS, Chodera JD, et al. What Makes a Kinase Promiscuous for Inhibitors? Cell Chem Biol. 2019;26: 390–399.e5. doi: 10.1016/j.chembiol.2018.11.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Zegzouti H, Zdanovskaia M, Hsiao K, Goueli SA. ADP-Glo: A bioluminescent and homogeneous adp monitoring assay for Kinases. Assay Drug Dev Technol. 2009;7: 560–572. doi: 10.1089/adt.2009.0222 [DOI] [PubMed] [Google Scholar]
  • 47.Zhang X, Zhang S, Yamane H, Wahl R, Ali A, Lofgren JA, et al. Kinetic mechanism of AKT/PKB enzyme family. J Biol Chem. 2006;281: 13949–13956. doi: 10.1074/jbc.M601384200 [DOI] [PubMed] [Google Scholar]
  • 48.Bauer M, Baumann J, Trommer WE. ATP binding to bovine serum albumin. FEBS Lett. 1992;313: 288–290. doi: 10.1016/0014-5793(92)81211-4 [DOI] [PubMed] [Google Scholar]
  • 49.Hillen HS, Kokic G, Farnung L, Dienemann C, Tegunov D, Cramer P. Structure of replicating SARS-CoV-2 polymerase. Nature. 2020;584. doi: 10.1038/s41586-020-2368-8 [DOI] [PubMed] [Google Scholar]
  • 50.Zhang L, Zhou R. Structural Basis of the Potential Binding Mechanism of Remdesivir to SARS-CoV-2 RNA-Dependent RNA Polymerase. J Phys Chem B. 2020;124. doi: 10.1021/acs.jpcb.0c04198 [DOI] [PubMed] [Google Scholar]
  • 51.World Health Organization. WHO recommends against the use of remdesivir in COVID-19 patients. WhoInt. 2020. [Google Scholar]
  • 52.Omotoso OE, Babalola AD, Matareek A. Mutational hotspots and conserved domains of SARS-CoV-2 genome in African population. Beni-Suef Univ J Basic Appl Sci. 2021;10. doi: 10.1186/s43088-021-00102-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Pachetti M, Marini B, Benedetti F, Giudici F, Mauro E, Storici P, et al. Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant. J Transl Med. 2020;18. doi: 10.1186/s12967-020-02344-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.World Health Organization. Weekly epidemiological update on COVID-19–29 June 2021. 2021. Available: https://www.who.int/publications/m/item/weekly-epidemiological-update-on-covid-19—29-june-2021
  • 55.Riou J, Althaus CL. Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020. Eurosurveillance. 2020;25: 2000058. doi: 10.2807/1560-7917.ES.2020.25.4.2000058 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Bell Sidney M., Nicola Müller Emma Hodcroft, Wagner Cassia, Hadfield James, Ilcisin Misja, Richard Neher TB. Genomic analysis of COVID-19 spread. Situation report 2020-03-27. 2020. [Google Scholar]
  • 57.Russell B, Moss C, George G, Santaolalla A, Cope A, Papa S, et al. Associations between immune-suppressive and stimulating drugs and novel COVID-19—a systematic review of current evidence. Ecancermedicalscience. 2020;14. doi: 10.3332/ecancer.2020.1022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Atkinson BJ, Kalra S, Wang X, Bathala T, Corn P, Tannir NM, et al. Clinical outcomes for patients with metastatic renal cell carcinoma treated with alternative sunitinib schedules. J Urol. 2014;191: 611–618. doi: 10.1016/j.juro.2013.08.090 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Wilhelm SM, Adnane L, Newell P, Villanueva A, Llovet JM, Lynch M. Preclinical overview of sorafenib, a multikinase inhibitor that targets both Raf and VEGF and PDGF receptor tyrosine kinase signaling. Molecular Cancer Therapeutics. 2008. pp. 3129–3140. doi: 10.1158/1535-7163.MCT-08-0013 [DOI] [PubMed] [Google Scholar]
  • 60.Ross FA, Hawley SA, Auciello FR, Gowans GJ, Atrih A, Lamont DJ, et al. Mechanisms of Paradoxical Activation of AMPK by the Kinase Inhibitors SU6656 and Sorafenib. Cell Chem Biol. 2017;24: 813–824.e4. doi: 10.1016/j.chembiol.2017.05.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Bain J, Plater L, Elliott M, Shpiro N, Hastie CJ, Mclauchlan H, et al. The selectivity of protein kinase inhibitors: A further update. Biochem J. 2007;408: 297–315. doi: 10.1042/BJ20070797 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Blake RA, Broome MA, Liu X, Wu J, Gishizky M, Sun L, et al. SU6656, a Selective Src Family Kinase Inhibitor, Used To Probe Growth Factor Signaling. Mol Cell Biol. 2000;20: 9018–9027. doi: 10.1128/MCB.20.23.9018-9027.2000 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Kuroda Y, Yamagata H, Nemoto M, Inagaki K, Tamura T, Maeda K. Antiviral effect of sinefungin on in vitro growth of feline herpesvirus type 1. J Antibiot (Tokyo). 2019;72: 981–985. doi: 10.1038/s41429-019-0234-4 [DOI] [PubMed] [Google Scholar]
