key: cord-0774905-pehjkjsf
authors: Ahmed, Mohammad Z.; Zia, Qamar; Haque, Anzarul; Alqahtani, Ali S.; Almarfadi, Omar M.; Banawas, Saeed; Alqahtani, Mohammed S.; Ameta, Keshav Lalit; Haque, Shafiul
title: FDA-approved antiviral and anti-infection agents as potential inhibitors of SARS-CoV-2 main protease: an in silico drug repurposing study
date: 2021-02-09
journal: J Infect Public Health
DOI: 10.1016/j.jiph.2021.01.016
sha: 14007e7bf8c66d68b3c3753186c960acb697c550
doc_id: 774905
cord_uid: pehjkjsf

Background The emergence and spread of SARS-CoV-2 throughout the world has created an enormous socioeconomic impact. Although there are several promising drug candidates in clinical trials, none is available clinically. Thus, the drug repurposing approach may help to overcome the current pandemic. Methods The main protease (Mpro) of SARS-CoV-2 is crucial for cleaving nascent polypeptide chains. Here, FDA-approved antiviral and anti-infection drugs were screened by high-throughput virtual screening (HTVS) followed by re-docking with standard-precision (SP) and extra-precision (XP) molecular docking. The most potent drug's binding was further validated by free energy calculations (Prime/MM-GBSA) and molecular dynamics (MD) simulation. Results Out of 1397 potential drugs, 157 showed considerable affinity towards Mpro. After HTVS, SP, and XP molecular docking, four high-affinity lead drugs (Iodixanol, Amikacin, Troxerutin, and Rutin) with docking energies -10.629 to -11.776kcal/mol range were identified. Among them, Amikacin exhibited the lowest Prime/MM-GBSA energy (-73.800kcal/mol). It led us to evaluate other aminoglycosides (Neomycin, Paramomycin, Gentamycin, Streptomycin, and Tobramycin) against Mpro. All aminoglycosides were bound to the substrate-binding site of Mpro and interacted with crucial residues. Altogether, Amikacin was found to be the most potent inhibitor of Mpro. MD simulations of the Amikacin-Mpro complex suggested the formation of a complex stabilized by hydrogen bonds, salt bridges, and van der Waals interactions. Conclusion Aminoglycosides may serve as a scaffold to design potent drug molecules against COVID-19. However, further validation by in vitro and in vivo studies are required before using aminoglycosides as an anti-COVID-19 agent.

At the end of 2019, many patients were diagnosed with a respiratory tract infection exhibiting severe pneumonia in Wuhan, the capital of Hubei province in China [1, 2] . In a short time, the disease spread throughout the world and caused a pandemic. It was revealed that the causal organism is a novel coronavirus closely related to bat Severe Acute Respiratory Syndrome (SARS)-like coronavirus, and thus named as SARS-CoV-2 [3, 4] . The RNA genome of SARS-CoV-2 is about 82% identical to the SARS coronavirus (SARS-CoV), with both viruses belonging to clade b of the genus Betacoronavirus [1, 2] . In general, coronaviruses are enveloped, positive-sense, single-stranded RNA viruses in the genus Coronavirus of the family Coronaviridae that can infect humans and several animals, including mammals and aves [5] [6] [7] . The famous outbreak of SARS-CoV in Guangdong, China [8] , and Middle East respiratory syndrome coronavirus (MERS-CoV) in many countries of the Middle East region [9] establish the fact that some coronaviruses can cause life-threatening infection in patients. Likewise, COVID-19 has been confirmed to be transmitted via a human-to-human transmission that quickly spread to the majority of J o u r n a l P r e -p r o o f countries worldwide [10] , affecting millions (40,657,071 reported cases), with a death toll reaching 1,123,122 till Oct 19, 2020 (https://www.worldometers.info/coronavirus/).

Unfolding COVID-19 pandemics shows a necessity of rapid finding of drug-candidates that could be used immediately in numerous hotspots of virus activity. One of the most attractive drug targets among coronaviruses is the main protease (M pro ), also named chymotrypsin-like protease (3CL pro ) [11] . This enzyme plays a crucial role in processing the polyproteins translated from the viral RNA [12] . Inhibiting the activity of this enzyme would severely block viral replication. Since no human proteases with similar cleavage specificity are known, this approach sounds promising, as the prospective drug candidate's toxic manifestations against this enzyme would be negligible.

