2-deoxy-D-glucose (2-DG). From Patanjali

Covid 19 been declared a public health emergency of global concern. Entry of SARS-CoV-2 is mediated through the viral spike glycoprotein (S2). Afterwards, the virus gets hold of the host cell machinery by employing the use of viral main protease 3CLpro and NSP15 endoribonuclease. In the present in silico study, active site mapping of the viral virulence factors was rendered by means of DoG Site Scorer. The possibility of repurposing of 2-deoxy-D-glucose (2-DG), a radio-chemo-modifier drug used for optimizing cancer therapy, and one of its derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose, has been investigated by conducting ligand-receptor docking. Binding pose depictions of ligands and viral receptors were assessed by employing molecular dynamics analysis. Molinspiration and Toxicity Estimation Software tools were used to assess the drug likeliness, bioactivity indices and ADMETox values. 2-DG can dock efficiently with viral main protease 3CLpro as well as NSP15 endoribonuclease, thus efficiently inactivating these viral receptors leading to incapacitation of the SARS-CoV-2 virus. Such incapacitation was possible by means of formation of a hydrogen bond between 2-DG and proline residues of viral protease. The 2-DG derivative formed a hydrogen bond with the glutamine amino acid residues of the viral spike glycoprotein. The present in silico study supports the potential benefits of using 2-DG and its glucopyranose derivative as repurposed drugs/prodrugs for mitigating the novel COVID-19 infection. Since both these moieties present no signs of serious toxicity, further empirical studies on model systems and human clinical trials to ascertain effective dose-response are warranted and should be urgently initiated.

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Posted on Authorea 31 Mar 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158567174.40895611 | This a preprint and has not been peer reviewed. Data may be preliminary.

Glucose antimetabolite 2-Deoxy-D-Glucose and its derivative as

promising candidates for tackling COVID-19: Insights derived

from in silico docking and molecular simulations

Acharya Balkrishna1, Pallavi Thakur1, Shivam Singh1, Swami Dev1, Viney Jain2, Anurag

Varshney1, and Rakesh Sharma3

1Patanjali Ayurved Ltd

2Jain Vishwa Bharti Institute

3Saveetha Institute of Medical and Technical Sciences

April 28, 2020

Abstract

A novel respiratory pathogen, SARS-CoV-2 has recently received worldwide attention and has been declared a public health

emergency of global concern. Entry of SARS-CoV-2 is mediated through the viral spike glycoprotein (S2). Afterwards, the

virus gets hold of the host cell machinery by employing the use of viral main protease 3CLpro and NSP15 endoribonuclease. In

the present in silico study, active site mapping of the viral virulence factors was rendered by means of DoG Site Scorer. The

possibility of repurposing of 2-deoxy-D-glucose (2-DG), a radio-chemo-modifier drug used for optimizing cancer therapy, and one

of its derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose, has been investigated by conducting ligand-receptor docking.

Binding pose depictions of ligands and viral receptors were assessed by employing molecular dynamics analysis. Molinspiration

and Toxicity Estimation Software tools were used to assess the drug likeliness, bioactivity indices and ADMETox values. 2-DG

can dock efficiently with viral main protease 3CLpro as well as NSP15 endoribonuclease, thus efficiently inactivating these viral

receptors leading to incapacitation of the SARS-CoV-2 virus. Such incapacitation was possible by means of formation of a

hydrogen bond between 2-DG and proline residues of viral protease. The 2-DG derivative formed a hydrogen bond with the

glutamine amino acid residues of the viral spike glycoprotein. The present in silico study supports the potential benefits of

using 2-DG and its glucopyranose derivative as repurposed drugs/prodrugs for mitigating the novel COVID-19 infection. Since

both these moieties present no signs of serious toxicity, further empirical studies on model systems and human clinical trials to

ascertain effective dose-response are warranted and should be urgently initiated.

Abbreviations : 2-DG: 2-deoxy-D-glucose; ADMETox: Adsorption, Distribution, Metabolism, Toxicity;

CoV: Coronavirus; DARS: Decoys as Reference State; FFT: Fast Fourier Transform; GPCR: G-protein

coupled receptor; MERS: Middle East Respiratory Syndrome; NSP: Non structural protein; O.E.C.D.: Or-

ganisation for Economic Co-operation and Development; PDB: Protein Data Bank; QSAR: Quantitative

Structure Activity Relationship; RCSB: Royal Collaborative Structural Biology; SARS: Severe Acute Respi-

ratory Syndrome; T.E.S.T.: Toxicity Estimation Software Tool; TPSA: Total polar surface area; VIF: Viral

infectivity factor

1. Introduction

The Corona virus (COVID-19), which sprung up in China during the late November, 2019, has shown a

burgeoning spread since then as it has been known to infect more than 8,03,011 people around the world,

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resulting in nearly 39,025 deaths as of 31 March, 2020 (Shao, 2020; WHO, 2020). It has been found to spread

in about 201 countries within a short time span of three months and hence, has been declared a pandemic

by the World Health Organization on 11th of March, 2020 (Cucinotta & Vanelli, 2020).

Coronaviruses presents a large family of enveloped RNA (non-segmented, positive sense) viruses that cause

zoonotic respiratory or occasional gastrointestinal infections in humans, wherein camels, cattle, bats and

cats may serve as reservoirs of viral transmission (Ye et al., 2020). The earlier timeline of spread of Coro-

naviruses have suggested that mainly 3 outbreaks of deadly pneumonia have been caused by Coronaviruses

in the 21st Century. These pathogenic serotypes of Coronaviruses have been named as SARS-CoV (Severe

Acute Respiratory Syndrome causing Coronavirus, outbreak in 2002); MERS-CoV (Middle East Respiratory

Syndrome causing Coronavirus, outbreak in 2012); and SARS-CoV-2 (Novel Beta-Coronavirus, outbreak in

2019) (Guarner, 2020). Genomic analysis have delineated the phylogenetic similarity between SARS-CoV

and SARS-CoV-2, however, the latter shows a mutational degree of genomic diversification, mainly in the

NSP domains (16 non-structural protein domains). Such mutations in the NSP domains of SARS-CoV-2

may be responsible for the differences in the host responsiveness, transmissibility and fatality of COVID-19

(Fung et al., 2020).

Analyzing the early history of SARS-CoV-2, it has been found that the virus got transmitted from animals

to humans as several cases of COVID-19 disease transmission were directly linked to seafood and live animal

ingestion in Wuhan, China (Jiang et al., 2020; Ward et al., 2020). It has also been found that the SARS-

CoV-2 bears nearly 96.2% similarities with that of the bat CoV RaTG13, thereby indicating bats to be the

natural reservoir of this virus (Zhou et al., 2020). Consequently, person-to-person spread of infection began

through direct contact with the infected individuals and via respiratory droplets (Carlos et al., 2020). Some

investigations have also suggested that SARS-CoV-2 may be present in feces of infected individuals and even

after the patient is cured, thereby indicating a feco-oral route of viral transmission as well (Yeo et al., 2020).

There are different stages of transmission of this virus, i.e. , contracting the disease upon travelling to the

virus-hit countries (Stage 1); local transmission by coming in contact with patients with a foreign travel

history (Stage 2); community transmission with difficulty in tracing the actual source of infection (Stage 3);

and ultimately occurrence of an epidemic, wherein the disease spreads at an alarmingly high rate and hence

becomes unlikely to be controlled. Italy and China have unfortunately reached the stage 3 of transmission,

wherein the death tolls are constantly increasing with rapidly rising new cases of infection. India is still

at stage 2 of COVID-19 outbreak and hence the disease transmission can be restricted by adopting proper

quarantine and isolation measures (WHO, 2020; Jiang et al., 2020).

