Umar et al. Journal of Genetic Engineering and Biotechnology
https://doi.org/10.1186/s43141-021-00120-7
(2021) 19:16
RESEARCH
Journal of Genetic Engineering
and Biotechnology
Open Access
Molecular docking studies of some selected
gallic acid derivatives against five nonstructural proteins of novel coronavirus
Haruna Isiyaku Umar1,2* , Bushra Siraj2,3, Adeola Ajayi1, Tajudeen O. Jimoh4,5 and Prosper Obed Chukwuemeka6
Abstract
Background: The World Health Organization has recently declared a new coronavirus disease (COVID-19) a
pandemic and a global health emergency. The pressure to produce drugs and vaccines against the ongoing
pandemic has resulted in the use of some drugs such as azithromycin, chloroquine (sulfate and phosphate),
hydroxychloroquine, dexamethasone, favipiravir, remdesivir, ribavirin, ivermectin, and lopinavir/ritonavir. However,
reports from some of the clinical trials with these drugs have proved detrimental on some COVID-19 infected
patients with side effects more of which cardiomyopathy, cardiotoxicity, nephrotoxicity, macular retinopathy, and
hepatotoxicity have been recently reported. Realizing the need for potent and harmless therapeutic compounds to
combat COVID-19, we attempted in this study to find promising therapeutic compounds against the imminent
threat of this virus. In this current study, 16 derivatives of gallic acid were docked against five selected nonstructural proteins of SARS-COV-2 known to be a good target for finding small molecule inhibitors against the virus,
namely, nsp3, nsp5, nsp12, nsp13, and nsp14. All the protein crystal structures and 3D structures of the small
molecules (16 gallic acid derivatives and 3 control drugs) were retrieved from the Protein database (PDB) and
PubChem server respectively. The compounds with lower binding energy than the control drugs were selected and
subjected to pharmacokinetics screening using AdmetSAR server.
Results: 4-O-(6-galloylglucoside) gave binding energy values of − 8.4, − 6.8, − 8.9, − 9.1, and − 7.5 kcal/mol against
Mpro, nsp3, nsp12, nsp13, and nsp15 respectively. Based on the ADMET profile, 4-O-(6-galloylglucoside) was found
to be metabolized by the liver and has a very high plasma protein binding.
Conclusion: The result of this study revealed that 4-O-(6-galloylglucoside) could be a promising inhibitor against
these SAR-Cov-2 proteins. However, there is still a need for further molecular dynamic simulation, in vivo and
in vitro studies to support these findings.
Keywords: In silico, Novel coronavirus, Druglikeness, Gallic acid derivatives, Molecular docking, SARS-COV-2, Nonstructural proteins, Molecular interactions, Binding energy
* Correspondence: ariwajoye3@gmail.com
1
Department of Biochemistry, School of Sciences, Federal University of
Technology, Along Owo-Ilesha Express Way, P.M.B. 704, Akure, Ondo State,
Nigeria
2
Ioncure Tech Pvt. Ltd., Delhi 110085, India
Full list of author information is available at the end of the article
© The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if
changes were made. The images or other third party material in this article are included in the article's Creative Commons
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licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Umar et al. Journal of Genetic Engineering and Biotechnology
(2021) 19:16
Background
The World Health Organization has declared the most
recent coronavirus (COVID-19) a pandemic and a global
emergency that causes a global outbreak since early this
year after emerging from Wuhan, Hubei province of
China in late December of 2019 [1, 2]. This viral disease
is caused by severe acute respiratory syndrome 2 (SARSCOV-2); a spherical-shaped, single-stranded, positively
sensed RNA virus with a genome size of approximately
30,000 base pairs consisting of about eleven open reading frames (ORFs) that encodes numerous proteins
(structural and non-structural) involved in the viral life
cycle [2–4]. The proteins result from the expression of
the viral mRNA and sgRNAs subsequent to its entry into
the host cell via the priming of the viral spike glycoprotein to angiotensin-converting enzyme 2 (ACE2). The
binding of the viral spike glycoprotein to angiotensinconverting enzyme 2 (ACE2) receptor mediates the viral
infectivity, hence, serving as the basis for pathogenicity
in its host. Once the virus gains entry into the host cell,
it liberates its RNA into the cytoplasm subsequently
resulting in the translation of its replicase gene. Within
the viral replicase gene are two overlapping open reading
frames flagged ORF1a/1b. The translation of the ORFs
results into polyprotein1a and 1ab. The two polyproteins
are subsequently cleaved by two cysteine proteinases
called main protease or 3-chymotrypsin-like protease
(Mpro/3CLpro) and papain-like protease (PLpro) releasing 16 non-structural proteins (nsp1 to 16). Among
these nsps are the papain-like protease (nsp3), main protease (nsp5), RNA-dependent RNA polymerase (RdRp/
nsp12), helicase (nsp13), and nsp15 (NendoU) which
have been viewed to be viable antiviral drug targets [4,
5].
Papain-like protease (PLpro) is involved in cleavage at
the N-terminus of replicase polyproteins to release nsp1,
nsp2, and nsp3, also generating replicase complex to
allow viral spread [5, 6]. This enzyme is a multifunctional one; aside from polyproteins processing, maturation, and forming replication-transcription complex, it
interferes with the host anti-viral immune response by
modifying host cellular proteins of immune relevance
after their translation [5, 7]. Then, the main protease
otherwise called nsp5, cleaved itself from the polyproteins and then cleaved the same polyproteins on 11 distinct sites yielding nsp4 to nsp16 [5, 8]. Interestingly,
this process leads to the maturity of the nsps [5, 8]. Also,
RNA-dependent RNA polymerase (RdRp/nsp12) is an
enzyme of high pertinence that involves in the synthesis
of complementary RNA strands with the aid of other
nsps such as nsp7 and nsp8 playing a critical role in replication and transcription of the virus [4, 5, 9]. Helicase
(nsp13) as well, unwinds the duplex RNA, and also adds
a 5′-terminal cap to the viral RNA, thus allowing its
Page 2 of 14
recognition for translation and playing a key role in nuclear export, stability, and splicing of the viral mRNA [4,
9]. Finally, Nsp15 (NendoU or EndoU) is an endonuclease that prevents the host immune apparatus to detect
the virus via viral RNA cleavage and degradation at the
polyuridine sequence region, thereby forming 2′-3′cyclic
phosphodiester product [3, 4, 10].
Due to the worldwide outbreak of COVID-19,
pharmaceutical companies, government institutions, private organizations, and biotechnological firms are under
burdened to produce drugs and vaccines against the ongoing pandemic. As a result, drugs such as azithromycin,
chloroquine (sulfate and phosphate), hydroxychloroquine,
dexamethasone,
favipiravir,
remdesivir,
interferon-alpha, ribavirin, sofospuvir, ivermectin, and
lopinavir/ritonavir have been compassionately used for
treatment [11]. Even though significant data are available
from clinical randomized trials that could give clear-cut
clinical guidance on their use, dosage, or time for treatment or prophylaxis [12], there were several reports on
the side effects of these therapies on COVID-19 patients
more of which cardiomyopathy, cardiotoxicity, nephrotoxicity, macular retinopathy, and hepatotoxicity [12–14]
are the prominent ones. Thus, this has prompted the
quest for better and readily available options to thwart
this viral malady.