  • 64.Bhattacharya A, Sharma M, Packianathan C, Rosen BP, Leprohon P, Ouellette M. Genomewide Analysis of Mode of Action of the S-Adenosylmethionine Analogue Sinefungin in Leishmania infantum. mSystems. 2019;4. doi: 10.1128/mSystems.00416-19 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Sun Y, Chung DH, Chu YK, Jonsson CB, Parker WB. Activity of ribavirin against Hantaan virus correlates with production of ribavirin-5′-triphosphate, not with inhibition of IMP dehydrogenase. Antimicrob Agents Chemother. 2007;51: 84–88. doi: 10.1128/AAC.00790-06 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Feld JJ, Jacobson IM, Sulkowski MS, Poordad F, Tatsch F, Pawlotsky JM. Ribavirin revisited in the era of direct-acting antiviral therapy for hepatitis C virus infection. Liver International. 2017. pp. 5–18. doi: 10.1111/liv.13212 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Gogrefe N, Reindl S, Günther S, Rosenthal M. Structure of a functional cap-binding domain in rift valley fever virus L protein. PLoS Pathog. 2019;15. doi: 10.1371/journal.ppat.1007829 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Severin C, De Moura TR, Liu Y, Li K, Zheng X, Luo M. The cap-binding site of influenza virus protein PB2 as a drug target. Acta Crystallogr Sect D Struct Biol. 2016;72: 245–253. doi: 10.1107/S2059798316000085 [DOI] [PubMed] [Google Scholar]
  • 69.Chuang CH, Chiou SJ, Cheng TL, Wang YT. A molecular dynamics simulation study decodes the Zika virus NS5 methyltransferase bound to SAH and RNA analogue. Sci Rep. 2018;8. doi: 10.1038/s41598-018-24775-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Slanina H, Madhugiri R, Bylapudi G, Schultheiß K, Karl N, Gulyaeva A, et al. Coronavirus replication-transcription complex: Vital and selective NMPylation of a conserved site in nsp9 by the NiRAN-RdRp subunit. Proc Natl Acad Sci U S A. 2021;118. doi: 10.1073/pnas.2022310118 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.Yan L, Ge J, Zheng L, Zhang Y, Gao Y, Wang T, et al. Cryo-EM Structure of an Extended SARS-CoV-2 Replication and Transcription Complex Reveals an Intermediate State in Cap Synthesis. Cell. 2021;184: 184–193.e10. doi: 10.1016/j.cell.2020.11.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72.Sievers F, Higgins DG. Clustal Omega. Curr Protoc Bioinforma. 2014;2014: 3.13.1–3.13.16. doi: 10.1002/0471250953.bi0313s48 [DOI] [PubMed] [Google Scholar]
  • 73.Mitchell C. Multalin–multiple sequence alignment. Bioinformatics. 1993;9: 614. doi: 10.1093/bioinformatics/9.5.614 [DOI] [Google Scholar]
  • 74.Gouet P, Robert X, Courcelle E. ESPript/ENDscript: sequence and 3D information from protein structures. Acta Crystallogr Sect A Found Crystallogr. 2005;61: c42–c43. doi: 10.1107/s0108767305098211 [DOI] [Google Scholar]
  • 75.Holm L, Laakso LM. Dali server update. Nucleic Acids Res. 2016;44: W351–W355. doi: 10.1093/nar/gkw357 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76.Ghouzam Y, Postic G, De Brevern AG, Gelly JC. Improving protein fold recognition with hybrid profiles combining sequence and structure evolution. Bioinformatics. 2015;31: 3782–3789. doi: 10.1093/bioinformatics/btv462 [DOI] [PubMed] [Google Scholar]
  • 77.Ye Y, Godzik A. Database searching by flexible protein structure alignment. Protein Sci. 2004;13: 1841–1850. doi: 10.1110/ps.03602304 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78.DeLano WL. The PyMOL Molecular Graphics System. Schrödinger LLC wwwpymolorg. 2002;Version 1.: http://www.pymol.org. doi:citeulike-article-id:240061 [Google Scholar]