SARS-CoV-2 possesses a high magnitude of risk owing to its massive transmission rate (~3%), high case

fatality rate (~4.3 – 11%, however the fatality rate may change), longer half life of virus (4-72 hours), nosoco-

mial mode of transmission (~79% transmission in hospitals) and asymptomatic mode of transmission (~2-14

days of incubation). The most common symptoms of COVID-19 include fever, malaise, nasal congestion,

dry cough, sore throat, dyspnoea, diarrhoea and multiple organ complications. However, some people serve

as asymptomatic carriers of the disease. Such asymptomatic cases of COVID-19 are the most difficult to

diagnose and thereupon treat. Although the defined symptoms appear to be mild, however, there have

been reported illnesses ranging from mild to severe conditions, and even death (Huang et al., 2020; Kim,

2020; Ralph et al., 2020). Despite several research efforts, there are yet no specific antiviral medications and

vaccines available for fighting with COVID-19. Many ongoing clinical trials are currently being conducted to

identify the most propitious drug candidate against COVID-19. The most acclamatory way of identifying the

propitious drug candidates for COVID-19 depends on understanding the pathophysiology of SARS-CoV-2

(Guo et al., 2020).

The first step of attachment and entry of Coronaviruses is dependent on the binding of SARS-CoV-2 spike

glycoprotein (S2) to cellular receptors (Angiotensin converting enzyme 2, ACE2) of the host. Secondly, after

entry into the host cell, the virus starts replicating with the aid of viral nuclease (NSP15 endoribonuclease)

and protease (Main Protease 3CLpro). All these said viral virulence factors are vital for the viral life cycle

(Liu et al., 2020). Hence, unraveling the pathogenesis of these virulence factors might provide insights into

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the etiology of COVID-19 and reveal therapeutic targets (Fig. 1 ).

Although, the structure and sequence of these viral virulence factors are known and drug screening is

continuously being conducted by targeting these virulence factors. However, yet there are no approved

drugs for effectively managing COVID-19 infection. WHO has recently announced restricted use permission

for repurposed anti-HIV, anti-malarial, anti-flu and anti-Ebola drugs (Guo et al., 2020; Senathilake et al.,

2020). Considering such a considerable emergency of this outbreak, the current in silico study is aimed at

investigating the possibilities of a glucose anti-metabolite, 2-deoxy-D-glucose (2-DG) as a repurposed drug

for the treatment of novel SARS-CoV-2 virus. Post entry of virus, the host cells have been observed to

undergo metabolic reprogramming to meet the increased demand of nutrients and energy for replication of

the virus, wherein 2-DG might serve as a probable drug candidate as it acts as a dual inhibitor of glycolysis as

well as glycosylation (Gualdoni et al., 2018). 2-DG has already been granted permission for clinical trials, as

evidenced from previously published results (Mohanti et al., 1996; Vijayaraghavan et al., 2006; Dwarkanath

et al., 2009).

In the present study, the drug-like potential of 2-DG will be studied by targeting SARS-CoV-2 spike glyco-

protein (S2), viral nuclease (NSP15 endoribonuclease) and protease (Main Protease 3CLpro). The binding

mechanism of 2-DG with the said viral virulence factors will be assessed by means of in silico molecular

docking as well as pharmacophore modeling. Moreover, another tetra-acetate glucopyranose derivative of

2-DG (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose) has also been assessed for studying its binding

affinities with the said viral virulence factors. The rationale for selecting this tetra-acetate glucopyranose

derivative as probable antiviral drug is dependent on its activity of impairing glycolysis and glycosylation.

Hence, this derivative can possibly be used as a prodrug for 2-DG (Jeon et al., 2020; Pajak et al., 2020).

One such prodrug of 2-DG, namely, 3,6-di-O-acetyl-2-deoxy-d-glucose has been developed in Dr. Waldemar

Priebe’s laboratory. This compound is currently being tested as an antiviral drug for targeting the novel

Coronavirus (Priebe et al., 2018; Keith et al., 2019; Pajak et al., 2020). Similar plan of repositioning 2-

deoxy-D-glucose and 1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose has been presented in the present

study, wherein all the molecular interactions of 2-DG and 2-DG derivative have been compared with the

currently used anti-retroviral drugs, i.e. , lopinavir; anti-flu drug, i.e. , favipiravir; and anti-malarial drug,

i.e. , hydroxychloroquine. The detailed molecular interactions and probable modes of action of 2-DG and

its prodrug have also been discussed in the present manuscript.

2. Materials and Methods

Conduction of the present in silico study has been made possible by the assistance of several databases includ-

ing PubChem (https://pubchem.ncbi.nlm.nih.gov/), RCSB Protein Data Bank (https://www.rcsb.org/) and

Proteins Plus Server (https://proteins.plus/); and softwares like Argus lab (http://www.arguslab.com/arguslab.com/ArgusLab.html),

Molinspiration (https://www.molinspiration.com/), Open Babel (http://openbabel.org), Hex (http://hex.loria.fr/),

and Toxicity Estimation Software Tool (https://www.epa.gov/chemical-research/toxicity-estimation-software-

tool-test). PubChem is an open chemistry database that provides two-dimensional chemical information

about the ligands being used in this study (Butkiewicz et al., 2013). The RCSB Protein Data Bank is a

global archive of three-dimensional structural data of biomolecules, per say viral receptors in this study (Rose

et al., 2015). Proteins Plus server is a common online server for computational drug modeling, wherein one

of its counterparts, namely, Pose View is used to visualize receptor structures and create pose depictions of

ligand-receptor binding. Moreover, another counterpart of Proteins Plus server, namely, DoG Site Scorer is

used to predict the active binding sites and druggability of binding pockets of receptors (F¨ahrrolfes et al.,

2017; Volkamer et al., 2012). Argus lab is molecular modeling software which is mainly used to visualize

the receptors as well as ligands and customize both of them for docking (Joy et al., 2006). Molinspiration is

online chemiinformatics software focused on calculating the molecular properties of ligands and predicting

their bioactivity properties (Jarrahpour et al., 2012). OpenBabel is an open platform for inter-converting

chemical file formats, thereby aiding in converting the 2D structure of ligands to 3D pdb structure and

hence customizing them for molecular docking (Samdani & Vetrivel, 2018). Hex is an interactive molecular

docking program for calculating the binding energies of interaction between receptors and ligands (Ritchie &

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Venkatraman, 2010). Toxicity Estimation Software Tool is a Quantitative Structure Activity Relationships

(QSAR) which is used to estimate the toxicity of ligands based on the molecular descriptors of the ligands

(Barron et al., 2012).

2.1 Preparation of 3D structure of viral virulence factors as receptors

The crystal structures of SARS-CoV-2 spike glycoprotein (S2; PDB code: 6VSB), viral nuclease (NSP15

endoribonuclease; PDB code: 6VWW) and protease (Main Protease 3CLpro; PDB code: 1Q2W) were

obtained from RCSB Protein Data Bank (https://www.rcsb.org/). Hydrogen atoms were introduced in

all these 3D structures using Argus Lab (4.0.1), so as to customize the viral receptors for rigid docking

(http://www.arguslab.com/arguslab.com/ArgusLab.html).

2.2 Preparation of 3D structure of 2-DG and 2-DG derivative as ligands

The structure of 2-deoxy-D-glucose and 2-DG derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose)

were downloaded in xml format from PubChem database and structures were validated (Butkiewicz et

al., 2013). Hydrogen atoms were introduced into the ligands structure using Argus lab (4.0.1), so as to

customize them for rigid docking. The hydrogenated ligand molecules were then converted into pdb format

using Open Babel (2.4) interface (openbabel.org/docs/dev/OpenBabel.pdf), as required for rigid docking.

Similarly, 3D structures of standard chemotherapeutic agents (lopinavir, favipiravir, hydroxychloroquine)

were also customized for docking.

2.3 Active site analysis of viral virulence factors

DoG Site Scorer, a web based tool (https://proteins.plus/), was used to predict the possible binding sites

in the 3D structure of spike glycoprotein, viral nuclease and viral main protease. Predictions with DoG Site

Scorer were based on the difference of gaussian filter to detect potential pockets on the protein surfaces and

thereby splitting them into various sub-pockets. Subsequently, global properties, describing the size, shape

and chemical features of the predicted pockets were calculated so as to estimate simple score for each pocket,

based on a linear combination of three descriptors, i.e ., volume, hydrophobicity and enclosure. For each

queried input structure, a druggability score between 0-to-1 was obtained. Higher the druggability score,

higher the physiological relevance of the pocket as potential target (Volkamer et al., 2012).

