Article

Volume 12, Issue 1, 2022, 61 - 73

https://doi.org/10.33263/BRIAC121.061073

DFT Calculations and In silico Study of Chlorogenic,

Ellagic and Quisqualic acids as Potential Inhibitors of
SARS-CoV-2 Main Protease Mpro
Siyamak Shahab 1,2,3 , Sadegh Kaviani 4,* , Masoome Sheikhi 5 ,
6 1,3
Hora Alhosseini Almodarresiyeh , Sultan Al Saud
1 Belarusian State University, ISEI BSU, Minsk, Republic of Belarus
2 Institute of Physical Organic Chemistry, National Academy of Sciences of Belarus,13 Surganov Str., Minsk 220072,
Republic of Belarus
3 Institute of Chemistry of New Materials, National Academy of Sciences of Belarus, 36 Skarina Str., Minsk 220141,
Republic of Belarus
4 Department of Chemistry, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran
5 Young Researchers and Elite Club, Gorgan Branch, Islamic Azad University, Gorgan, Iran
6 Department of Materials Science and Engineering, School of Engineering, Meybod University, 89616-99557, Meybod,
Yazd, Iran
* Correspondence: kaviani.sadegh@mail.um.ac.ir (S.K.);
Scopus Author ID: 57190261707
Received: 7.03.2021; Revised: 5.04.2021; Accepted: 9.04.2021; Published: 19.04.2021

Abstract: In the present work, at first, density functional theory calculations were performed to
investigate the molecular structure of the Chlorogenic, Ellagic, and Quisqualic acids by CAM-
B3LYP/MidiX level of theory. A detail of quantum molecular descriptors of the title compounds such
as ionization potential (IP) and Electron Affinities (EA), Hardness (η), Softness (S), Electronegativity
(μ), Electrophilic Index (ω), Electron Donating Power (ω-), Electron Accepting Power (ω+) and Energy
Gap (Eg) have been calculated. Pharmacokinetic properties of the title compounds and their bioactivity
were investigated. In the following, a molecular docking study was carried out to screen for an effective
available compound that may work as a strong inhibitor for the SARS-CoV-2 main protease Mpro. The
binding energy between SARS-CoV-2 main protease Mpro and title organic acids showed a good
binding affinity. Therefore, the Chlorogenic, Ellagic, and Quisqualic acids can be used for potential
application against the SARS-CoV-2 main protease Mpro.

Keywords: SARS-CoV-2 main protease Mpro; DFT; molecular docking; chlorogenic; Ellagic and
Quisqualic acids; pharmacokinetic properties.
© 2021 by the authors. This article is an open-access article distributed under the terms and conditions of the Creative
Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction

The appearance of a severe acute respiratory syndrome (SARS-CoV-2) created a

pandemic in the Wuhan city and more than 212 countries, resulting in over 27 million infections
and about 900.000 deaths worldwide [1-4]. SARS-CoV-2 falls into the category of RNA
viruses, which causes disorders in hepatic, pulmonary, central nervous, and gastrointestinal
systems [5,6]. SARS-CoV-2 can encode cysteine proteases, including the chymotrypsin-like
cysteine (3CLpro) or main protease (Mpro) and the papain-like cysteine protease (PLpro), which
are responsible for catalyzing the proteolysis of polyproteins translated from the genome of the
virus into nonstructural proteins required for packaging the nascent virion and replication of
virus [7-10]. Therefore, inhibition of the activity of these proteases would prevent the virus
https://biointerfaceresearch.com/ 61
 https://doi.org/10.33263/BRIAC121.061073