  • 79.Gouw M, Michael S, Sámano-Sánchez H, Kumar M, Zeke A, Lang B, et al. The eukaryotic linear motif resource—2018 update. Nucleic Acids Res. 2018;46: D428–D434. doi: 10.1093/nar/gkx1077 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 80.Buchan DWA, Jones DT. The PSIPRED Protein Analysis Workbench: 20 years on. Nucleic Acids Res. 2019;47: W402–W407. doi: 10.1093/nar/gkz297 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81.Marchler-Bauer A, Derbyshire MK, Gonzales NR, Lu S, Chitsaz F, Geer LY, et al. CDD: NCBI’s conserved domain database. Nucleic Acids Res. 2015;43: D222–D226. doi: 10.1093/nar/gku1221 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82.Pagni M, Ioannidis V, Cerutti L, Zahn-Zabal M, Jongeneel CV, Hau J, et al. MyHits: Improvements to an interactive resource for analyzing protein sequences. Nucleic Acids Res. 2007;35. doi: 10.1093/nar/gkl987 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 83.Song J, Wang H, Wang J, Leier A, Marquez-Lago T, Yang B, et al. PhosphoPredict: A bioinformatics tool for prediction of human kinase-specific phosphorylation substrates and sites by integrating heterogeneous feature selection. Sci Rep. 2017;7. doi: 10.1038/s41598-017-00035-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 84.Manual U. Schrödinger Release 2019–3: Glide, Schrödinger, LLC, New York, NY, 2019. Schrödinger Release 2018–3 LigPrep, Schrödinger, LLC, New York, NY, 2018. 2018. [Google Scholar]
  • 85.Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJE. The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc. 2015;10: 845–858. doi: 10.1038/nprot.2015.053 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 86.Tian W, Chen C, Lei X, Zhao J, Liang J. CASTp 3.0: Computed atlas of surface topography of proteins. Nucleic Acids Res. 2018;46: W363–W367. doi: 10.1093/nar/gky473 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 87.Maffucci I, Contini A. Improved Computation of Protein-Protein Relative Binding Energies with the Nwat-MMGBSA Method. J Chem Inf Model. 2016;56: 1692–1704. doi: 10.1021/acs.jcim.6b00196 [DOI] [PubMed] [Google Scholar]
  • 88.Mariadasse R, Choubey SK, Jeyakanthan J. Insights into Exogenous Tryptophan-Mediated Allosteric Communication and Helical Transition of TRP Protein for Transcription Regulation. J Chem Inf Model. 2020;60: 175–191. doi: 10.1021/acs.jcim.9b00755 [DOI] [PubMed] [Google Scholar]
  • 89.Rajamanikandan S, Jeyakanthan J, Srinivasan P. Molecular Docking, Molecular Dynamics Simulations, Computational Screening to Design Quorum Sensing Inhibitors Targeting LuxP of Vibrio harveyi and Its Biological Evaluation. Appl Biochem Biotechnol. 2017;181. doi: 10.1007/s12010-016-2319-x [DOI] [PubMed] [Google Scholar]
  • 90.Butina D, Segall MD, Frankcombe K. Predicting ADME properties in silico: Methods and models. Drug Discovery Today. 2002. doi: 10.1016/s1359-6446(02)02288-2 [DOI] [PubMed] [Google Scholar]
  • 91.Surekha K, Prabhu D, Richard M, Nachiappan M, Biswal J, Jeyakanthan J. Investigation of vital pathogenic target orotate phosphoribosyltransferases (OPRTase) from Thermus thermophilus HB8: Phylogenetic and molecular modeling approach. Gene. 2016;583. doi: 10.1016/j.gene.2016.02.006 [DOI] [PubMed] [Google Scholar]
  • 92.Sato T, Yuki H, Ogura K, Honma T. Construction of an integrated database for hERG blocking small molecules. PLoS One. 2018;13. doi: 10.1371/journal.pone.0199348 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 93.Edelheit O, Hanukoglu A, Hanukoglu I. Simple and efficient site-directed mutagenesis using two single-primer reactions in parallel to generate mutants for protein structure-function studies. BMC Biotechnol. 2009;9. doi: 10.1186/1472-6750-9-61 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 94.Zhao L, Cong X, Zhai L, Hu H, Xu JY, Zhao W, et al. Comparative evaluation of label-free quantification strategies. J Proteomics. 2020;215. doi: 10.1016/j.jprot.2020.103669 [DOI] [PubMed] [Google Scholar]
  • 95.Yao P, Zhang Y, Sun Y, Gu Y, Xu F, Su B, et al. Isolation and Growth Characteristics of SARS-CoV-2 in Vero Cell. Virologica Sinica. 2020. pp. 348–350. doi: 10.1007/s12250-020-00241-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 96.Lu X, Wang L, Sakthivel SK, Whitaker B, Murray J, Kamili S, et al. US CDC real-time reverse transcription PCR panel for detection of severe acute respiratory syndrome Coronavirus 2. Emerg Infect Dis. 2020;26: 1654–1665. doi: 10.3201/eid2608.201246 [DOI] [PMC free article] [PubMed] [Google Scholar]
PLoS Comput Biol. doi: 10.1371/journal.pcbi.1009384.r002