Several studies have now reported putative inhibitors using bioinformatics studies. For example, Gentile et al. (2020) screened a collection of 14,064 compounds searching for potential SARS-CoV-2 M pro inhibitors [13] . Similarly, Jin and colleagues identified 30 drugs and compounds as SARS-CoV-2 M pro inhibitors through protein modeling and virtual screening [14] , which represents rapid progress in dealing with the crisis. Virtual screening suggested that ledipasvir or velpatasvir might be particularly attractive as therapeutics to combat the new coronavirus [15] . Moreover, this protease's potential inhibitors were postulated to be alpha-keto amides with modifications added based on the proteincompound interactions [16] . However, to the best of our knowledge, no study to date exploited aminoglycosides as M pro inhibitors. Therefore, we screened a library of antiviral agents against the M pro enzyme. Initial results indicate Amikacin's effectiveness (aminoglycoside) in binding at the substrate site of M pro and making contacts with the J o u r n a l P r e -p r o o f catalytic residues. Further, some other aminoglycosides were selected to examine their effect on the M pro binding. Overall, Amikacin was found to be the best amongst aminoglycosides.

The ligands in antiviral (L7000) and anti-infection (L3100) agents libraries available at Selleck Inc (www.selleckchem.com) were processed using "LigPrep-2018 (Schrodinger, LLC, NY, USA)" as described previously [17] . Briefly, the ionization states of ligands were defined at pH 7.0 ± 2.0, and the salt (if any) was removed using "Epik-2018 (Schrodinger, LLC, NY, USA)". For each ligand, a maximum of 32 conformations was allowed to be generated. The energies of each ligand were minimized by OPLS3e (Optimized Potential for Liquid Simulations). A total of 3809 conformations representing different ionization states of ligands were generated and employed further in the study.

The 3D structural coordinates of the SARS-CoV-2 main protease (M pro ) were retrieved from the PDB databank (www.rcsb.org/structure/6LU7). The X-ray crystal structure of M pro (PDB Id: 6LU7) was resolved to 2.16 Å and contained a bound peptide-based inhibitor (N3) [18] .

Before virtual screening and molecular docking, the structure of M pro was processed using "Protein Preparation Wizard-2018 (Schrodinger, LLC, NY, USA)" as reported earlier [17] .

Briefly, hydrogen atoms were added, bond orders were assigned, any missing loops or side chains were added using "Prime-2018 (Schrodinger, LLC, NY, USA)". Non-catalytic water molecules and any other heterogeneous atoms were removed. A hydrogen bond network was created and optimized at a physiological pH of 7.4. Finally, the energy of the protein was J o u r n a l P r e -p r o o f minimized using OPLS3e forcefield. The grid enclosing substrate-binding site was created using the "Receptor Grid Generation tool (Schrodinger, LLC, NY, USA)" by selecting the bound ligand (N3) as the center of the grid. A grid box of 88×88×88 Å dimension was generated for virtual screening and molecular docking.

Screening of ligands towards the substrate-binding site of M pro was performed using the HTVS module in "Glide-2018 (Schrodinger, LLC, NY, USA)". The ligands displaying a good affinity for M pro were again docking at the substrate-binding site using standard precision (SP) docking. Further, the ligands filtered through SP docking were once again docked at the substrate-binding site of M pro using extra precision (XP) docking of "Glide-2018 (Schrodinger, LLC, NY, USA)" [17] . Analyses of the results were performed using "Maestro-2018 (Schrodinger, LLC, NY, USA)". The binding energy (ΔG) was used to calculate binding affinity (Kd) of ligands using the relation, as described previously [19] .

where R and T represent Boltzmann's gas constant (= 1.987 cal (mol K) -1 and temperature (= 298 K), respectively.