Gallic acid (GA) and its derivatives are one of the
abundant plant chemicals with diverse pharmacological
aptitudes that can aid in the management of several diseases such as inflammatory, cardiovascular, respiratory,
gastrointestinal, and metabolic diseases [15, 16]. Our
interest in gallic acid derivatives were based on their
pharmacological aptitudes, abundance in nature, and
most of all, had not been used for any study to evaluate
them against the etiological agent of the recent coronavirus outbreak. Although there are numerous studies on
gallic acid and its derivatives against different diseases
such as antibacterial, antifungal, and antiviral diseases
[17, 18]; nonetheless, no study has reported its use as a
therapeutic compound against COVID-19. The derivatives of gallic acid include propyl gallate, lauryl gallate,
octyl gallate, theaflavin, tannic acid, (−)-epigallocatechin
gallate (EGCG), (−)-epigallocatechin (EGC), (−)-epicatechin gallate (ECG), and (+)-epicatechin (EC) [18, 19].
Realizing the uniqueness of its potentials to treat various
diseases, we have considered a subset of its derivatives in
this study to understand their mechanistic as inhibitors
against the aforementioned viral non-structural proteins
via various computational approaches. However, recent
studies have revealed the relevance of in silico techniques to find newer and potential therapeutics in drug
discovery and development [20–23]. Thus, an alternative
novel evidence based on a molecular docking approach
could become dexterous to the advancement of novel
Umar et al. Journal of Genetic Engineering and Biotechnology
(2021) 19:16
drug for the management/treatment of this on-going
pandemic. In this study, molecular docking was
employed to evaluate some selected gallic acid derivatives as antiviral aptitude against SARS-COV-2. We
looked into their binding energies (kcal/mol) and molecular interactions with five key important proteins/enzymes of SARS-COV-2, namely, nsp3, nsp5, nsp12,
nsp13, and nsp14. Also, we evaluated the pharmacoactivities of the best hit compounds after the docking experiment in silico.
Methods
Materials used for the in silico study
The softwares used to execute this present in silico work
are Python Prescription 0.8 (PyRx) used for optimizing
ligands and for molecular docking since it abhors AutoDock Vina module; UCSF-Chimera© (version 1.13) software used for protein target preparation for docking;
PyMol Molecular Graphic system version 2.4.1 used for
preparing protein-ligand complexes after docking and
for 3D visualization; and Discovery Studio 2016 and LigPlot+ were used for 2D visualization of protein-ligand
complexes. All softwares were run on a personal computer, HP brand with a processor of Intel (R) Celeron
(R) CPU N3060 @ 1.6GHz, 4GB RAM, and 500GB hard
disk.
Selection and optimization of ligands
Gallic acid and fifteen (15) derivatives of gallic acid were
selected with three (3) control drugs approved globally
to combat COVID-19 (dexamethasone, hydroxychloroquine, and remdesivir). Three-dimensional (3D) structures of these ligands were retrieved from PubChem
server (https://pubchem.ncbi.nlm.nih.gov/compound) in
simple data format (SDF) and were optimized using
Open babel in PyRx (version 0.8) which converted the ligands energetically to the most stable structures using
merk molecular force field 94 (MMFF94).
Drug likeness screening of ligands
The drug likeliness of all the ligands was assessed by the
Lipinski’s rule of five parameters (molecular weight <
500 Da, no more than 5 hydrogen bond donors, no. of
hydrogen bond acceptors should be less than 10, and
AlogP should not be greater than 5). The Lipinski’s rule
of five parameters were obtained from the ADMETSar
server [24]. Physicochemical properties and toxicity risks
assessment prediction was done via the OSIRIS property
explorer software (https://www.organic-chemistry.org/
prog/peo/). This was done by uploading the respective
compounds’ SMILES into the web server and software.
Page 3 of 14
Protein targets selection and preparation
Main protease (Mpro/nsp5), papain-like protease (Plp/
nsp3), RNA-dependent RNA polymerase (RdRp/nsp12),
helicase (nsp13), and uridylate-specific endoribonuclease
(NendoU/nsp15) of SARS CoV 2 were selected for this
study. The 3D crystal structures of the receptors were
retrieved from the Protein Data Bank (PDB) (www.pdb.
org/pdb) with PDB IDs of 6 LU7 [8], 6W9C [7], 6 M71
[25], 6XEZ [9], and 6VWW [10] respectively. Chain A of
the protein receptors was selected and cleaned from heteroatoms, then prepared for docking using the Dock
preparation tool of UCSF-Chimera© (version 1.13) software (http://www.cgl.ucsf.edu/chimera). The receptors
were minimized base on the AMBER force field in
UCSF-Chimera software setting the steepest gradient to
100 and conjugated gradient to 10 [26].
In silico docking protocol validation
Validation of the docking protocol was carried out to
substantiate the exactness and dependability of the docking results. The purpose is to correctly reproduce the
binding model and the molecular interaction of the cocrystalized ligand of the experimentally crystalized protein structures in this present in silico studies. Accordingly, the native ligands of all the X-ray proteins were
separated from the protein and then prepared for docking via UCSF-Chimera [26]. The ligands were subsequently docked back into the receptors’ active sites
using the Auto Dock Vina module of PyRx. The docked
complexes were aligned with the X-rayed resolved crystals of proteins bearing the co-crystalized ligand to produce the root mean square deviation (RMSD) value
using PyMOL molecular visualizer and also viewing the
molecular interactions that results using LigPlot+ [27].
Molecular docking
The molecular docking was executed using a flexible
docking protocol as described by Trott and Olson [28]
with slight modifications. Accordingly, Python Prescription 0.8, a suite comprising of Auto Dock Vina, was utilized for the molecular docking analysis of the selected
ligands with our target proteins. The protein data bank,
partial charge, and atom type (PDBQT) files of the proteins were generated (using their previously created PDB
files as inputs). All other parameters were kept as default
except for the grid box which was adjusted base on the
active sites of each protein molecule (see Table 1), and
all bonds contained in ligand were allowed to rotate
freely, making the receptor rigid [28]. Once the molecular docking experiments were completed and 10 configurations for each protein-ligand complex were generated
for all the phytocompounds, text files of scoring results
were also produced for the purpose of manual comparative analysis. The lowest binding energy (BE, kcal/mol)
Umar et al. Journal of Genetic Engineering and Biotechnology
Page 4 of 14
(2021) 19:16
Table 1 Grid box parameters selected and active site of the target proteins
S/ Target proteins
N
Center grid
box (XYZ), Å
Dimension
(XYZ), Å
Active site amino acid residues
1. Papain-like protease, Nsp3 (PDB ID:
6W9C)
− 39.05 ×
39.62 × 32.04
33.50 ×
28.55 ×
29.87
Cys111, His272, Asp286, Gly286, Trp106, Gly271, His73, Arg140, and
Asn109 [7]
2. Main protease, Nsp5 (PDB ID: 6 LU7)
−14.85 ×
14.923 ×
69.59
25.02 ×
27.98 ×
30.87
Thr25, Cys44, Thr26, His41, Met49, Tyr54, Phe140, Leu141, Gly143,
Cys145, Asn142, His163, His164, Met165, Ser144, Glu166, Pro168, His172,
Val186, Asp187, Arg188, Gln189, Phe185, Thr190, and Gln192 [29]
3. RNA-Dependent RNA polymerase,
Nsp12 (PDB ID: 6 M71)
123.944 ×
136.894 ×
128.548
20.84 ×
18.27 ×
25.00
Asp618, Ser759, Asp760, and Asp761 [25]
4. Helicase, Nsp13 (PDB ID: 6XEZ)
−13.89 ×
15.19 ×
−73.25
29.92 ×
25.83 ×
24.80
Lys288, Ser289, Asp374, Glu375, Gln404, and Arg567 [9]
5. Nidoviral Uridylate-specific endoribonu- − 91.15 ×
21.86 ×
clease, NendoU, Nsps15 (PDB ID:
−30.63
6VWW)
20.62 ×
25.00 ×
24.23
His235, His250, Lys290, Thr341, Thr343, and Ser294 [10]
and root mean square deviation (RMSD) conformation
was considered as the most suitable docking pose.