Decision Letter 0

Nir Ben-Tal, Avner Schlessinger

1 Apr 2021

Dear Dr. Biswal,

Thank you very much for submitting your manuscript "Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2" for consideration at PLOS Computational Biology.

As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

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Sincerely,

Avner Schlessinger

Associate Editor

PLOS Computational Biology

Nir Ben-Tal

Deputy Editor

PLOS Computational Biology

***********************

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: The manuscript by Dwivedy et al. characterizes the RNA-dependent RNA polymerase from SARS-CoV-2 computationally and proposes an intriguing hypothesis that the NiRAN domain has “kinase like activity.” I cannot comment on the computational work, but as for the experimental portion there is one more important experiment lacking here, otherwise the authors cannot substantiate their claim about the activity. They measure ADP production from the RdRp using an ADP-Glo assay and conclude that there is kinase like activity. However, there are several problems with this conclusion. First, they merely measured ADP production, which implies ATP hydrolysis (or autophosphorylation), but does not show kinase-like activity. Secondly, they use the whole RdRp protein instead of the NiRAN domain. It seems possible that another part of the protein, say the RdRp active site, has ATPase activity. They need to rule out this possibility, with one or more of the following experiments:

-purify the NiRAN domain separately and show ATP hydrolysis

-show phosphotransfer activity for the whole protein or better the NiRAN domain. While no known substrates are known, standard generic substrates like dephosphorylated MBP should work.

-mutate residues in the NiRAN domain and show that the protein is still well folded but has a loss of ATP hydrolysis. They predict the active site of the NiRAN domain, but then need to test it out.

If not, then the authors can’t claim kinase like activity or any function to the NiRAN domain. While the potency of the kinase inhibitors is suggestive of kinase-like binding pocket, more needs to be shown to prove that.

Reviewer #2: This manuscript seeks to understand the function of the NiRAN domain of the SARS-CoV-2 polymerase, which is unique to nideoviruses. Based on both sequence and structural homology, the authors find that it is likely a kinase. In support of this hypothesis, they show it functions similarly to a known kinase, and that broad spectrum kinase inhibitors inhibit the activity of the NiRAN domain. Using docking, they also find some novel potential inhibitors. Together, their work provides valuable insight into this unique feature of the virus and starting points for drug discovery efforts.

Is there any evidence that the NiRAN domain is essential for the viral replication cycle? If not, it may not be a very useful drug target.

Is the active site of the NiRAN domain sufficiently different from that of other kinases to potentially allow for specific inhibition of the virus without off-target effects?

It would be useful to report docking scores and predicted binding affinities for a few suspected non-binders as a reference for judging the results for GTP, UTP, and potential inhibitors.

