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Posted on Authorea 31 Mar 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158567174.40895611 | This a preprint and has not been peer reviewed.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