Throughout this in silico investigation, an exhaustiveness of 10 was used for docking, and the number of
modes set to 10 so as to achieve more accurate and reliable results. The interaction between ligands and proteins was then prepared, visualized, and analyzed using
PyMOL and Discovery Studio 2016 respectively [1, 30].
ADMET prediction
ADMET (Adsorption, Distribution, Metabolism, Excretion, and Toxicity) is important to analyze the pharmacodynamics of the proposed molecule which could be
used as a drug. ADMETSar and SWISSADME servers
were used to predict the ADMET properties of the compounds with the best hits after molecular docking analysis [24, 31, 32]. SMILES of the ligands from PubChem
Table 2 Druglikeness prediction according to Lipinski’s rule of gallic acid and its derivatives using the admetSAR server
S/
N
Compounds
Molecular weight (<
500)
AlogP (<
5)
H-Bond acceptor (<
10)
H-Bond donor (<
5)
Violations
1.
3-O-β-D-Glucopyranoside (3-glucogallic
acid)
332.26
− 2.03
9
7
1
2.
3-O-(6-Galloylglucoside)
484.37
−1.04
13
9
2
3.
3-O-Dodecanoyl (3-lauroylgallic acid)
352.43
4.62
5
3
0
4.
3-O-Methyl gallic acid
184.15
0.80
4
3
0
5.
4-O-(6-Galloylglucoside)
484.37
−1.04
13
9
2
6.
4-O-Methyl gallic acid
184.15
0.80
4
3
0
7.
Epicatechin gallate
458.38
2.23
11
8
2
8.
Epicatechin
290.27
1.55
6
5
0
9.
Epigallocatechin gallate
458.38
2.23
11
8
2
10.
Epigallocatechin
306.27
1.25
7
6
1
11.
Gallic acid
170.12
0.50
4
4
0
12.
Lauryl gallate
338.44
4.88
5
3
0
13.
Octyl gallate
282.34
3.32
5
3
0
14.
Propyl gallate
212.20
1.37
5
3
0
15.
Pyrogallol
126.11
0.80
3
3
0
16.
Resorcinol
110.11
1.10
2
2
0
17.
Dexamethasone
392.47
1.90
5
3
0
18.
Hydroxychloroquine
335.88
3.78
4
2
0
19.
Remdesivir
602.59
2.31
13
4
2
Control drugs
Umar et al. Journal of Genetic Engineering and Biotechnology
Page 5 of 14
(2021) 19:16
compounds showed good solubility between −0.63 and −
4.99. Eight compounds were predicted to have poor druglikeness properties; whereas four showed very low drug
scores (below 0.20). The toxicity risk assessment shows
that gallic acid, propyl gallate, pyrogallol, resorcinol, and
remdesivir pose a toxicity risk.
(https://pubchem.ncbi.nlm.nih.gov/compound/)
were
uploaded onto the search bar of the servers and were
predicted.
Results and discussion
Druglikeness, physicochemical properties, and toxicity
risk assessments
The results of the druglikeness of the ligands selected
for this work are presented in Table 2. The molecular
weight of the compounds was found to be within the acceptable range except remdesivir with MW 602.59. None
of the compounds had a lipophilicity value above 5. Five
molecules exceed the number of hydrogen bond acceptors required. In the same vein, six compounds exceeded
the acceptable limit for the number of hydrogen bond
donors. Finally, two compounds violate the rule while
five compounds violated two parameters.
In addition, the physicochemical and toxicity risk assessments were carried out using OSIRIS property explorer. The results are presented in Table 3 with
parameters such as solubility, topological surface area
(TPSA), druglikeness, drug score, mutagenicity, tumorigenicity, reproductive effect, and irritation. All
Molecular docking analysis
Prior to docking, our docking protocol was validated for
all target receptors as explained in the “Method” section.
This crucial step was carried out in other to provide
guarantees of the molecular docking protocols and softwares to accurately deliver correct binding signatures
with quality molecular interactions between target receptors and the compounds investigated in this in silico
study. The outcome of this exercise is depicted in Figs.
2a, 3, 4, 5, and 6a. This exercise was adjudged to be successful since the docked complexes reproduced the original poses as the native ligands precisely (Figs. 2a, 3, 4,
5, and 6a) with RMSD values of 0.000 Å, 0.533 Å, 0.605
Å, 2.298 Å, and 0.208 Å for Mpro, PLpro, RdRp, helicase,
and NendoU respectively. In this present docking work,
sixteen ligands (thirteen gallic acid derivatives and three
Table 3 Physicochemical properties and toxicity risks assessment employing the OSIRIS Property Explorer (https://www.organicchemistry.org/prog/peo/)
S.