2.4 Molecular Docking and Ligand Receptor Binding analysis

The docking analysis of pdb structures of 2-deoxyglucose and its analogue (1, 3, 4, 6-Tetra-O-acetyl-2-

deoxy-D-glucopyranose) with viral receptors (spike glycoprotein, viral nuclease and viral main protease) was

carried by Hex Cuda 8.0.0 software. Receptor and Ligand files were imported in the software (Harika et

al., 2017). The grid dimension of docking was defined according the to the binding site analysis of DoG

Site Scorer (Volkamer et al., 2012). Graphic settings and Docking parameters were customized so as to

calculate the binding energies (E values) of ligand receptor docking. The parameters used for the docking

process were set as (i) Correlation type: Shape + Electro + DARS, (ii) FFT mode: 3D fast lite, (iii) Grid

Dimension: 0.6, (iv) Receptor range: 180°, (v) Ligand range: 180°, (vi) Twist range: 360°. The best docked

conformations with lowest docking energy were selected for further MD simulations using Pose View for

creating pose depictions of selected ligand-receptor binding (Ezat et al., 2014). Molecular Docking and MD

simulations for the standard chemotherapeutic agents (lopinavir, favipiravir, hydroxychloroquine) were also

conducted. The MM-PBSA method was used to compute the binding free energy of receptor-ligand docking

during simulation. In this study, the binding free energy of the receptors to ligands was calculated using the

GROMACS tool, wherein the binding free energy of the receptor and ligand was defined as

ΔGbinding =ΔGcomplex – (ΔGreceptor +ΔGligand)

For each subunit, the free energy, G, can be presented as summation of mechanical potential energy (Elec-

trostatic and Vander Waals interaction) and solvation free energy (Gpolar + Gnonpolar ), wherein the total

entropy is excluded from the total value (Weis et al., 2006).

2.5 Molinspiration based Molecular property and Bioactivity analysis

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Molinspiration software was used to analyze molecular descriptors and bioactivity scores of the ligands and

standard chemotherapeutic agents, namely, MiLog P, Total polar surface area (TPSA), molecular weight,

number of atoms, number of rotatable bonds, number of hydrogen bond donors and acceptors. Bioactivity

of the ligands was also checked by using Molinspiration which can analyze the activity score of GPCR

ligands, kinase inhibitors, ion channel modulators, enzymes and nuclear receptors. Ligands were loaded in

the Molinspiration software in SMILES format and the molecular descriptor as well as bioactivity analysis

was conducted (Jarrahpour et al., 2012).

2.6 In silico Toxicity estimation

Ligands (2-DG and 2-DG derivative) and standard chemotherapeutic agents (lopinavir, favipiravir, and

hydroxychloroquine) were uploaded in the Toxicity Estimation Software Tool in sdf format. Oral rat LD50 ,

Bioconcentration Factor, Developmental Toxicity and Ames Mutagenicity were estimated using consensus

method of QSAR analysis (Barron et al., 2012).

3. Results & Discussion

3.1 Active site analysis

Active site analysis of SARS-CoV-2 spike glycoprotein (S2), viral nuclease (NSP15 endoribonuclease) and

protease (Main Protease 3CLpro) as conducted by DoG Site Scorer indicated that there are various active

pockets within the studied viral virulence factors with druggability ranging from 0.12 to 0.86 (Table 1 ).

It was found that pockets P 11 (Drug score: 0.847), P 1 (Drug score:0.860) and P 0 (Drug score: 0.805)

were energetically favourable for performing further molecular docking studies with the viral receptors being

spike glycoprotein, NSP15 endoribonuclease and Main Protease 3CLpro, respectively. While conducting the

active site analysis, the DoG Site Scorer tool analysed the heavy atom coordinates on the surface of the 3D

structure of the respective viral receptors. Depending on these atomic coordinates, a hypothetical grid was

spanned by outruling the chances of any spatial overlap of the grid with the heavy atoms. Furthermore, the

tool engages in applying a Gaussian filter to the defined grids, so as to identify spherical pockets of binding.

Druggability score (0-1) of the selected spherical pockets are deduced on the basis of their surface area,

volume, enclosure and hydrophobicity. As a general rule, higher druggability score is indicative of a more

druggable pocket (Volkamer et al., 2012). The most druggable pockets of SARS-CoV-2 spike glycoprotein,

NSP15 endoribonuclease and main protease 3CLpro have been elucidated inFig. 2 .

3.2 Molecular Docking

Docking results of the viral virulence factors, namely, spike glycoprotein, NSP15 endoribonuclease and

Main Protease 3CLpro; and the drug 2-deoxy-D-glucose (2-DG) as well as 2-DG derivative (1, 3, 4, 6-

Tetra-O-acetyl-2-deoxy-D-glucopyranose) are shown in Table 2 . These docking based E values have also

been compared with that of the standard drugs (lopinavir, favipiravir and hydroxychloroquine). The Hex

based docking results reveal that the E-value of docking of 2-DG with viral main protease 3CLpro (E

value2-DG + Protease = -140.05 Kcal/mol) was found to be better than that of the standard drug lopinavir (E

valueLopinavir + Protease = -124.00 Kcal/mol). Similarly, the docking of 2-DG with viral endoribonuclease also

yielded significantly better binding energies (E value2-DG + Endoribonuclease = -168.65 Kcal/mol) as compared

to that of the standard drug favipiravir (E valueFavipiravir + Endoribonuclease = -128.00 Kcal/mol). However, the

binding energy of 2-DG with that of spike glycoprotein (E value2-DG + Spike glycoprotein = -118.31 Kcal/mol)

was found to be moderately lower as compared to that of the tested standard drugs. It is obvious from the

E-values that 2-deoxy-D-glucose binds spontaneously and irreversibly to main protease 3CLpro and viral

endoribonuclease, wherein the binding efficiency of 2-DG has been found to be exceedingly better than

that of lopinavir and favipiravir. Such significant binding affinity of 2-DG with that of SARS-CoV-2 viral

receptors presumably indicates the probable mechanism of action of 2-deoxy-D-glucose as viral protease

and endoribonuclease inhibitor. Viral protease is fundamental for continuing the viral life cycle of SARS-

CoV-2 as it is required by the virus to catalyze the cleavage of viral polyprotein precursors which are

ultimately necessary for viral capsid formation and enzyme production (Anand et al., 2003). Similarly, viral

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endonucleases are necessary for catalyzing the processing of viral RNAs and hence are required for enduring

the process of viral replication (Ward et al., 2020). Henceforth, the 2-deoxy-D-glucose moiety contingently

inactivates the viral protease, thereby inhibiting the process of viral capsid formation. Furthermore, 2-DG

may also be responsible for withholding the action of viral endoribonuclease, thereby halting the process of

viral replication altogether.

Moreover, the 2-DG derivative, namely, 1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose also showed an

increase in the free energy of the complex with the viral receptors. The E-value of docking of 2-DG derivative

with viral main protease 3CLpro (E value2-DG derivative + Protease = -187.64 Kcal/mol) was found to be better

than that of the standard drug lopinavir (E valueLopinavir + Protease = -124.00 Kcal/mol). Similarly, the

docking of 2-DG derivative with viral endoribonuclease (E value2-DG derivative + Endoribonuclease = -208.33

Kcal/mol) as well as spike glycoprotein (E value2-DG derivative + Spike glycoprotein = -173.89 Kcal/mol) yielded

significantly better results as compared to that of favipiravir, wherein its E value is lower in both cases, i.e.

, E valueFavipiravir + Endoribonuclease = -128.00 Kcal/mol; and E valueFavipiravir + Spike glycoprotein = -118.31

Kcal/mol. The 2-DG derivative exhibited significantly better binding values as compared to that of 2-DG

itself. The derivative displayed spontaneous binding efficiencies while docking with viral protease, viral

endonuclease and spike glycoprotein. The binding energy of 2-DG derivative was found to be comparable to

that of hydroxychloroquine which has been proposed as the cornerstone for COVID-19 therapy. Hence, 1, 3, 4,

6-Tetra-O-acetyl-2-deoxy-D-glucopyranose could presumably mitigate the virus completely as it could restrict

viral entry into the host cell by inactivating the spike glycoprotein; halt viral capsid formation by inactivating

the viral main protease; and cease viral replication by inactivating the viral endoribonuclease. Earlier

studies have also indicated that glucopyranose derivatives are glycolysis inhibitors and cause mitochondrial

oxidative phosphorylation, thereby indicating a probable antiviral role of 1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-

D-glucopyranose (Jeon et al., 2020).