Many experimental screens of FDA-approved drugs have been performed. Can the authors comment on why none of these kinase inhibitors showed up as hits? Is there still hope that the NiRAN domain could be targeted successfully?

The figures are quite low resolution.

In Fig. 1, why not use the same color scheme in the structure in panel A and the secondary structure diagrams?

Reviewer #3: The manuscript by Dwivedy et al., characterizes the NiRAN domain of the RdRp protein from SARS-CoV-2 in terms of its structure, function, potential binding site and interactions with protease inhibitors. It is concluded that this domain possesses a kinase-like activity which could be inhibited by small ligands. It is therefore suggested that this domain may be a viable target for the development of new pharmaceuticals to fight of the COVID-19 pandemic.

Given the current state of the COVID-19 pandemic and the lack of therapies, any addition to the limited arsenal of tools to combat it, is important. From this perspective, the results presented in this manuscript are timely and relevant. Moreover, the manuscript is overall well written. However, there are multiple issues in the manuscript that need to be addressed before it is ready for publications. These are listed below:

Major points:

1. Line 139: Nothing that was discussed until this point actually supports the idea that the NiRAN domain assumes a kinase-like fold since its fold does not comply with the canonical kinase fold, nor with the other folds in Figure 1C.

2. Line 205: The fact that the three kinase inhibitors docked into the NiRAN site is rather meaningless as are the docking scores. You would probably be able to dock into this site other compounds which are clearly not kinase inhibitors. A more convincing argument can be put forth by searching for inactive analogues of the kinase inhibitors and demonstrating that they don’t bind well into the site.

3. Line 214: Based on the above, I don’t think that the docking analysis supports the kinase / phosphotransferase activity of NiRAN.

4. Line 251: I fail to see the value of the DFT calculations. The HOMO and LUMO energies by themselves are meaningless as are the corresponding energy differences. Similarly, the electrostatic potentials don’t add anything to the discussion. They may have been interesting had the authors tried to use them to explain the resulting binding modes, for example, by looking at how they match the electrostatic potential of the site, but this was not attempted.

5. Line 263: Why does the fact that the HOMO is more spread than the LUMO suggestive of a possible nucleophilic reaction? I would think that this spreading would reduce the electronic density at each point thereby reducing the strength of a nucleophilic attack. And which nucleophilic reaction are we talking about in the first place?

6. Line 280: Chemical reactivity towards what?

7. Line 350: Which simulations are we talking about? If this refers to the MM-GBSA simulations then their results were not discussed in the manuscript and furthermore, I don’t see what they add.

8. Line 352: Technically, 1000 nM count as nano-molar but these are really micro-molar concentrations.

9. Materials and methods: The docking protocol was not validated in any way. Table S3 contains a list of compounds selected for docking. Some of these compounds were solved in complex with their corresponding targets. The authors should try and reproduce the binding modes of these compounds with their docking protocol. Without this, how can we tell that the docking protocol is suitable for the task in hand?

10. Line 405: As stated above, what is the purpose of the MM-GBSA calculations?

11. Line 424: As noted above, I don’t see the value of the DFT calculations. Moreover, an implicit solvent model can hardly be qualified as “near physiological state” (line 431). Also, what were the starting geometries for the DFT calculations?

12. Lines 525 and 535: Docking scores by themselves are rather meaningless and are only good for comparison purposes. Furthermore, the docking scores of GTP and UTP were found to be -9.84 and -6.59 kcal/mol, respectively. Those of the three broad spectrum inhibitors were found to range between -2.6 and -3.5 kcal/mol. How could the latter then be classified as having “significantly low free binding energies”?

Minor points:

1. Line 72 and on: PDB codes should be given when discussing the cryo-EM structures.

2. Line 107: The sentence starting with “Apart from” is not clear. Are there 78 or 84 conserved residues?

3. Line 114: What is the meaning of “entry” pockets and how does the number “five” relate to the single site discussed later in the work?

4. Line 132: Change “comprises of an” to “comprises an”.

5. Line 184: This seems like a repeat of what was already discussed on line 175.

6. Line 213: I think it should be Table S4 rather than Table S3.

7. Line 339: Change “fewer” to “less”.

8. Line 355: Change “Sunitinib as” to “Sunitinib were”.

9. Line 413: The “.” Should be moved to after the “)”.

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Reviewer #3: Yes

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PLoS Comput Biol. doi: 10.1371/journal.pcbi.1009384.r004

Decision Letter 1

Nir Ben-Tal, Avner Schlessinger

26 Aug 2021

Dear Dr. Biswal,

Thank you very much for submitting your manuscript "Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Avner Schlessinger

Associate Editor

PLOS Computational Biology

Nir Ben-Tal

Deputy Editor

PLOS Computational Biology

***********************

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

[LINK]

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #2: I'm satisfied with the author's response.