no
Compounds
Solubility
(Log S)
TPSA
(Å)
Druglikeness Drug
score
1
3-O-β-D-Glucopyranoside (3glucogallic acid)
−0.63
177.1
−3.44
2
3-O-(6-Galloylglucoside)
−1.32
243.9
1.77
0.71
No
No
No
No
3
3-O-Dodecanoyl (3-lauroylgallic
acid)
− 4.04
104.0
−25.23
0.3
No
No
No
No
4
3-O-Methyl gallic acid
−1.06
86.99
1.1
0.85
No
No
No
No
5
4-O-(6-Galloylglucoside)
−1.32
243.9
1.99
0.72
No
No
No
No
6
4-O-Methyl gallic acid
−1.05
86.99
1.24
0.69
No
Medium risk
No
No
7
Epicatechin gallate
−2.16
197.3
1.58
0.7
No
No
No
No
8
Epicatechin
−1.76
110.3
1.92
0.87
No
No
No
No
9
Epigallocatechin gallate
−2.16
197.3
1.58
0.7
No
No
No
No
10
Epigallocatechin
−1.47
130.60
1.10
0.82
No
No
No
No
11
Gallic acid
−0.74
97.99
0.12
0.27
Yes
No
Yes
No
12
Lauryl gallate
−3.87
86.99
−20.89
0.28
No
No
No
No
13
Octyl gallate
−2.79
86.99
−20.89
0.25
No
No
No
Yes
0.48
Mutagenic Tumorigenic Reproductive
effect
Irritants
No
No
No
No
14
Propyl gallate
−1.44
86.99
0.54
0.17
Yes
Yes
Yes
No
15
Pyrogallol
−0.73
60.69
−3.5
0.07
Yes
Yes
Yes
Yes
Resorcinol
−1.02
40.46
− 1.94
0.12
Yes
Yes
No
Yes
16
Control drugs
17
Dexamethasone
−3.25
94.83
3.18
0.8
No
No
No
No
18
Hydroxychloroquine
−3.55
48.39
6.54
0.48
Yes
No
No
No
19
Remdesivir
−4.99
213.30
−30.39
0.05
No
Yes
Yes
Yes
Solubility, ranging 0 (highly soluble) to −6 (poorly soluble); TPSA, topological polar surface area ≤ 130 Å2; druglikeness, scores with positive value are likely to be
an oral drug; drug score, 0-1.0
Umar et al. Journal of Genetic Engineering and Biotechnology
Page 6 of 14
(2021) 19:16
Table 4 Binding energies of Ligands docked against Mpro, Plp, RdRp, helicase, and NendoU of SARS-Cov-2
S.
No.
Ligands
1.
Binding affinity (kcal/mol)
NSP5/MPro
NSP3/PLp
NSP12/RdRp
NSP13/Helicase
NSP15/NendoU
4-O-(6-Galloylglucoside)
−7.8
−6.8
−8.9
−9.1
−7.5
2.
Epigallocatechin-gallate
−7.7
−5.9
−8.5
−8.5
−6.9
3.
3-O-(6-Galloylglucoside)
−8.4
−6.6
− 8.4
− 9.0
− 6.8
4.
Epicatechin-gallate
− 8.4
− 6.1
− 8.3
− 8.4
− 7.2
5.
3-Glucogallic-acid
− 6.7
− 5.6
− 7.1
− 7.9
− 7.0
6.
Epicatechin
− 7.1
−6.0
− 7.1
− 7.6
− 6.8
7.
Epigallocatechin
− 6.9
− 5.7
− 7.1
-7.3
− 6.7
8.
3-O-Methyl-gallic-acid
−5.4
−4.8
− 6.2
− 6.1
− 5.2
9.
Gallic-acid
− 5.6
−4.6
− 5.9
− 5.9
−5.0
10.
3-O-Dodecanoyl(3-lauroylgallic-acid)
−5.3
−4.5
−5.8
− 6.4
− 5.7
11.
Lauryl-gallate
− 5.4
−4.1
− 5.5
− 6.1
−5.5
12.
Octyl gallate
−5.8
−5.0
− 5.1
− 6.6
−5.7
13.
4-o-Methylgallic-acid
−5.1
−4.6
−5.0
− 6.0
− 5.1
−6.8
−6.4
−7.5
− 8.0
− 7.1
Control drugs
14.
Dexamethasone
15.
Remdesivir
−7.9
−6.5
− 7.3
− 7.4
− 6.7
16.
Hydroxychloroquine
− 6.3
−5.0
−6.1
− 6.8
− 5.8
Fig. 1 Structures of SARS COV 2 proteins with their respective binding site. (a) Main protease (3CL-protease), (b) papain-like protease, (c) RdRp, (d)
helicase and NendoU. Sourced from Mirza and Froeyen (2020) Structural elucidation of SARS-CoV-2 vital proteins. https://doi.org/10.1016/j.jpha.
2020.04.008 and Kim et al (2020)
Umar et al. Journal of Genetic Engineering and Biotechnology
(2021) 19:16
control drugs) were docked against five protein targets
in SARS-Cov-2, namely, Mpro, PLp, RdRp, helicase/
nsp13, and NendoU Autodock Vina module in-built in
Python Prescription suit according to Trott and Olson
[28]. The binding energies (BE) that results after the
docking experiment are provided in Table 4.
After the docking was completed, the least binding energy (BE, kcal/mol) and root mean square deviation
(RMSD) conformation was considered as the most suitable docking pose of the compounds as presented in
Table 4. 3-O-(6-Galloylglucoside) (3O6G) and epicatechin gallate (ECG) produced the least BE of −8.4 kcal/
mol when docked with Mpro. Similarly, 3-O-(6-galloylglucoside) and its isomer, 4-O-(6-galloylglucoside)
(4O6G) yielded the least BE of −6.8 and −6.6 kcal/mol
respectively with PLp. Also, 4-O-(6-galloylglucoside)
show the least BE of −8.9, −9.1, and −7.5 kcal/mol when
docked with RdRp, nsp13, and NendoU respectively.
Molecular interaction analysis
In this current in silico study, gallic acid derivatives were
docked against Mpro using Auto Dock Vina. The Mpro
used for this investigation was retrieved in its 3D crystal
structure (6 LU7), co-crystallized with an inhibitor Nleucinamide, resolved at 2.16 Å, sequence length of 306,
and a homodimeric protein [29]. The binding site of
Mpro is surrounded by 25 amino acids such as Thr25,
Cys44, Thr26, His41, Met49, Tyr54, Phe140, Leu141,
Gly143, Cys145, Asn142, His163, His164, Met165,
Ser144, Glu166, Pro168, His172, Val186, Asp187,
Arg188, Gln189, Phe185, Thr190, and Gln192. Also, the
Page 7 of 14
binding site shows a CysHis (Cys145 and His41) catalytic
dyad [29, 33] (Fig. 1). We found that 3-O-(6-galloylglucoside) and epicatechin gallate had the utmost bound
energy of −8.4 kcal/mol (Table 4). This prompted the
initiative to visualized their binding pose and bring to
fore their interaction patterns with the target protein in
relative to the best hit control drug (remdesivir) using
PyMol and Discovery Studio visualizer. The compounds
were observed to fit into the same cavity of the binding
site (Fig. 2b). More also, 3-O-(6-galloylglucoside) was
able to produce interaction with five amino acids within
the binding pouch of Mpro such as Thr26, Ser144,
Cys145, His163, and Glu166 at bond length of 2.86 Å,
4.46 Å, 4.07 Å, 5.50 Å, and 5.01 Å respectively. A pisigma bond of length 5.62 Å was also observed between
the aromatic side chain of Thr25 and the galloyl’s aromatic ring of 3-O-(6-galloylglucoside), while a pi-alkyl
interaction with bond length of 4.95 Å was established
between the aromatic side chain of Met165 and the aromatic ring attached to the glucoside. A carbon-hydrogen
bond was formed with Gln189. The remaining interaction was by van der Waals with Thr24, Leu27, His41,
Met49, Phe140, Leu141, Asn142, Gly143, His164,
Asp187, Arg188, and Gln192. However, Glu166 and
His164 interacted with epicatechin gallate (ECG) via
hydrogen bond at a distance of 2.85 Å and 5.04 Å respectively. Pi-pi and amide-pi stacked interactions
emerged between Met165 and Leu141 with ECG at bond
lengths of 7.83 Å and 6.71 Å respectively. Thr25, Leu27,
Met49, His41, Phe140, His163, Ser144, Gly143, His172,
Asp187, Arg188, Gln189, and Thr190 interact with ECG
Fig. 2 Molecular docking studies of gallic acid derivatives against main protease (Mpro) of SARS-Cov-2. a Protocol validation of molecular
docking experiment using AutoDock Vina, PyMOL, and LigPlot+. (a) Comparison of binding modes for re-docked ligand (red) vs. co-crystallized
ligand (green) shown as stick representation. Amino acid residues interaction with (b) co-crystalized and (c) re-docked ligand accomplished in
LigPlot+. b Binding mode and molecular interaction of hit ligands with Mpro. (a) Surface representation of Mpro (PDB: 6 LU7) show the binding
mode of docked 3-O-(6-galloylglucoside) (yellow), epicatechin gallate (green), and remdesivir (pink). 2D interaction of (b) 3-O-(6-galloylglucoside),
(c) epicatechin gallate, and (d) remdesivir
Umar et al. Journal of Genetic Engineering and Biotechnology
(2021) 19:16
through van der Waals forces. More so, Cys145 interacts
with ECG by forming alkyl, pi-alkyl, and pi-sulfur bonds
with distance of 6.28 Å, 6.59 Å, and 6.32 Å respectively.