3.3 Ligand Receptor binding pose depictions

The best docking pose of 2-DG, and its derivatives with SARS-CoV-2 viral receptors was also identified

using Pose View tool so as to visualize the interactions of the ligands with that of the residues present in

the active sites of the viral receptors. Both 2-deoxy-D-glucose and its derivative were found to form salt

bridges with the amino acid residues of the viral receptors, namely, main protease 3CLpro and viral spike

glycoprotein, respectively. The orientational binding of the ligands and the viral receptors showing the pose

view and residue interactions have been depicted in Fig. 3 . It was observed that the hydroxyl group of

2-deoxy-D-glucose formed a hydrogen bond with the carbonyl residue of Proline amino acid (108th position)

found in the viral main protease. In earlier studies it has been found that the proline amino acid residues

are found in the conserved domains of HIV viral infectivity factor (Vif) and these proline-rich motifs are

therapeutic targets for neutralizing the human immunodeficiency virus (Yang et al., 2003; Ralph et al.,

2020). Chemical bridging of 2-deoxy-D-glucose and proline residues of viral main protease 3CLpro present

a similar case where proline residues were invariably bound and neutralized, thereby possibly neutralizing

the COVID-19 virus. Similarly, the 2-DG derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose)

formed a hydrogen bond with the amide group of Glutamine amino acid (804thposition) found in the viral

spike glycoprotein. Reynard and Volchkov have also previously highlighted that mutation or any change in

the glutamine residues of Ebola virus spike glycoprotein causes viral neutralization (Reynard & Volchkov,

2015). In conclusion, the binding interactions of 2-deoxy-D-glucose with viral main protease and 1, 3, 4,

6-Tetra-O-acetyl-2-deoxy-D-glucopyranose with viral spike glycoprotein is now evident, as analysed by using

Pose View tool.

2-deoxy-D-glucose and its derivative can influence several cellular pathways, including glycolysis, glycosyla-

tion, endoplasmic stress response (ER), phagocytosis and apoptosis. Both the moieties inhibit the processes

of glucose transport and glycolysis by competing with glucose. Competitive uptake of 2-DG or its deriva-

tive in the infected cell leads to the formation of 2-deoxy-d-glucose-6-phosphate (2-DG-6-P) by means of

hexokinase enzyme. 2-DG-6-P cannot be further metabolized, thereby hampering the bioenergetic process

of ATP production by glycolysis (Sharma et al., 1996); inactivating the glycolytic enzymes; inducing cell

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cycle arrest and ultimately leading to inactivation of nCoV-19 in infected cells (Maher et al., 2004; Pajak

et al., 2020). The depletion of ATP levels leads to activation of AMP-activated protein kinase (AMPK).

Such activation will lead to phosphorylation of proteins of the mTOR kinase complex (mammalian target of

rapamycin kinase, mTORC). As a consequence, expression of p53 is induced which ultimately promotes cell

cycle arrest (G1 phase arrest) in virus infected cells. All these factors (glycolysis inhibition, ATP depletion

and cell cycle arrest) cause a sensitized response leading to the upregulation of TNF expression, ultimately

leading to an apoptotic response. Moreover, both 2-DG and its tetra-acetate glucopyranose derivative es-

calate the production of reactive oxygen species, ultimately leading to virus infected cell death (Fig. 4 )

(Zhang et al., 2015; Pajak et al., 2020).

3.4 Molecular property analysis

After analyzing the binding energies and ligand-receptor binding pose depictions, it was requisite to evaluate

the drug likeliness of the ligands. Analysis of molecular descriptors is necessary in elucidating the pharma-

cokinetic parameters of the drugs such as absorption, distribution, metabolism, and excretion. Molinspiration

software was used to analyze the Lipinski Rule of Five, including the Log P value (partition coefficient),

molecular weight, polar surface area, number of hydrogen bond donor and number of hydrogen bond accep-

tor. According to the Lipinski’s rule, a drug like moiety should have a low molecular weight ([?] 500 D), log P

value [?] 5, number of hydrogen bond acceptors [?]10, and number of hydrogen bond donors [?]5. A bioactive

druggable molecule should ensue to at least 4 of the 5 Lipinski rules (Zhang & Wilkinson, 2007). In the

present study, it was found that 2-deoxy-D-glucose and 1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose

befalls within the said permissible limits of Lipinski rules and hence, both these drugs can be said to possess

satisfactory oral bioavailability (Table 3 ).

3.5 Bioactivity analysis

Molinspiration was used to virtually screen the biological activity of drug moieties, per say 2-DG and 2-

DG derivative in the present study. The fundamental principle behind this in silico bioactivity screening

is the identification of substructure(s) responsible for endowing pharmacological features (GPCR binding

ability, ion channel modulation potential, kinase inhibition activity, nuclear receptor binding potential, and

protease inhibition) to the drug molecules being studied. The bioactivity score of the ligands and standard

chemosynthetic moieties is presented in Table 4 . In general, if the bioactivity score for a particular target is

more than 0.0, then the said drug moiety is considered to be highly active. Additionally, a bioactivity score

of a ligand lying between -5.0 and 0.0 is considered to be moderately active. However, bioactivity scores

of ligands below -5.0 render it to be inactive (Singh et al., 2013). As observed in Table 4, the bioactivity

scores of 2-DG for most of the bioactivity descriptors were below -0.5, thereby indicating its inactivity

towards those targets. However, 2-DG possessed moderate bioactivity as ion channel modulator (Bioactivity

score Ion channel modulator ˜ -0.14) and protease inhibitor (Bioactivity score Protease inhibitor ˜ -0.37). This

bioactivity score of 2-DG is in corroboration with the molecular docking results which also suggest 2-DG to

be a significant protease inhibitor (E 2-DG + Protease = -140.05 Kcal/mol). The antiviral effect of 2-DG has

also been recognized in previous studies. Inhibition of multiplication has been reported for some enveloped

viruses such as influenza virus, sindbis virus, semliki forest virus, herpes simplex virus, respiratory syncytial

virus and measles virus (Kang & Hwang, 2006; Krol et al., 2017). Furthermore, 2-DG eliminated genital

herpes from most of the tested patients. It also alleviated the severity of infection of calves with respiratory

syncytial virus and infectious of bovine rhino-tracheitis virus (Leung et al., 2012). According to all these

earlier studies, inhibition of viral envelope biosynthesis and virion assembly due to blocked glycosylation

of membrane proteins appears to be the major mechanism of 2-DG for virus attenuation. This has been

supported by altered gel electrophoresis profiles of membrane proteins as well as denuded appearance of

budding particles shown by electron microscopy. Studies also suggest that 2- DG can also suppress viral

gene expression or viral replication (Camarasa et al., 1986; Kang & Hwang, 2006; Leung et al., 2012; Krol

et al., 2017).

Furthermore, the bioactivity score of 2-DG derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose)

suggested that it mainly acts as a GPCR ligand (Bioactivity score GPCR ligand˜ 0.13), ion channel modulator

7

Citations (1)

References (52)

… 2-deoxy-D-glucose (2-DG): A glucose analogue, 2-deoxy-D-glucose, is believed to have profound effects on a range of diseases such as cancer, viral infection and ageing-related morbidity 28 . Recent in vitro studies suggest the potential benefits of using 2-DG to mitigate COVID-19 infection 29,30 . A Phase 2 trial to determine the safety and efficacy of the drug as an adjunctive therapy to standard of care in patients with moderate-to-severe COVID-19 is underway at 12 sites (CTRI/2020/06/025664). …

Emerging trends from COVID-19 research registered in the Clinical Trials Registry – India

Article

Nov 2020INDIAN J MED RES

Vishnu Vardhana Rao Mendu

Atul JunejaMohua MaulikNeha Yadav

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been declared a public health emergency of global concern. Entry of SARS-CoV-2 is mediated through the viral spike glycoprotein (S2). Afterwards, the virus gets hold of the host cell machinery by employing the use of viral main protease 3CLpro and NSP15 endoribonuclease. In the present in silico study, active site mapping of the viral virulence factors was rendered by means of DoG Site Scorer. The possibility of repurposing of 2-deoxy-D-glucose (2-DG), a radio-chemo-modifier drug used for optimizing cancer therapy, and one of its derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose, has been investigated by conducting ligand-receptor docking. Binding pose depictions of ligands and viral receptors were assessed by employing molecular dynamics analysis. Molinspiration and Toxicity Estimation Software tools were used to assess the drug likeliness, bioactivity indices and ADMETox values. 2-DG can dock efficiently with viral main protease 3CLpro as well as NSP15 endoribonuclease, thus efficiently inactivating these viral receptors leading to incapacitation of the SARS-CoV-2 virus. Such incapacitation was possible by means of formation of a hydrogen bond between 2-DG and proline residues of viral protease. The 2-DG derivative formed a hydrogen bond with the glutamine amino acid residues of the viral spike glycoprotein. The present in silico study supports the potential benefits of using 2-DG and its glucopyranose derivative as repurposed drugs/prodrugs for mitigating the novel COVID-19 infection. Since both these moieties present no signs of serious toxicity, further empirical studies on model systems and human clinical trials to ascertain effective dose-response are warranted and should be urgently initiated.