The solvent effect on the binding of a ligand to protein was evaluated by estimating the MM-GBSA using "Prime-2018 (Schrodinger, LLC, NY, USA)" as reported earlier [17] . i.e., MM-GBSA continuum solvent model [20] [21] [22] .

MD simulation of the most potent protein-ligand complex was performed to evaluate its stability and dynamics behavior. The initial conformation of the selected protein-ligand complex was subjected to an MD simulation of 100 ns using "Desmond-2018 (Schrodinger, LLC, NY, USA)" as described earlier [17] . An orthorhombic box was utilized to submerge protein-ligand complex in TIP3P explicit water solvent, at least 10 Å away from the box's walls. Proper counterions were added to neutralize the system, and physiological conditions were mimicked by adding 150 mM NaCl. Further, the whole system's energy was minimized with a convergence criterion of 1 kcal/mol/Å. MD simulation was performed under NTP conditions (300 K temperature and 1.013 bar pressure) wherein the temperature and pressure were maintained using Nose-Hoover-Chain thermostat and Martyna-Tobias-Klein barostat, respectively [23, 24] . A time-step of 2 fs was fixed, and the energy and structure were recorded and saved in the trajectory every 10 ps. The results were analyzed using "Maestro-2018 (Schrodinger, LLC, NY, USA)". Table 1 Table 1) .

The initial screening of ligands by HTVS and shortlisting by different docking procedures Table 2) . Amongst aminoglycosides, Amikacin was the most potent inhibitor of Mpro as its XP docking score (-11.238 kcal mol -1 ), and Prime/MM-GBSA score (-73.800 kcal mol -1 ) was the lowest. A detailed analysis of M pro -Amikacin interaction is given below, while the interaction of other aminoglycosides with M pro is described in supplementary data.

Amikacin-Mpro interaction analysis revealed that it was bound at the substrate-binding site and interacted with key amino acid residues (Figure 1 and Table 3 ). Amikacin formed seven hydrogen bonds (one hydrogen bond with each of Phe140, Pro168, and Gln189, and two hydrogen bonds with Cys145 and Glu166 each), and two salt bridges with Cys145 and Glu166. It also networked through van der Waals' interaction with some other amino acid residues such as Hie41, Met49, Tyr54, Leu141, Asn142, Gly143, Ser144, His163, His164, Met165, Leu167, Gly170, Hie172, Asp187, and Arg188. It is worth to note that His41 and Cys145 are catalytic amino acid residues of SARS-CoV-2 M pro . The docking energy and binding affinity of Amikacin towards M pro were estimated to be -11.238 kcal/mol and 1.75 × 10 8 M -1, respectively. The Prime/MM-GBSA score of Amikacin-M pro interaction was estimated to be -73.800 kcal/mol ( Table 2) .

J o u r n a l P r e -p r o o f Table 3 : Molecular interaction between SARS-CoV-2 M pro and different aminoglycosides.

No. 

RMSD is a measure of deviation in the position of Cα-atoms compared to the initial frame, as a function of simulation time. An RMSD value of ±2.00 Å suggests that the structure of protein remains stable throughout the simulation. The RMSD plots of M pro , Amikacin, and M pro -Amikacin complex is shown in Figure 2A . 

RMSF measures the conformation changes in the side chains of individual amino acid residues during a simulation. Figure 2B represents the RMSF plot of the M pro -Amikacin complex (blue curve) and the B-factor of M pro (brown curve) determined experimentally during X-ray crystallography. The RMSF values of the M pro -Amikacin complex were in agreement with the B-factor of M pro, i.e., the protein did not undergo any significant conformational changes due to the inhibitor's binding. The vertical green lines on X-axis show the contact between Amikacin and M pro , while the light brown and teal vertical bars represent the regions of α-helices and β-sheets. The RMSF plot of the M pro -Amikacin complex also confirmed that all the contacts between M pro and Amikacin were located in domain II, harboring the substrate-binding site ( Figure 2B ).

The analysis of rGyr of a ligand demonstrates its compactness as a function of simulation. In this study, the rGyr of Amikacin in the M pro -Amikacin complex was found to remain constant around 4.88 ± 0.08 Å (Figure 2C) . 