Among the control drugs in this study, remdesivir
showed a good bound energy of −7.9 kcal/mol. It was
able to form three hydrogen bonds with Thr190 and
Arg188 at a distance of 5.62 Å, 4.22 Å, and 6.26 Å respectively. Meanwhile, Met165 established pi-alkyl and
pi-sulfur bonds with distance of 5.42 Å and 5.68 Å respectively. Met49 and His41 associated with control
drug via pi-alkyl and pi-pi stacked bonds with distance
of 5.60 Å and 4.51 Å respectively.
The PLpro used for this investigation was retrieved in
its 3D crystal structure (6W9C), resolved at 2.70 Å, with
sequence length of 317, and a homotrimeric protein [7].
The substrate binding site in PLpro is made up of a canonical cysteine protease catalytic triad (Cys111, His272,
and Asp286) (Fig. 1) found at the interface between the
thumb and palm domains; other amino acids in the
binding site are Trp106, Gly266, Gly271, His73, Arg140,
and Asn109 [7]. The in silico docking of PLp with gallic
acid derivatives revealed that 3-O-(6-galloylglucoside), 4O-(6-galloylglucoside), and remdesivir had the utmost
binding affinity scores of −6.6, −6.8, and −6.5 kcal/mol
respectively (Table 4). Furthermore, the molecular interactions of these inhibitors were predictably ascertained
indicating that these inhibitors bind to the same cleft of
the catalytic site of our target protein (Fig. 3b). 3-O-(6Galloylglucoside) with Met206, Arg166, Gln174, and
Ser170 formed hydrogen bonds at distance of 3.32 Å,
5.94 Å, 4.70 Å, 3.73 Å, and 4.61 Å respectively. Although
Page 8 of 14
Met206 had another interaction with 3O6G via pi-alky
bond with a distance of 4.68 Å while two pi-sulfur bonds
were observed between Arg166 and 3O6G, Glu203,
Val202, Tyr207, Met208, and Tyr171 interacted via van
der Waals forces. 4O6G had Gln174, Ser170 and
Met208 engaged via hydrogen bonding at distance of
4.69 Å, 3.63 Å, 4.44 Å, and 5.04 Å respectively. Moreover,
Arg166 and Met206 were engaged via pi-sulfur and pialkyl interactions with 4O6G at distance 6.19 Å and 4.34
Å respectively. Van der Waals force was observed between 4O6G with Va202, Tyr171, Asp164, Glu167,
Glu203 and Tyr207. Remdesivir binding was found to
involve three H-bonds with Lys232, Ser170, and Arg166
with distance of 5.35 Å, 5.24 Å, and 4.73 Å respectively.
Met206 and Val202 established pi-alky bonds with
remdesivir at distance of 4.99 Å and 6.24 Å respectively.
Lys232, Leu199, Val187, and Leu185 form links with our
ligand via an alky-type bond. While Leu199 established a
pi-alkyl bond with remdesivir.
3D crystal structure of nsp12 was retrieved from protein data bank with PDB code of 6 M71, resolution of
2.9 Å, fused together with nsp8 and nsp7 as cofactors,
chain A of the complex and sequence length of 942
amino acids [25]. The active site of nsp12 is conserved
in the polymerase motifs A-G (Fig. 1), which comprises
of Asp618, Ser759, Asp760, and Asp761 [25]. Total of
seventeen gallic acid derivatives was screened for identifying the potential drug against RdRp using molecular
docking. All the compounds were evaluated on the basis
of their maximum scoring function, and the top ranked
compound was selected and analyzed for the
Fig. 3 Molecular docking studies of gallic acid derivatives against papain-like protease (PLpro) of SARS-Cov-2. a Protocol validation of molecular
docking experiment using AutoDock Vina, PyMOL, and LigPlot+. (a) Comparison of binding modes for re-docked ligand (green) vs. co-crystalized
ligand (red) shown as stick representation. Amino acid residues interaction with (b) co-crystalized and (c) re-docked ligand accomplished in
LigPlot+. b Binding mode and molecular interaction of hit ligands with PLp. (a) surface representation of PLp (PDB: 6W9C) show the binding
mode of docked 3-O-(6-galloylglucoside) (yellow), 4-O-(6-galloylglucoside) (blue), and remdesivir (red). 2D interaction of (b) 3-O-(6galloylglucoside), (c) 4-O-(6-galloylglucoside) and (d) remdesivir
Umar et al. Journal of Genetic Engineering and Biotechnology
(2021) 19:16
Page 9 of 14
Fig. 4 Molecular docking studies of gallic acid derivatives against RNA-dependent RNA polymerase (RdRp) of SARS-Cov-2. a Protocol validation of
molecular docking experiment using AutoDock Vina, PyMOL, and LigPlot+. (a) Comparison of binding modes for re-docked ligand (blue) vs. cocrystalized ligand (red) shown as stick representation. Amino acid residues interaction with (b) co-crystalized and (c) re-docked ligand
accomplished in LigPlot+. b Binding mode and molecular interaction of hit ligands with RdRp. (a) surface representation of RdRp (PDB: 6 M71)
show the binding mode of docked 4-O-(6-galloylglucoside) (green), and dexamethasone (red). 2D interaction of (b) 4-O-(6-galloylglucoside) and
(c) dexamethasone
interactions with RdRp protein. 4-O-(6-Galloylglucoside)
possessed the highest binding affinity of −8.9 kcal/mol
showing strong bonding with RdRp (Table 4). The
docked conformation of 4-O-(6-galloylglucoside) with
their interacting residues is shown in Fig. 4. This compound contributes seven hydrogen bonding interactions
with viral RdRp which were observed between Lys47,
Tyr129, His133, Ser709, Thr710, Gln773, and Ser784 at
distance of 4.78 Å, 5.99 Å, 4.25 Å, 3.68 Å, 4.43 Å, and
5.19 Å respectively. Pi-alkyl interaction with Ala130 at a
distance of 5.88 Å. Lys780, Asn705, Ala706, Gly774,
Asp711, Phe134, Cys139, Leu142, Asp140, Thr141, and
Asn138 interact with 4O6G via van der Waals forces.