Reviewer #3: The authors have adequately responded to all my comments on the original submission and I now find the manuscript ready for publication. Still, I have found a few typos that should be corrected. These are listed below:

1. Line 47: “play” -> “playing”

2. Line 85: “hinting as” -> “hinting at”

3. Line 127: “4” -> “four”

4. Line 158: “retrieved in” -> “retrieved by”

5. Line 217: “6” -> “six”

6. Line 252: “docking in” -> “docking”

7. Line 299: “like of” -> “type”

8. Line 303: “in appropriate” -> “under appropriate”

9. Line 362: “spread across” -> “spreads across”

10. Line 399: “such Rift” -> “such as Rift”

11. Line 616: “present” -> “presents”

12. Line 648: “interaction” -> “interactions”

**********

Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #2: Yes: Gregory R Bowman

Reviewer #3: No

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Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

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To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

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If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

PLoS Comput Biol. doi: 10.1371/journal.pcbi.1009384.r006

Decision Letter 2

Nir Ben-Tal, Avner Schlessinger

26 Aug 2021

Dear Dr. Biswal,

We are pleased to inform you that your manuscript 'Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2' has been provisionally accepted for publication in PLOS Computational Biology.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology. 

Best regards,

Avner Schlessinger

Associate Editor

PLOS Computational Biology

Nir Ben-Tal

Deputy Editor

PLOS Computational Biology

***********************************************************

PLoS Comput Biol. doi: 10.1371/journal.pcbi.1009384.r007

Acceptance letter

Nir Ben-Tal, Avner Schlessinger

31 Aug 2021

PCOMPBIOL-D-20-02312R2

Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2

Dear Dr Biswal,

I am pleased to inform you that your manuscript has been formally accepted for publication in PLOS Computational Biology. Your manuscript is now with our production department and you will be notified of the publication date in due course.

The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript.

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Thank you again for supporting PLOS Computational Biology and open-access publishing. We are looking forward to publishing your work!

With kind regards,

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PLOS Computational Biology | Carlyle House, Carlyle Road, Cambridge CB4 3DN | United Kingdom ploscompbiol@plos.org | Phone +44 (0) 1223-442824 | ploscompbiol.org | @PLOSCompBiol

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. A multiple protein sequence alignment of NiRAN and interface domains from the RdRp molecules of coronaviruses affect various vertebrate hosts.

    (TIF)

    S2 Fig. Organization and conservation of the NiRAN Domain.

    (A) Organization of the entry pockets at CoV-2-RdRp NiRAN domain lined with the strictly conserved residues. (B) While the conserved residues in the interface domain are scattered across the structural elements, the majority of the conserved residues in NiRAN domain lie between the antiparallel β-sheet and the immediately following helix bundle, possibly hinting at the NiRAN domain active site. (C) The predicted active site of the NiRAN domain possess both charged and uncharged residues, where in the charged residues primarily line the entry points of the pocket and the uncharged residues line in the deeper sections (Blue indicates positively charged regions, red indicates negatively charged regions and green indicates neutral regions, grey indicates regions beyond GTP-binding pocket).

    (TIF)

    S3 Fig. Pairwise alignments corresponding to the alignment of the structural elements of CoV-2-RdRp NiRAN with known Kinases.

    (A) Lim 2 kinase domain. (B) Syk kinase domain (C) O-mannosyl kinase domain. (D) IRAK4 kinase domain. (E) FGFR2 kinase domain. (F) Insulin receptor kinase domain. (Colour codes- Block 1: orange-cyan; Block 2: yellow-turquoise; Block 3: lime- deep blue; Block 4: green- deep blue; Block 5: green- purple).

    (TIF)

    S4 Fig. The structural superimposition of the Cα chains of CoV-2-RdRp NiRAN with known Kinases reveal significant alignment of the polypeptide chains.