The analysis of the interaction between Amikacin and M pro that occurred during simulation indicates that hydrogen bonds played a significant role in stabilizing the M pro -

Amikacin complex (Figure 3) . Amikacin formed various interactions such as hydrogen bonds, hydrophobic interactions, ionic interactions, and water bridges with different substrate binding sites' residues ( Figure 3A) . The total number of contacts formed between M pro and Amikacin during the simulation was in the 2-17 range, with an average of 8 contacts ( Figure 3B, upper panel) . The significant amino acid residues participated in different capacities to stabilize the M pro -Amikacin complex were His41, Ser139, Phe140, Leu141, Asn142, Gly143, Ser144, Cys145, His163, His164, Met165, Glu166, Leu167, Pro168, Gly170, His172, Val180, Asp187, Arg188, Gln189, Thr190, Ala191, and Gln192.

Interestingly, Asn142, Ser144, Cys145, His164, and Glu166 played a significant role in making a stable M pro -Amikacin complex (Figure 3B, lower panel) . The catalytic residue

Cys145 formed a hydrogen bond and a water bridge with Amikacin for 76% and 37% of simulation time, respectively. Moreover, Glu166 formed two hydrogen bonds with Amikacin for 97% and 73% of simulation time, and a water bridge for more than 50% simulation time. His164 also formed a hydrogen bond with Amikacin for a shorter duration of around 37% simulation time ( Figure 3C ).

The analysis of variations in the secondary structure of a protein during simulation is crucial to examine protein conformation's stability. Figure 4A shows the contribution of individual amino acid residues in secondary structure formation, i.e., α-helices (blue bars) and β-sheets brown bars). It is evident that the majority of domain I and domain II amino acid residues, which are part of α-helices and β-sheets in the native structure, continue to contribute nearly 100% of simulation time in maintaining M pro 's secondary structural J o u r n a l P r e -p r o o f conformation. Similarly, the amino acid residues of domain III, which are part of β-sheets in the native structure, continue to participate nearly 100% of simulation time in maintaining the protein's conformation ( Figure 4A) . Moreover, the secondary structural elements (SSE) of M pro reported in X-ray crystal structure were 52 % (α-helix: 27% + β-sheet: 25%). During the simulation, the average secondary structure of Mpro was estimated to be 48 % (α-helix:

24% + β-sheet: 24%), which was in agreement with the reported value ( Figure 4B) . The contribution of individual amino acid residues over the simulation duration is represented in Figure 4C . It is evident that the secondary structure of M pro remained steady and did not deviate significantly upon Amikacin's binding during the whole simulation duration. The minor local changes might be due to the entry of a big ligand such as Amikacin into the substrate-binding cavity of M pro . inhibitor (N3) [14] . Some other computer-based drug designing and drug repurposing approaches have identified potential inhibitors of M pro , such as Nelfinavir and Lopinavir [25] ; Hesperidin and Diosmin [26] ; Kaempferol, Quercetin, and Rutin [26] ; and Ebselen [14] . Other aminoglycosides such as Gentamycin, Neomycin, Paramomycin, Streptomycin, and Tobramycin were also evaluated for their potential to inhibit M pro . All the aminoglycosides have been found to interact with M pro at the substrate-binding site, primarily through extensive hydrogen-bonding interactions with the key/catalytic residues. Among aminoglycosides, Amikacin was an effective inhibitor of Mpro due to its lowest Prime/MM-GBSA score. Hence, the stability of M pro -Amikacin was evaluated by molecular dynamics simulation. Amikacin interacted with M pro with crucial amino acid residues, Asn142, Ser144, Glu166, Cys145, and His164 in domain II. Among the crucial amino acids at the binding site, Glu166 forms a strong hydrogen bond with the Amikacin terminal NH3 and OH atoms. It has been shown that the catalytic dyad (His41 and Cys145) at the junction of domain I and domain II of M pro is responsible for its catalytic activity. Our analysis revealed that the residues Pro168 and Glu166, adjacent to Cys145, are involved in the interaction with the drug molecule, suggesting their crucial role in inhibiting the protein-protein interaction between the main protease and the human epigenetic regulatory proteins.