Dexamethasone exhibits highest −7.5 kcal/mol binding
Fig. 5 Molecular docking studies of gallic acid derivatives against helicase/Nsp13 (RdRp) of SARS-Cov-2. a Protocol validation of molecular
docking experiment using AutoDock Vina, PyMOL, and LigPlot+. (a) Comparison of binding modes for re-docked ligand (green) vs. co-crystalized
ligand (red) shown as stick representation. Amino acid residues interaction with (b) co-crystalized and (c) re-docked ligand accomplished in
LigPlot+. b Binding mode and molecular interaction of hit ligands with Helicase. (a) surface representation of Helicase (PDB: 6XEZ) show the
binding mode of docked 4-O-(6-galloylglucoside) (blue), and dexamethasone (red). 2D interaction of (b) 4-O-(6-galloylglucoside) and
(c) dexamethasone
Umar et al. Journal of Genetic Engineering and Biotechnology
(2021) 19:16
affinity although remdesivir was a known RdRp inhibitor. Within the binding cavity of RdRp, it forms hydrogen bond with His810, Thr817, Tyr816, and His872 at
distance of 3.59 Å, 4.03 Å, 4.96 Å, and 5.39 Å respectively. Carbon-hydrogen bond was observed with Tyr831
at a distance of 5.77 Å. Moreover, His872, Pro873, and
Lys807 formed alkyl-type interactions at distance of 5.39
Å, 4.47 Å, 4.65 Å, 6.45 Å, and 4.62 Å respectively with
control drug. The van der Waals interaction occurred
between the drug and Met818, Gly808, Pro809 in
addition to Glu802.
The 3D crystal structure was together with RdRp,
nsp8, and nsp7 (6XEZ), with resolution of 3.5 Å, sequence length of 605 amino acids and homodimeric [9].
The amino acids of relevance in the binding cavity of
nsp13 are Lys288, Ser289, Asp374, Glu375, Gln404, and
Arg567 [9] (Fig. 1). Gallic acid derivatives were screened
as potential inhibitors of helicase using molecular docking. At the end of the docking study, 4O6G had the best
binding affinity of −9.1 kcal/mol. Also, dexamethasone,
one of the control drugs in this study fared better than
other control drugs with binding affinity of −8.0 kcal/
mol (Table 4). 4O6G and dexamethasone occupied similar area in the active portion of helicase (Fig. 5b). The
molecular interaction in 2D show the binding signatures
maintained by both molecules (Fig. 5b). 4O6G was able
to create hydrogen bond with seven amino acids such as
Gly287, Lys288, Arg443, Arg567, Lys320, Ala316, and
Ser289 at distance of 3.18 Å, 3.40 Å, 3.15 Å, 6.80 Å, 5.69
Å, 6.26 Å, 5.71 Å, 5.53 Å, 4.18 Å, 3.86 Å, 3.14 Å, and
Page 10 of 14
4.37 Å respectively. Also, pi-cation bond was formed
with Lys288 and Lys320 at distance of 5.46 Å and 4.63 Å
respectively. However, Gly538 interacted with 4O6G via
a pi-sigma bond. In addition, van der Waals force form
the link between 4O6G and eight amino acids which are
Pro283, Gly285, Thr286, Pro284, Gln404, Gly400,
Gln537, and Glu319 then Glu375 established a carbonhydrogen bond with 4O6G at a distance of 3.47 Å. Dexamethasone, interacted with Thr286, Lys288, Arg443, and
Gly285 at distance of 4.00 Å, 4.58 Å, 6.22 Å, and 4.20 Å
respectively via hydrogen bond. Although, alkyl interaction occurred with Lys288 and Ala316 at distance of
4.15 and 5.57 respectively but Ala316 formed another
interaction via pi-alky bond at a distance of 5.25 Å.
However, ten amino acids interacted with dexamethasone by van der Waals force. They include Glu540,
Ser289, His290, Gly287, Lys323, Glu219, Gly538, Lys320,
Pro284, and Pro283.
A 2.20 Å X-ray resolved protein was used in this
current work with sequence length of 342 amino acids
and hexameric structure [10]. The active cavity of NendoU is made up of His235, His250, Lys290, Thr341,
Thr343, and Ser294 [3, 10] (Fig. 1). Therefore, it is of
pertinence to evaluate the selected gallic acid derivatives
against NendoU using molecular docking technique.
4O6G (−7.5 kcal/mol) and dexamethasone (−7.1 kcal/
mol) were found to have the utmost binding affinity
among the gallic acid derivatives and the control drugs
respectively. Both compounds occupied the same site on
the catalytic region of the target protein (Fig. 6b). The
Fig. 6 Molecular docking studies of gallic acid derivatives against Nidoviral RNA uridylate-specific endoribonuclease, NSP15 (NendoU) of SARSCov-2. a Protocol validation of Molecular Docking experiment using AutoDock Vina, PyMOL, and LigPlot+. (a) Comparison of binding modes for
re-docked ligand (red) vs. co-crystalized ligand (cyan) shown as stick representation. Amino acid residues interaction with (b) co-crystalized and
(c) re-docked ligand accomplished in LigPlot+. b Binding mode and molecular interaction of hit ligands with NendoU. (a) Surface representation
of NendoU (PDB: 6VWW) show the binding mode of docked 4-O-(6-galloylglucoside) (green), and dexamethasone (pink). 2D interaction of (b) 4O-(6-galloylglucoside) and (c) dexamethasone
Umar et al. Journal of Genetic Engineering and Biotechnology
Page 11 of 14
(2021) 19:16
Table 5 ADMET properties of best hits compounds with remdesivir. ADMET was predicted using the AdmetSAR server
Class
Properties
3-O(galloylglucoside)
4-O(galloylglucoside)
Epicatechin
gallate
Remdesivir
Dexamethasone
Absorption
Caco-2 permeability
Negative
Negative
Negative
Negative
Positive
Human intestinal
absorption
Negative
Negative
Positive
Positive
Positive
Human oral bioavailability
Negative
Negative
Negative
Negative
Negative
Pgp-inhibitor
Negative
Negative
Negative
Positive
Negative
Pgp-substrate
Negative
Negative
Negative
Positive
Positive
Moderately high
(95.31%)
Moderately high
(94.27%)
High (102.20%)
Very high
(118.2%)
High (100%)
Distribution PPB (plasma protein
binding)
Negative
Negative
Negative
Positive
Positive
Metabolism CYP450 1A2 inhibition
BBB (Blood–brain barrier)
Negative
Negative
Negative
Negative
Negative
CYP450 3A4 inhibition
Negative
Negative
Negative
Negative
Negative
CYP450 3A4 substrate
Negative
Negative
Positive
Positive
Positive
CYP450 2C9 inhibition
Negative
Negative
Negative
Negative
Negative
CYP450 2C9 substrate
Negative
Negative
Negative
Negative
Negative
Toxicity
CYP450 2C19 inhibition
Negative
Negative
Negative
Negative
Negative
CYP450 2D6 inhibition
Negative
Negative
Negative
Negative
Negative
CYP450 2D6 substrate
Negative
Negative
Negative
Negative
Negative
CYP inhibitory promiscuity Negative
Negative
Negative
Negative
Negative
UGT catalyzed
Positive
Positive
Negative
Negative
Positive
Sub-cellular localization
Mitochondria
Mitochondria
Mitochondria
Lysosomes
Mitochondria
Acute oral toxicity (kg/
mol)
2.5726
2.5958
2.3672
3.4279
2.486
Ames mutagenicity
Negative
Negative
Negative
Negative
Negative
Carcinogens
Negative
Negative
Negative
Negative
Negative
Human hepatotoxicity
Positive
Negative
Positive
Positive
Negative
binding patterns of both compounds are shown in Fig.