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Posted on Authorea 31 Mar 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158567174.40895611 | This a preprint and has not been peer reviewed. Data may be preliminary.

Glucose antimetabolite 2-Deoxy-D-Glucose and its derivative as

promising candidates for tackling COVID-19: Insights derived

from in silico docking and molecular simulations

Acharya Balkrishna1, Pallavi Thakur1, Shivam Singh1, Swami Dev1, Viney Jain2, Anurag

Varshney1, and Rakesh Sharma3

1Patanjali Ayurved Ltd

2Jain Vishwa Bharti Institute

3Saveetha Institute of Medical and Technical Sciences

April 28, 2020

Abstract

A novel respiratory pathogen, SARS-CoV-2 has recently received worldwide attention and has been declared a public health

emergency of global concern. Entry of SARS-CoV-2 is mediated through the viral spike glycoprotein (S2). Afterwards, the

virus gets hold of the host cell machinery by employing the use of viral main protease 3CLpro and NSP15 endoribonuclease. In

the present in silico study, active site mapping of the viral virulence factors was rendered by means of DoG Site Scorer. The

possibility of repurposing of 2-deoxy-D-glucose (2-DG), a radio-chemo-modifier drug used for optimizing cancer therapy, and one

of its derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose, has been investigated by conducting ligand-receptor docking.

Binding pose depictions of ligands and viral receptors were assessed by employing molecular dynamics analysis. Molinspiration

and Toxicity Estimation Software tools were used to assess the drug likeliness, bioactivity indices and ADMETox values. 2-DG

can dock efficiently with viral main protease 3CLpro as well as NSP15 endoribonuclease, thus efficiently inactivating these viral

receptors leading to incapacitation of the SARS-CoV-2 virus. Such incapacitation was possible by means of formation of a

hydrogen bond between 2-DG and proline residues of viral protease. The 2-DG derivative formed a hydrogen bond with the

glutamine amino acid residues of the viral spike glycoprotein. The present in silico study supports the potential benefits of

using 2-DG and its glucopyranose derivative as repurposed drugs/prodrugs for mitigating the novel COVID-19 infection. Since

both these moieties present no signs of serious toxicity, further empirical studies on model systems and human clinical trials to

ascertain effective dose-response are warranted and should be urgently initiated.

Abbreviations : 2-DG: 2-deoxy-D-glucose; ADMETox: Adsorption, Distribution, Metabolism, Toxicity;

CoV: Coronavirus; DARS: Decoys as Reference State; FFT: Fast Fourier Transform; GPCR: G-protein

coupled receptor; MERS: Middle East Respiratory Syndrome; NSP: Non structural protein; O.E.C.D.: Or-

ganisation for Economic Co-operation and Development; PDB: Protein Data Bank; QSAR: Quantitative

Structure Activity Relationship; RCSB: Royal Collaborative Structural Biology; SARS: Severe Acute Respi-

ratory Syndrome; T.E.S.T.: Toxicity Estimation Software Tool; TPSA: Total polar surface area; VIF: Viral

infectivity factor

1. Introduction

The Corona virus (COVID-19), which sprung up in China during the late November, 2019, has shown a

burgeoning spread since then as it has been known to infect more than 8,03,011 people around the world,

1

Posted on Authorea 31 Mar 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158567174.40895611 | This a preprint and has not been peer reviewed. Data may be preliminary.

resulting in nearly 39,025 deaths as of 31 March, 2020 (Shao, 2020; WHO, 2020). It has been found to spread

in about 201 countries within a short time span of three months and hence, has been declared a pandemic

by the World Health Organization on 11th of March, 2020 (Cucinotta & Vanelli, 2020).

Coronaviruses presents a large family of enveloped RNA (non-segmented, positive sense) viruses that cause

zoonotic respiratory or occasional gastrointestinal infections in humans, wherein camels, cattle, bats and

cats may serve as reservoirs of viral transmission (Ye et al., 2020). The earlier timeline of spread of Coro-

naviruses have suggested that mainly 3 outbreaks of deadly pneumonia have been caused by Coronaviruses

in the 21st Century. These pathogenic serotypes of Coronaviruses have been named as SARS-CoV (Severe

Acute Respiratory Syndrome causing Coronavirus, outbreak in 2002); MERS-CoV (Middle East Respiratory

Syndrome causing Coronavirus, outbreak in 2012); and SARS-CoV-2 (Novel Beta-Coronavirus, outbreak in

2019) (Guarner, 2020). Genomic analysis have delineated the phylogenetic similarity between SARS-CoV

and SARS-CoV-2, however, the latter shows a mutational degree of genomic diversification, mainly in the

NSP domains (16 non-structural protein domains). Such mutations in the NSP domains of SARS-CoV-2

may be responsible for the differences in the host responsiveness, transmissibility and fatality of COVID-19

(Fung et al., 2020).

Analyzing the early history of SARS-CoV-2, it has been found that the virus got transmitted from animals

to humans as several cases of COVID-19 disease transmission were directly linked to seafood and live animal

ingestion in Wuhan, China (Jiang et al., 2020; Ward et al., 2020). It has also been found that the SARS-

CoV-2 bears nearly 96.2% similarities with that of the bat CoV RaTG13, thereby indicating bats to be the

natural reservoir of this virus (Zhou et al., 2020). Consequently, person-to-person spread of infection began

through direct contact with the infected individuals and via respiratory droplets (Carlos et al., 2020). Some

investigations have also suggested that SARS-CoV-2 may be present in feces of infected individuals and even

after the patient is cured, thereby indicating a feco-oral route of viral transmission as well (Yeo et al., 2020).

There are different stages of transmission of this virus, i.e. , contracting the disease upon travelling to the

virus-hit countries (Stage 1); local transmission by coming in contact with patients with a foreign travel

history (Stage 2); community transmission with difficulty in tracing the actual source of infection (Stage 3);

and ultimately occurrence of an epidemic, wherein the disease spreads at an alarmingly high rate and hence

becomes unlikely to be controlled. Italy and China have unfortunately reached the stage 3 of transmission,

wherein the death tolls are constantly increasing with rapidly rising new cases of infection. India is still

at stage 2 of COVID-19 outbreak and hence the disease transmission can be restricted by adopting proper

quarantine and isolation measures (WHO, 2020; Jiang et al., 2020).

SARS-CoV-2 possesses a high magnitude of risk owing to its massive transmission rate (~3%), high case

fatality rate (~4.3 – 11%, however the fatality rate may change), longer half life of virus (4-72 hours), nosoco-

mial mode of transmission (~79% transmission in hospitals) and asymptomatic mode of transmission (~2-14

days of incubation). The most common symptoms of COVID-19 include fever, malaise, nasal congestion,

dry cough, sore throat, dyspnoea, diarrhoea and multiple organ complications. However, some people serve

as asymptomatic carriers of the disease. Such asymptomatic cases of COVID-19 are the most difficult to

diagnose and thereupon treat. Although the defined symptoms appear to be mild, however, there have

been reported illnesses ranging from mild to severe conditions, and even death (Huang et al., 2020; Kim,

2020; Ralph et al., 2020). Despite several research efforts, there are yet no specific antiviral medications and

vaccines available for fighting with COVID-19. Many ongoing clinical trials are currently being conducted to

identify the most propitious drug candidate against COVID-19. The most acclamatory way of identifying the

propitious drug candidates for COVID-19 depends on understanding the pathophysiology of SARS-CoV-2

(Guo et al., 2020).