In addition to anti-bacterial activity, aminoglycosides have been discovered to possess antiviral properties against herpes simplex virus, influenza virus, and Zika virus [35, 36] .

Thus, aminoglycosides could serve as lead molecules to develop potential inhibitors against SARS-CoV-2.

During the COVID-19 pandemic, drug repurposing is being pursued as a fast strategy to develop safe and effective COVID-19 treatments. With some candidates being moved into clinical trials, no drug has shown a beneficial response against COVID-19 infection. In this study, a variety of potential ligands were considered for its affinity towards SARS-CoV-2 protease. Out of four potential lead compounds, Amikacin (an aminoglycoside) emerged as the most potent drug-candidate exhibiting the highest binding affinity towards M pro . Other aminoglycosides such as Gentamycin, Neomycin, Paramomycin, Streptomycin, and

Tobramycin also showed a high affinity towards M pro . However, before clinical application, detailed studies are needed to establish the antiviral potential of aminoglycosides.

The supplementary information comprises the following tables and figures.

Supplementary Table 1 

A pneumonia outbreak associated with a new coronavirus of probable bat origin

A new coronavirus associated with human respiratory disease in China

Full-genome evolutionary analysis of the novel corona virus (2019-nCoV) rejects the hypothesis of emergence as a result of a recent recombination event

Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding

Coronavirus genome structure and replication

Drug Design Targeting the Main Protease, the Achilles Heel of Coronaviruses

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Epidemiologic clues to SARS origin in China

Middle East Respiratory Syndrome Coronavirus (MERS-CoV): Announcement of the Coronavirus Study Group

A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster

Coronavirus main proteinase (3CLpro) Structure: Basis for design of anti-SARS drugs

From SARS to MERS: crystallographic studies on coronaviral proteases enable antiviral drug design

Putative inhibitors of SARS-COV-2 main protease from a library of marine natural products: A virtual screening and molecular modeling study

Structure of M pro from COVID-19 virus and discovery of its inhibitors

Potential therapeutic agents for COVID-19 based on the analysis of protease and RNA polymerase docking

Crystal structure of SARS-CoV-2 main protease provides a basis for design of improved a-ketoamide inhibitors

Identifying novel inhibitor of quorum sensing transcriptional regulator (SdiA) of

Klebsiella pneumoniae through modelling, docking and molecular dynamics simulation

Investigation on the binding of aloe-emodin with tyrosinase by spectral analysis and molecular docking

Interaction of meropenem with 'N' and 'B' isoforms of human serum albumin: a spectroscopic and molecular docking study

OPLS3: A Force Field Providing Broad Coverage of Drug-like Small Molecules and Proteins

The VSGB 2.0 model: A next generation energy model for high resolution protein structure modeling

The MM/PBSA and MM/GBSA methods to estimate ligandbinding affinities

Nosé-Hoover chain method for nonequilibrium molecular dynamics simulation

Constant pressure molecular dynamics algorithms

Potential Inhibitor of COVID-19 Main Protease ( M pro ) from Several Medicinal Plant Compounds by Molecular Docking Study

Main Protease (Mpro) Inhibitors from Natural Polyphenols: An in Silico Strategy Unveils a Hope against CORONA 2020

Current status and future trends in the diagnosis and treatment of drug-susceptible and multidrug-resistant tuberculosis

Best drug treatment for multidrugresistant and extensively drug-resistant tuberculosis

Antibiotics that affect the ribosome

Troxerutin improves hepatic lipid homeostasis by restoring NAD +-depletion-mediated dysfunction of lipin 1 signaling in high-fat diet-treated mice

Treatment of the common cold with troxerutin

Troxerutin protects the isolated perfused rat liver from a possible lipid peroxidation by coumarin

Protection of cellular DNA from γ-radiation-induced damages and enhancement in DNA repair by troxerutin

Metabolic and pharmacological properties of Rutin, a dietary quercetin glycoside, for treatment of inflammatory bowel disease

New activities for old antibiotics

Topical application of aminoglycoside antibiotics enhances host resistance to viral infections in a microbiota-independent manner