6b-c. 4O6G was able to interact with seven amino acids
through hydrogen bond. The amino acids involved are
Ser296, Leu346, Tyr343, Lys290, Thr341, Asp240, and
Gln245 with distance of 3.89 Å, 3.68 Å, 5.91 Å, 4.95 Å,
3.93 Å, 4.22 Å, 4.79 Å, and 5.96 Å respectively. His235
forms a pi-pi T-shaped bond with 4O6G while Pro344,
Lys345, Leu246, Gly247, His243, Gly248, Cys293,
His250, and Val292 all interacted with the compound
via van der Waals force. However, dexamethasone
formed hydrogen bond with Ly290 at a distance of 4.60;
Pi-sigma and pi-alkyl bonds with Tyr343 at a distance of
4.14 Å and 5.46 Å respectively; alkyl bond with Leu346,
His250, and Tyr343 at distance of 4.69 Å, 6.77 Å, 5.91 Å,
and 5.72 Å respectively. Lys345, Ser294, Val292, Gly248,
His235, Thr341, Gly247, and Leu246 interacted with the
drug via van der Waals force.
ADMET prediction
3-O-(6-Galloylglucoside), 4-O-(6-galloylglucoside), and
epicatechin gallate were screened for their absorption,
distribution, metabolism, and toxicity (ADMET) through
a web tool called AdmetSAR. Also, dexamethasone and
remdesivir were also screened. This in silico toxicity
screening of our hit compounds cannot be over emphasized as it will ultimately predict the pharmacokinetics
and pharmacodynamics of these compounds in relation
to the selected control drugs. As we know, the control
drugs are part of the treatment regimen in the fight
against this global malady, but there are safety concerns.
The results are depicted in Table 4.
In the absorption class, caco-2 permeability, human intestinal absorption, human oral availability, pglycoprotein inhibition and substrates were predicted.
Out of the five molecules, only dexamethasone was predicted to permeant caco-2, epicatechin gallate, dexamethasone, and remdesivir were predicted to be
absorbed by the human intestine. None of them were
predicted to be orally available but dexamethasone and
remdesivir might serve as substrate to p-glycoprotein.
Although remdesivir was predicted to inhibit pglycoprotein. The distribution of these molecules were
predicted via two properties (PPB and BBB). All the
compounds indicate that they might possibly reach their
Umar et al. Journal of Genetic Engineering and Biotechnology
(2021) 19:16
target site in high to moderate dose as their ability to
bind to plasma proteins was predicted to be high. Dexamethasone and remdesivir might be able to reach the
central nervous system (CNS) as they were predicted to
permeant the blood-brain-barrier (BBB). All the compounds were predicted to be localized in the mitochondria except remdesivir which was predicted to be
localized in the lysosomes. The metabolism of these
molecules by the human liver was predicted to ascertain
whether they can cause harm or not. More also, none of
these molecules were predicted to inhibit cytochrome
P450 1A2 and 3A4. 3-O-(6-galloylglucoside) and 4-O(6-galloylglucoside) were predicted to be non-substrate
to Cytochrome P450 3A4. None of the compounds were
predicted to be substrates or inhibitors of Cytochrome
P450 2C9, 2C19, and 2D6. All the compounds were catalyzed by UGT except epicatechin gallate and remdesivir
as predicted by the web server. The toxicity was evaluated based on acute oral toxicity, AMES mutagenesis,
carcinogenicity, and human hepatotoxicity. None of the
compound was predicted to be AMES mutagenic and
carcinogens; 4-O-(6-galloylglucoside) and dexamethasone were predicted to be non-toxic to the liver cells.
The acute oral toxicity (kg/mol) were also predicted
(Table 5).
Discussion
Gallic acid (GA) and its derivatives are one of many phytocompounds with diverse pharmacological propensities
that can assist in the management of several diseases
such as inflammatory, cardiovascular, respiratory, gastrointestinal, and metabolic diseases caused by bacteria,
fungi, and viruses. It is pertinent to note in this present
in silico study, compounds were selected based on their
pharmacological roles, large quantity in nature, and most
significantly, had not been used for any study to evaluate
them against the etiological agent of the recent coronavirus outbreak be it in silico, in vitro, nor in vivo. However, there are numerous studies on gallic acid and its
derivatives against different diseases such as antibacterial, antifungal, and antiviral diseases [17, 18]; nonetheless, no study have reported its use as a therapeutic
compound against the on-going pandemic. Base on resent studies [20–23], computational approaches have
been deployed to discover novel and potential small
molecules in drug discovery and development.
The compounds and control drugs were screened for
their oral druggability via Lipinski’s rule; a rule of thumb
that states that for a molecule to be orally active as drug,
the molecular weight must not exceed 500 Da, lipophilicity must be below 5, number of hydrogen bond acceptors and donors must not exceed 10 and 5 respectively.
The consequence of a molecule exceeding these landmarks might affect its adsorption, metabolism, excretion,
Page 12 of 14
and toxicity in the body, making it a poor drug. The
physicochemical and toxicity assessment was carried out
in silico to fish out some compounds that were perceived to be toxicant; this step buttressed some of the
findings of the druglikeness screening using Lipinski’s
rule.
The significance of our selected SARS-CoV-2 proteins
had earlier been discussed. Main protease (Mpro) is a
vital enzyme in SARS COV 2 that acts on polyproteins
to give rise to nsp4 to nsp16. Thus, without this action,
viral replication and transcription might not take place.
The binding site of Mpro is surrounded by 25 amino
acids such as Thr25, Cys44, Thr26, His41, Met49, Tyr54,
Phe140, Leu141, Gly143, Cys145, Asn142, His163,
His164, Met165, Ser144, Glu166, Pro168, His172,
Val186, Asp187, Arg188, Gln189, Phe185, Thr190, and
Gln192. Also, the binding site shows a CysHis (Cys145
and His41) catalytic dyad [29, 33]. The BE of 3O6G and
ECG noticed with Mpro might be as a result of the interactions that were established with the two key amino
acid residues that formed the catalytic triad in its substrate binding domain (Fig. 2 and Table 4). Another vital
protein in viral life cycle with an additional function of
innate immune antagonism by cleaving ubiquitin and
ISG15 from interferon-α (IFN-α) is the papain-like protease (PLpro) [6]. The substrate binding domain is made
up of a canonical cysteine protease catalytic triad
(Cys111, His272, and Asp286) (Fig. 1) found at the interface between the thumb and palm domains; other amino
acids in these domain are Trp106, Gly266, Gly271,
His73, Arg140, and Asn109 [7]. It is noteworthy that
none of the hit compounds had interactions with the
catalytic triad (Cys111, His272, and Asp286) and might
be the reason for the characteristics BE values exhibited
by them (Fig. 3 and Table 4).