The first step of attachment and entry of Coronaviruses is dependent on the binding of SARS-CoV-2 spike

glycoprotein (S2) to cellular receptors (Angiotensin converting enzyme 2, ACE2) of the host. Secondly, after

entry into the host cell, the virus starts replicating with the aid of viral nuclease (NSP15 endoribonuclease)

and protease (Main Protease 3CLpro). All these said viral virulence factors are vital for the viral life cycle

(Liu et al., 2020). Hence, unraveling the pathogenesis of these virulence factors might provide insights into

2

Posted on Authorea 31 Mar 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158567174.40895611 | This a preprint and has not been peer reviewed. Data may be preliminary.

the etiology of COVID-19 and reveal therapeutic targets (Fig. 1 ).

Although, the structure and sequence of these viral virulence factors are known and drug screening is

continuously being conducted by targeting these virulence factors. However, yet there are no approved

drugs for effectively managing COVID-19 infection. WHO has recently announced restricted use permission

for repurposed anti-HIV, anti-malarial, anti-flu and anti-Ebola drugs (Guo et al., 2020; Senathilake et al.,

2020). Considering such a considerable emergency of this outbreak, the current in silico study is aimed at

investigating the possibilities of a glucose anti-metabolite, 2-deoxy-D-glucose (2-DG) as a repurposed drug

for the treatment of novel SARS-CoV-2 virus. Post entry of virus, the host cells have been observed to

undergo metabolic reprogramming to meet the increased demand of nutrients and energy for replication of

the virus, wherein 2-DG might serve as a probable drug candidate as it acts as a dual inhibitor of glycolysis as

well as glycosylation (Gualdoni et al., 2018). 2-DG has already been granted permission for clinical trials, as

evidenced from previously published results (Mohanti et al., 1996; Vijayaraghavan et al., 2006; Dwarkanath

et al., 2009).

In the present study, the drug-like potential of 2-DG will be studied by targeting SARS-CoV-2 spike glyco-

protein (S2), viral nuclease (NSP15 endoribonuclease) and protease (Main Protease 3CLpro). The binding

mechanism of 2-DG with the said viral virulence factors will be assessed by means of in silico molecular

docking as well as pharmacophore modeling. Moreover, another tetra-acetate glucopyranose derivative of

2-DG (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose) has also been assessed for studying its binding

affinities with the said viral virulence factors. The rationale for selecting this tetra-acetate glucopyranose

derivative as probable antiviral drug is dependent on its activity of impairing glycolysis and glycosylation.

Hence, this derivative can possibly be used as a prodrug for 2-DG (Jeon et al., 2020; Pajak et al., 2020).

One such prodrug of 2-DG, namely, 3,6-di-O-acetyl-2-deoxy-d-glucose has been developed in Dr. Waldemar

Priebe’s laboratory. This compound is currently being tested as an antiviral drug for targeting the novel

Coronavirus (Priebe et al., 2018; Keith et al., 2019; Pajak et al., 2020). Similar plan of repositioning 2-

deoxy-D-glucose and 1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose has been presented in the present

study, wherein all the molecular interactions of 2-DG and 2-DG derivative have been compared with the

currently used anti-retroviral drugs, i.e. , lopinavir; anti-flu drug, i.e. , favipiravir; and anti-malarial drug,

i.e. , hydroxychloroquine. The detailed molecular interactions and probable modes of action of 2-DG and

its prodrug have also been discussed in the present manuscript.

2. Materials and Methods

Conduction of the present in silico study has been made possible by the assistance of several databases includ-

ing PubChem (https://pubchem.ncbi.nlm.nih.gov/), RCSB Protein Data Bank (https://www.rcsb.org/) and

Proteins Plus Server (https://proteins.plus/); and softwares like Argus lab (http://www.arguslab.com/arguslab.com/ArgusLab.html),

Molinspiration (https://www.molinspiration.com/), Open Babel (http://openbabel.org), Hex (http://hex.loria.fr/),

and Toxicity Estimation Software Tool (https://www.epa.gov/chemical-research/toxicity-estimation-software-

tool-test). PubChem is an open chemistry database that provides two-dimensional chemical information

about the ligands being used in this study (Butkiewicz et al., 2013). The RCSB Protein Data Bank is a

global archive of three-dimensional structural data of biomolecules, per say viral receptors in this study (Rose

et al., 2015). Proteins Plus server is a common online server for computational drug modeling, wherein one

of its counterparts, namely, Pose View is used to visualize receptor structures and create pose depictions of

ligand-receptor binding. Moreover, another counterpart of Proteins Plus server, namely, DoG Site Scorer is

used to predict the active binding sites and druggability of binding pockets of receptors (F¨ahrrolfes et al.,

2017; Volkamer et al., 2012). Argus lab is molecular modeling software which is mainly used to visualize

the receptors as well as ligands and customize both of them for docking (Joy et al., 2006). Molinspiration is

online chemiinformatics software focused on calculating the molecular properties of ligands and predicting

their bioactivity properties (Jarrahpour et al., 2012). OpenBabel is an open platform for inter-converting

chemical file formats, thereby aiding in converting the 2D structure of ligands to 3D pdb structure and

hence customizing them for molecular docking (Samdani & Vetrivel, 2018). Hex is an interactive molecular

docking program for calculating the binding energies of interaction between receptors and ligands (Ritchie &

3

Posted on Authorea 31 Mar 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158567174.40895611 — This a preprint and has not been peer reviewed. Data may be preliminary.

Venkatraman, 2010). Toxicity Estimation Software Tool is a Quantitative Structure Activity Relationships

(QSAR) which is used to estimate the toxicity of ligands based on the molecular descriptors of the ligands

(Barron et al., 2012).

2.1 Preparation of 3D structure of viral virulence factors as receptors

The crystal structures of SARS-CoV-2 spike glycoprotein (S2; PDB code: 6VSB), viral nuclease (NSP15

endoribonuclease; PDB code: 6VWW) and protease (Main Protease 3CLpro; PDB code: 1Q2W) were

obtained from RCSB Protein Data Bank (https://www.rcsb.org/). Hydrogen atoms were introduced in

all these 3D structures using Argus Lab (4.0.1), so as to customize the viral receptors for rigid docking

(http://www.arguslab.com/arguslab.com/ArgusLab.html).

2.2 Preparation of 3D structure of 2-DG and 2-DG derivative as ligands

The structure of 2-deoxy-D-glucose and 2-DG derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose)

were downloaded in xml format from PubChem database and structures were validated (Butkiewicz et

al., 2013). Hydrogen atoms were introduced into the ligands structure using Argus lab (4.0.1), so as to

customize them for rigid docking. The hydrogenated ligand molecules were then converted into pdb format

using Open Babel (2.4) interface (openbabel.org/docs/dev/OpenBabel.pdf), as required for rigid docking.

Similarly, 3D structures of standard chemotherapeutic agents (lopinavir, favipiravir, hydroxychloroquine)

were also customized for docking.

2.3 Active site analysis of viral virulence factors

DoG Site Scorer, a web based tool (https://proteins.plus/), was used to predict the possible binding sites

in the 3D structure of spike glycoprotein, viral nuclease and viral main protease. Predictions with DoG Site

Scorer were based on the difference of gaussian filter to detect potential pockets on the protein surfaces and

thereby splitting them into various sub-pockets. Subsequently, global properties, describing the size, shape

and chemical features of the predicted pockets were calculated so as to estimate simple score for each pocket,

based on a linear combination of three descriptors, i.e ., volume, hydrophobicity and enclosure. For each

queried input structure, a druggability score between 0-to-1 was obtained. Higher the druggability score,

higher the physiological relevance of the pocket as potential target (Volkamer et al., 2012).