    (A) Lim 2 kinase domain. (B) Syk kinase domain (C) O-mannosyl kinase domain. (D) IRAK4 kinase domain. (E) FGFR2 kinase domain. (F) Insulin receptor kinase domain. (The aforementioned kinases’ Cα chains are shown in cyan, CoV-2-RdRp NiRAN Cα chains are shown in yellow.)

    (TIF)

    S5 Fig. The prediction of kinase like motifs reveals the presence of sequence motifs belonging to kinase families PkA, PkC and Src.

    (A) Kinase consensus site search prediction also predicts multiple phosphorylation sites. (Bold- NiRAN domain; Italics- Interface domain; Underlines: Red- Kinase consensus sequence, Blue- PkC like motif, purple- PkA like motif, Green- Src kinase like motif, Grey- Unspecified Kinase like motifs, Yellow- Myristoylation site consensus sequence). (B) An inactive analog of Daidzein docked into the NiRAN domain putative active site. (C) An inactive analog of Geinstein docked into the NiRAN domain putative active site.

    (TIF)

    S6 Fig. Purification of SARS-CoV2-RdRp.

    A) Size exclusion chromatogram of recombinant SARS-CoV-2 RdRp (The peak indicated with a blue arrow represents the purified protein sample). (B) SDS-PAGE profile of the purified SARS-CoV-2 RdRp (The band indicated with a blue arrow represents the purified protein sample and the molecular weight markers are indicated in red arrows). (C) Fluorescence spectra for native and mutant SARS-CoV-2 RdRp suggest that the incorporated mutations have negligible effect on the protein structural integrity.

    (TIF)

    S7 Fig. MS-MS Spectra for the peptide KSLVSKGTLVQTK from Histone H1.

    (A) Histone H1 treated with SARS-CoV-2 RdRp in presence of ATP and Mg2+. (B) Histone H1 treated with human Akt2 in presence of ATP and Mg2+. (C) Histone H1 treated with SARS-CoV-2 RdRp in the presence of Mg2+ only (The b and y ions are shown in red and blue, respectively).

    (TIF)

    S8 Fig. Ion series detected in MS-MS for the peptide KSLVSKGTLVQTK from Histone H1.

    (A) Histone H1 treated with SARS-CoV-2 RdRp in presence of ATP and Mg2+. (B) Histone H1 treated with human Akt2 in presence of ATP and Mg2+. (C) Histone H1 treated with SARS-CoV-2 RdRp in the presence of Mg2+ only.

    (TIF)

    S1 Table. Top 15 molecules with structurally similar fold(s) predicted by HHPred analysis.

    (XLSX)

    S2 Table. Top 15 molecules with structurally similar fold(s) predicted by ORION_DSIMB analysis.

    (XLSX)

    S3 Table. Docking analysis of kinase inhibitors at the proposed active site of NiRAN domain.

    (XLSX)

    S4 Table. The complete list of compounds selected for docking at the predicted active site of CoV-2-RdRp NiRAN domain.

    (XLSX)

    S5 Table. Docking analysis of best 5 proposed inhibitors at the proposed active site of NiRAN domain.

    (XLSX)

    S6 Table. The predicted ADME/T properties of best 5 proposed inhibitors.

    (XLSX)

    S7 Table. LC-MS/MS verification of the SARS-CoV-2 RdRp.

    (XLSX)

    S8 Table. Phosphorylated peptide fragment of protein Histone H1 (K88-K100) detected by mass spectrometry.

    (XLSX)

    S1 Data. Raw data points for the graphs presented in Figs 5A, 6A, 6B and 6C; and the raw reads for the real-time PCR analysis.

    (XLSX)

    Attachment

    Submitted filename: Response_to_reviewers.docx

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    Submitted filename: Response_to_reviewers.docx

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    Submitted filename: Response_to_reviewers.docx

    Data Availability Statement

    The raw data points for the graphs presented in Figs 5A, 6A, 6B and 6C; and the raw reads for the real-time PCR analysis are provided in the S1 Data file. The mass spectrometry raw data files are submitted to the OSF repository at- “https://osf.io/rt6aw/?view_only=815070ca377a4a6cb4aac2e56990152e”. The results for the multiple sequence alignment, structural alignment, structural fold searches and small molecule dockings are submitted to the OSF repository at- “https://osf.io/bvcq2/?view_only=1a002bc15cf94bb884df06bc7d7601bc”.


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