RNA-dependent RNA polymerase (RdRp/nsp12) is
one of the crucial molecular target for developing promising leads against coronavirus since is the central piece
of the replication-transcription machinery [9, 25, 34].
The active site of nsp12 is conserved in the polymerase
motifs A-G (Fig. 1), comprising of Asp618, Ser759,
Asp760, and Asp761 [25]. The BE exhibited by 4O6G
and dexamethasone might be ascribed to the interactions that results with key residues that are pertinent to
activity of the enzyme. However, helicase, nsp13 as a
member of the functional complex with RdRp called
replication-transcription complex (RTC) is also crucial
in the life cycle of SARS COV 2 [9]. The amino acids of
relevance in the binding cavity are Lys288, Ser289,
Asp374, Glu375, Gln404, and Arg567 [9] (Fig. 1). The
characteristics BE portrayed by 4O6G and dexamethasone might be attributed to their abilities to interact with
three key amino acid residues that contributes to the
catalytic activity of helicase (Fig. 5 and Table 4). NendoU
Umar et al. Journal of Genetic Engineering and Biotechnology
(2021) 19:16
(nsp15) is key to SARS COV 2 since it is known to interfere with the host immune system by cleaving the
double and single stranded RNA at the uridylate region
releasing 2′-3′cyclic phosphate end [10]. The active cleft
of NendoU is made up of His235, His250, Lys290,
Thr341, Thr343, and Ser294 [3, 10] (Fig. 1). The BE exhibited after docking by 4O6G and dexamethasone
against NendoU might be linked to the interactions
formed with key amino acid residues that are significant
to the catalytic activity of the enzyme (Fig. 6 and Table
4).
The interactions reported in this present in silico
study, viz., hydrogen bond, hydrophobic interaction
(alkyl and pi-typed bonds), and electrostatic interactions
(pi-cation and anion), had been reported [27, 35, 36]
earlier to provide stability to the protein–ligand complexes and also influence the binding energy values of
the hit compounds in complex with all the target proteins. Thus, the available facts from the pool of investigated active compounds related to gallic acid, suggest
that 3O6G, 4O6G, and ECG may possess the most in
silico inhibitory effect against SARS-CoV-2 through a
molecular docking technique. However, these outcomes
need to be validated using molecular dynamic simulation, in vitro and in vivo studies. The studies from in
silico toxicity profiling (Table 5) revealed that 4-O-(6galloylglucoside) is better than the rest of the hit compounds but it will require chemosimilar or pharmacophoric modeling that will improve some key parameters
relating to absorption and distribution which might be
linked to the earlier screening for druglikeness using the
Lipinski’s rule of five where it violated the parameters:
hydrogen bond donor and acceptor. This is also the
same for the remaining two hit compounds. Thus, they
could be repurposed as a defense line against this viral
malady.
Conclusion
At present, the greatest threat to global human health is
the recent coronavirus outbreak caused by the novel
SARS-CoV-2 coronavirus. We performed a molecular
docking assay with some selected gallic acid derivatives
against five key proteins of SARS-CoV-2 that are found
to be vital throughout the viral life cycle and proliferation. These proteins are Nsp3, Nsp5, Nsp12, Nsp13, and
Nsp15. From our present in silico study, we observed
that three of the selected compounds, namely, 3-O-(6galloylglucoside), 4-O-(6-galloylglucoside), and epicatechin gallate could be promising inhibitors of the selected
SARS-CoV-2 non-structural proteins, and a possible
treatment option against the current COVID-19 pandemic. The result, from our present in silico study, also
revealed that 4-O-(6-galloylglucoside) had the best binding energies (BE) against Nsp3, Nsp12, Nsp13, and
Page 13 of 14
Nsp15 with BE of −6.8, −8.9, −9.1, and −7.5 kcal/mol respectively. However, 3-O-(6-galloylglucoside) and epicatechin gallate show better BE against Nsp5 of −8.4 kcal/
mol each. Although the studies from in silico toxicity
profiling revealed that 4-O-(6-galloylglucoside) is better
than the rest of the hit compounds, thus, could be
repurposed as a defense line against this viral malady.
However, since this study had been accomplished
through molecular docking methods, there would be
need for molecular dynamics simulation of at least 100
ns to validate the outcome of our present in silico study.
More so, an actual experiment of the identified compounds in this study for both in-vitro and in-vivo studies
with appropriate models is also recommended to further
authenticate the findings from this study.
Abbreviations
ADMET: Adsorption, distribution, metabolism, excretion and toxicity;
BE: Binding energy; COVID-19: Coronavirus disease 19; Mpro: Main protease;
NSP: Non-structural proteins; ORF: Open reading frame; PLpro: Papain-like
protease; RdRp: RNA-dependent RNA polymerase; RNA: Ribonucleic acid;
SARS-CoV 2: Severe acute respiratory syndrome coronavirus 2
Acknowledgements
The authors are grateful to Federal University of Technology, Akure, for
providing research platform. Our study was not supported by any funding
authority. HIU acknowledged the technical support of Eng. Ramoni Badmus
of Federal Radio Corporation, Nigeria, during the course of this study.
Authors’ contributions
HIU: Conceptualization, methodology, investigation, writing of original draft;
BS: Methodology, investigation, writing of original draft; AA: Methodology,
investigation, writing of original draft; TOJ: Conceptualization, investigation,
writing, reviewing, and editing; POC: Methodology, investigation, writing,
reviewing, and editing of the manuscript. All authors have read and
approved the manuscript for publication.
Funding
Not applicable
Availability of data and materials
We declare that all the data generated are included in this study.
Ethics approval and consent to participate
Not applicable
Consent for publication
Not applicable
Competing interests
Not applicable
Author details
1
Department of Biochemistry, School of Sciences, Federal University of
Technology, Along Owo-Ilesha Express Way, P.M.B. 704, Akure, Ondo State,
Nigeria. 2Ioncure Tech Pvt. Ltd., Delhi 110085, India. 3Dr. Zafar H. Zaidi Center
for Proteomics, University of Karachi, Karachi, Pakistan. 4Faculty of
Pharmaceutical Sciences, Department of Pharmacognosy and Pharmaceutical
Botany, Chulalongkorn University, Bangkok, Thailand. 5Department of
Biochemistry, Habib Medical School, Islamic University in Uganda, P. O. Box
7689, Kampala, Uganda. 6Department of Biotechnology, School of sciences,
Federal University of Technology, Akure, Ondo State, Nigeria.
Umar et al. Journal of Genetic Engineering and Biotechnology
(2021) 19:16
Received: 31 October 2020 Accepted: 12 January 2021
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