2.4 Molecular Docking and Ligand Receptor Binding analysis

The docking analysis of pdb structures of 2-deoxyglucose and its analogue (1, 3, 4, 6-Tetra-O-acetyl-2-

deoxy-D-glucopyranose) with viral receptors (spike glycoprotein, viral nuclease and viral main protease) was

carried by Hex Cuda 8.0.0 software. Receptor and Ligand files were imported in the software (Harika et

al., 2017). The grid dimension of docking was defined according the to the binding site analysis of DoG

Site Scorer (Volkamer et al., 2012). Graphic settings and Docking parameters were customized so as to

calculate the binding energies (E values) of ligand receptor docking. The parameters used for the docking

process were set as (i) Correlation type: Shape + Electro + DARS, (ii) FFT mode: 3D fast lite, (iii) Grid

Dimension: 0.6, (iv) Receptor range: 180°, (v) Ligand range: 180°, (vi) Twist range: 360°. The best docked

conformations with lowest docking energy were selected for further MD simulations using Pose View for

creating pose depictions of selected ligand-receptor binding (Ezat et al., 2014). Molecular Docking and MD

simulations for the standard chemotherapeutic agents (lopinavir, favipiravir, hydroxychloroquine) were also

conducted. The MM-PBSA method was used to compute the binding free energy of receptor-ligand docking

during simulation. In this study, the binding free energy of the receptors to ligands was calculated using the

GROMACS tool, wherein the binding free energy of the receptor and ligand was defined as

ΔGbinding =ΔGcomplex – (ΔGreceptor +ΔGligand)

For each subunit, the free energy, G, can be presented as summation of mechanical potential energy (Elec-

trostatic and Vander Waals interaction) and solvation free energy (Gpolar + Gnonpolar ), wherein the total

entropy is excluded from the total value (Weis et al., 2006).

2.5 Molinspiration based Molecular property and Bioactivity analysis

4

Posted on Authorea 31 Mar 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158567174.40895611 — This a preprint and has not been peer reviewed. Data may be preliminary.

Molinspiration software was used to analyze molecular descriptors and bioactivity scores of the ligands and

standard chemotherapeutic agents, namely, MiLog P, Total polar surface area (TPSA), molecular weight,

number of atoms, number of rotatable bonds, number of hydrogen bond donors and acceptors. Bioactivity

of the ligands was also checked by using Molinspiration which can analyze the activity score of GPCR

ligands, kinase inhibitors, ion channel modulators, enzymes and nuclear receptors. Ligands were loaded in

the Molinspiration software in SMILES format and the molecular descriptor as well as bioactivity analysis

was conducted (Jarrahpour et al., 2012).

2.6 In silico Toxicity estimation

Ligands (2-DG and 2-DG derivative) and standard chemotherapeutic agents (lopinavir, favipiravir, and

hydroxychloroquine) were uploaded in the Toxicity Estimation Software Tool in sdf format. Oral rat LD50 ,

Bioconcentration Factor, Developmental Toxicity and Ames Mutagenicity were estimated using consensus

method of QSAR analysis (Barron et al., 2012).

3. Results & Discussion

3.1 Active site analysis

Active site analysis of SARS-CoV-2 spike glycoprotein (S2), viral nuclease (NSP15 endoribonuclease) and

protease (Main Protease 3CLpro) as conducted by DoG Site Scorer indicated that there are various active

pockets within the studied viral virulence factors with druggability ranging from 0.12 to 0.86 (Table 1 ).

It was found that pockets P 11 (Drug score: 0.847), P 1 (Drug score:0.860) and P 0 (Drug score: 0.805)

were energetically favourable for performing further molecular docking studies with the viral receptors being

spike glycoprotein, NSP15 endoribonuclease and Main Protease 3CLpro, respectively. While conducting the

active site analysis, the DoG Site Scorer tool analysed the heavy atom coordinates on the surface of the 3D

structure of the respective viral receptors. Depending on these atomic coordinates, a hypothetical grid was

spanned by outruling the chances of any spatial overlap of the grid with the heavy atoms. Furthermore, the

tool engages in applying a Gaussian filter to the defined grids, so as to identify spherical pockets of binding.

Druggability score (0-1) of the selected spherical pockets are deduced on the basis of their surface area,

volume, enclosure and hydrophobicity. As a general rule, higher druggability score is indicative of a more

druggable pocket (Volkamer et al., 2012). The most druggable pockets of SARS-CoV-2 spike glycoprotein,

NSP15 endoribonuclease and main protease 3CLpro have been elucidated inFig. 2 .

3.2 Molecular Docking

Docking results of the viral virulence factors, namely, spike glycoprotein, NSP15 endoribonuclease and

Main Protease 3CLpro; and the drug 2-deoxy-D-glucose (2-DG) as well as 2-DG derivative (1, 3, 4, 6-

Tetra-O-acetyl-2-deoxy-D-glucopyranose) are shown in Table 2 . These docking based E values have also

been compared with that of the standard drugs (lopinavir, favipiravir and hydroxychloroquine). The Hex

based docking results reveal that the E-value of docking of 2-DG with viral main protease 3CLpro (E

value2-DG + Protease = -140.05 Kcal/mol) was found to be better than that of the standard drug lopinavir (E

valueLopinavir + Protease = -124.00 Kcal/mol). Similarly, the docking of 2-DG with viral endoribonuclease also

yielded significantly better binding energies (E value2-DG + Endoribonuclease = -168.65 Kcal/mol) as compared

to that of the standard drug favipiravir (E valueFavipiravir + Endoribonuclease = -128.00 Kcal/mol). However, the

binding energy of 2-DG with that of spike glycoprotein (E value2-DG + Spike glycoprotein = -118.31 Kcal/mol)

was found to be moderately lower as compared to that of the tested standard drugs. It is obvious from the

E-values that 2-deoxy-D-glucose binds spontaneously and irreversibly to main protease 3CLpro and viral

endoribonuclease, wherein the binding efficiency of 2-DG has been found to be exceedingly better than

that of lopinavir and favipiravir. Such significant binding affinity of 2-DG with that of SARS-CoV-2 viral

receptors presumably indicates the probable mechanism of action of 2-deoxy-D-glucose as viral protease

and endoribonuclease inhibitor. Viral protease is fundamental for continuing the viral life cycle of SARS-

CoV-2 as it is required by the virus to catalyze the cleavage of viral polyprotein precursors which are

ultimately necessary for viral capsid formation and enzyme production (Anand et al., 2003). Similarly, viral

5

Posted on Authorea 31 Mar 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158567174.40895611 — This a preprint and has not been peer reviewed. Data may be preliminary.

endonucleases are necessary for catalyzing the processing of viral RNAs and hence are required for enduring

the process of viral replication (Ward et al., 2020). Henceforth, the 2-deoxy-D-glucose moiety contingently

inactivates the viral protease, thereby inhibiting the process of viral capsid formation. Furthermore, 2-DG

may also be responsible for withholding the action of viral endoribonuclease, thereby halting the process of

viral replication altogether.

Moreover, the 2-DG derivative, namely, 1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose also showed an

increase in the free energy of the complex with the viral receptors. The E-value of docking of 2-DG derivative

with viral main protease 3CLpro (E value2-DG derivative + Protease = -187.64 Kcal/mol) was found to be better

than that of the standard drug lopinavir (E valueLopinavir + Protease = -124.00 Kcal/mol). Similarly, the

docking of 2-DG derivative with viral endoribonuclease (E value2-DG derivative + Endoribonuclease = -208.33

Kcal/mol) as well as spike glycoprotein (E value2-DG derivative + Spike glycoprotein = -173.89 Kcal/mol) yielded

significantly better results as compared to that of favipiravir, wherein its E value is lower in both cases, i.e.

, E valueFavipiravir + Endoribonuclease = -128.00 Kcal/mol; and E valueFavipiravir + Spike glycoprotein = -118.31

Kcal/mol. The 2-DG derivative exhibited significantly better binding values as compared to that of 2-DG

itself. The derivative displayed spontaneous binding efficiencies while docking with viral protease, viral

endonuclease and spike glycoprotein. The binding energy of 2-DG derivative was found to be comparable to

that of hydroxychloroquine which has been proposed as the cornerstone for COVID-19 therapy. Hence, 1, 3, 4,

6-Tetra-O-acetyl-2-deoxy-D-glucopyranose could presumably mitigate the virus completely as it could restrict

viral entry into the host cell by inactivating the spike glycoprotein; halt viral capsid formation by inactivating

the viral main protease; and cease viral replication by inactivating the viral endoribonuclease. Earlier

studies have also indicated that glucopyranose derivatives are glycolysis inhibitors and cause mitochondrial

oxidative phosphorylation, thereby indicating a probable antiviral role of 1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-

D-glucopyranose (Jeon et al., 2020).

3.3 Ligand Receptor binding pose depictions

The best docking pose of 2-DG, and its derivatives with SARS-CoV-2 viral receptors was also identified

using Pose View tool so as to visualize the interactions of the ligands with that of the residues present in

the active sites of the viral receptors. Both 2-deoxy-D-glucose and its derivative were found to form salt

bridges with the amino acid residues of the viral receptors, namely, main protease 3CLpro and viral spike

glycoprotein, respectively. The orientational binding of the ligands and the viral receptors showing the pose

view and residue interactions have been depicted in Fig. 3 . It was observed that the hydroxyl group of

2-deoxy-D-glucose formed a hydrogen bond with the carbonyl residue of Proline amino acid (108th position)

found in the viral main protease. In earlier studies it has been found that the proline amino acid residues

are found in the conserved domains of HIV viral infectivity factor (Vif) and these proline-rich motifs are

therapeutic targets for neutralizing the human immunodeficiency virus (Yang et al., 2003; Ralph et al.,

2020). Chemical bridging of 2-deoxy-D-glucose and proline residues of viral main protease 3CLpro present

a similar case where proline residues were invariably bound and neutralized, thereby possibly neutralizing

the COVID-19 virus. Similarly, the 2-DG derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose)

formed a hydrogen bond with the amide group of Glutamine amino acid (804thposition) found in the viral

spike glycoprotein. Reynard and Volchkov have also previously highlighted that mutation or any change in

the glutamine residues of Ebola virus spike glycoprotein causes viral neutralization (Reynard & Volchkov,

2015). In conclusion, the binding interactions of 2-deoxy-D-glucose with viral main protease and 1, 3, 4,

6-Tetra-O-acetyl-2-deoxy-D-glucopyranose with viral spike glycoprotein is now evident, as analysed by using

Pose View tool.

2-deoxy-D-glucose and its derivative can influence several cellular pathways, including glycolysis, glycosyla-

tion, endoplasmic stress response (ER), phagocytosis and apoptosis. Both the moieties inhibit the processes

of glucose transport and glycolysis by competing with glucose. Competitive uptake of 2-DG or its deriva-

tive in the infected cell leads to the formation of 2-deoxy-d-glucose-6-phosphate (2-DG-6-P) by means of

hexokinase enzyme. 2-DG-6-P cannot be further metabolized, thereby hampering the bioenergetic process

of ATP production by glycolysis (Sharma et al., 1996); inactivating the glycolytic enzymes; inducing cell

6

Posted on Authorea 31 Mar 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158567174.40895611 — This a preprint and has not been peer reviewed. Data may be preliminary.

cycle arrest and ultimately leading to inactivation of nCoV-19 in infected cells (Maher et al., 2004; Pajak

et al., 2020). The depletion of ATP levels leads to activation of AMP-activated protein kinase (AMPK).

Such activation will lead to phosphorylation of proteins of the mTOR kinase complex (mammalian target of

rapamycin kinase, mTORC). As a consequence, expression of p53 is induced which ultimately promotes cell

cycle arrest (G1 phase arrest) in virus infected cells. All these factors (glycolysis inhibition, ATP depletion

and cell cycle arrest) cause a sensitized response leading to the upregulation of TNF expression, ultimately

leading to an apoptotic response. Moreover, both 2-DG and its tetra-acetate glucopyranose derivative es-

calate the production of reactive oxygen species, ultimately leading to virus infected cell death (Fig. 4 )

(Zhang et al., 2015; Pajak et al., 2020).

3.4 Molecular property analysis

After analyzing the binding energies and ligand-receptor binding pose depictions, it was requisite to evaluate

the drug likeliness of the ligands. Analysis of molecular descriptors is necessary in elucidating the pharma-

cokinetic parameters of the drugs such as absorption, distribution, metabolism, and excretion. Molinspiration

software was used to analyze the Lipinski Rule of Five, including the Log P value (partition coefficient),

molecular weight, polar surface area, number of hydrogen bond donor and number of hydrogen bond accep-

tor. According to the Lipinski’s rule, a drug like moiety should have a low molecular weight ([?] 500 D), log P

value [?] 5, number of hydrogen bond acceptors [?]10, and number of hydrogen bond donors [?]5. A bioactive

druggable molecule should ensue to at least 4 of the 5 Lipinski rules (Zhang & Wilkinson, 2007). In the

present study, it was found that 2-deoxy-D-glucose and 1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose

befalls within the said permissible limits of Lipinski rules and hence, both these drugs can be said to possess

satisfactory oral bioavailability (Table 3 ).

3.5 Bioactivity analysis

Molinspiration was used to virtually screen the biological activity of drug moieties, per say 2-DG and 2-

DG derivative in the present study. The fundamental principle behind this in silico bioactivity screening

is the identification of substructure(s) responsible for endowing pharmacological features (GPCR binding

ability, ion channel modulation potential, kinase inhibition activity, nuclear receptor binding potential, and

protease inhibition) to the drug molecules being studied. The bioactivity score of the ligands and standard

chemosynthetic moieties is presented in Table 4 . In general, if the bioactivity score for a particular target is

more than 0.0, then the said drug moiety is considered to be highly active. Additionally, a bioactivity score

of a ligand lying between -5.0 and 0.0 is considered to be moderately active. However, bioactivity scores

of ligands below -5.0 render it to be inactive (Singh et al., 2013). As observed in Table 4, the bioactivity

scores of 2-DG for most of the bioactivity descriptors were below -0.5, thereby indicating its inactivity

towards those targets. However, 2-DG possessed moderate bioactivity as ion channel modulator (Bioactivity

score Ion channel modulator ˜ -0.14) and protease inhibitor (Bioactivity score Protease inhibitor ˜ -0.37). This

bioactivity score of 2-DG is in corroboration with the molecular docking results which also suggest 2-DG to

be a significant protease inhibitor (E 2-DG + Protease = -140.05 Kcal/mol). The antiviral effect of 2-DG has

also been recognized in previous studies. Inhibition of multiplication has been reported for some enveloped

viruses such as influenza virus, sindbis virus, semliki forest virus, herpes simplex virus, respiratory syncytial

virus and measles virus (Kang & Hwang, 2006; Krol et al., 2017). Furthermore, 2-DG eliminated genital

herpes from most of the tested patients. It also alleviated the severity of infection of calves with respiratory

syncytial virus and infectious of bovine rhino-tracheitis virus (Leung et al., 2012). According to all these

earlier studies, inhibition of viral envelope biosynthesis and virion assembly due to blocked glycosylation

of membrane proteins appears to be the major mechanism of 2-DG for virus attenuation. This has been

supported by altered gel electrophoresis profiles of membrane proteins as well as denuded appearance of

budding particles shown by electron microscopy. Studies also suggest that 2- DG can also suppress viral

gene expression or viral replication (Camarasa et al., 1986; Kang & Hwang, 2006; Leung et al., 2012; Krol

et al., 2017).

Furthermore, the bioactivity score of 2-DG derivative (1, 3, 4, 6-Tetra-O-acetyl-2-deoxy-D-glucopyranose)

suggested that it mainly acts as a GPCR ligand (Bioactivity score GPCR ligand˜ 0.13), ion channel modulator

7

Citations (1)

References (52)

… 2-deoxy-D-glucose (2-DG): A glucose analogue, 2-deoxy-D-glucose, is believed to have profound effects on a range of diseases such as cancer, viral infection and ageing-related morbidity 28 . Recent in vitro studies suggest the potential benefits of using 2-DG to mitigate COVID-19 infection 29,30 . A Phase 2 trial to determine the safety and efficacy of the drug as an adjunctive therapy to standard of care in patients with moderate-to-severe COVID-19 is underway at 12 sites (CTRI/2020/06/025664). …

Emerging trends from COVID-19 research registered in the Clinical Trials Registry – India

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