replication. Mpro hydrolyzes the Gln-Ser peptide bond in the Leu-Gln-Ser-Ala-Gly sequence,
which is different from the peptide sequence identified by other human cysteine proteases [11].
Therefore, Mpro is considered a promising site for designing anti-SARS-CoV-2 drugs.
Chlorogenic acid (CGA) is an important biologically active phenolic compound, being
the main component of coffee and tea produced by the plant's special species [12-14]. It is
recently receiving high attention due to its many promising useful effects related to its anti-
inflammatory and antioxidant properties, such as regulation of glucose and lipid metabolism in
cardiovascular [15], diabetes [16], cancer [17], and fatty liver [18] diseases. Before absorption
of CGA in the gastrointestinal system, it is hydrolyzed to caffeic acid and quinic acid through
the functioning of certain microbial esterases in both small and large intestine, while after
absorption, it is metabolized to glucuronide and sulfate as circulating species in plasma [19,20].
Based on Hoelzl et al.'s reports, the high levels of Chlorogenic acid in coffee decrease 8-
isoprostaglandin F2α and 3-nitrotyrosine about 15.3 and 16.1%, respectively, inducing a
protective effect against the damage generated by free radicals [21]. Sapio et al. reported that
Chlorogenic acid has an inhibitory effect on the proliferation of osteosarcoma (OS) cells, which
provides promising novel strategies in OS treatment [22].
Ellagic acid (EA) is a natural polyphenol compound with great antioxidant and anti-
cancer activities [23-25]. Its antioxidant efficacy is exerted by stimulation of the activity of
antioxidant enzyme systems, whereas the anti-cancer characteristic of Ellagic acid is related to
its capability to inhibit growth and tumor diffusion as well as increasing the sensitivity of tumor
cells to chemotherapy and radiotherapy [26-29]. Guptaa et al. showed the inhibitory potential
of Ellagic acid towards SphK1 as a therapeutic method to control sphingosine kinase 1
(SphK1)-dependent pathologies, such as cancer and diabetes [30]. Yousuf et al. demonstrated
that Ellagic acid could be a potential inhibitor of Cyclin-Dependent Kinase 6 (CDK6) in breast
cancer treatment [31]. Wang et al. suggested that Ellagic acid inhibits breast cancer metastasis
via regulation of ACTN4 in vitro and in vivo [32].
Quisqualic acid (QA) is an amino acid isolated from the seeds of Quisqualis indica,
which acts as an agonist of glutamate, kainate, and metabotropic receptors in the central
nervous systems (CNS) of mammalians [33,34]. Since quisqualate has an uncertain effect on
synaptic transmission, Quisqualic acid can induce an increased sensitivity of neurons to
depolarization by analogs of phenyl glycine, homoibotenic (HIBO) acid, and 2-amino-4-
phosphonobutyric acid (AP4) [35]. Bitzer et al. concluded Quisqualic acid reduces ZENK
expression, which causes myopia [36]. According to Rochford et al., Quisqualic acid affects
the rabbit eye's standing potential through its functioning on the retinal pigment epithelium
[37].
In silico and computational approaches are low-cost methods for predicting
pharmacokinetics' pharmacokinetics properties before experimental procedures, which give us
basic data in bioinformatics research [38-42]. In this study, computational/In silico methods
are utilized to screen the potential inhibitory of Chlorogenic, Ellagic, and Quisqualic acids for
SARS-CoV-2 main protease Mpro. ADMET characteristics are evaluated to represent selected
inhibitors' compatibility for human administration, whereas molecular docking and DFT
investigations are utilized to analyze their reactivity and binding with SARS-CoV-2 main
protease Mpro.

https://biointerfaceresearch.com/ 62
 https://doi.org/10.33263/BRIAC121.061073

2. Materials and Methods

2.1. ADME analysis.

Lipinski's Rule of Five [43] was used to investigate organic acids that were selected for
this study. Filters like Molecular weight of the ligand (<500 Da), high lipophilicity (LogP<5),
number of hydrogen bonds donors (<5), number of hydrogen bond acceptors (<10), and Molar
refractivity (40–130) (Ghose Rule) were used to carry out the further selection of the title
organic acids. Violation of more than 2 of the above-stated parameters debarred further analysis
of a particular molecule. Parameter details were calculated from using Molinspiration
Cheminformatics software [44].

2.2. Bioactivity score.

The investigated acids' bioactivity was predicted by calculating the activity score
toward G protein-coupled receptors (GPCR ligand), ion channel modulator, nuclear receptor
ligand, a kinase inhibitor, protease inhibitor, and enzyme inhibitor with the help of online
software Molinspiration (www.molinspiration.com).

2.3. DFT investigation.

A Pentium IV personal computer (CPU at 4.80 GHz) with the Windows 10 operating
system was used. The initial geometry optimization of title compounds was performed with
HyperChem (Version 8.0 Hypercube, Inc., Alberta, Canada). For all the ab initio calculations,
Gaussian 16 was employed [45]. The molecular properties of the compounds were calculated
by CAM-B3LYP/MidiX level of theory [46,47]. The lowest energy structures of the species
were computed by conformational analysis. Geometry optimization was performed at the
CAM-B3LYP level with the same basis set. The following formulas were applied to calculate
the electronic properties of the title molecules [48]:
IP = - EHOMO, (eV) (1)
EA = - ELUMO, (eV) (2)
η = (IP - EA)/2, (eV) (3)
S = 1/2η, (eV) (4)
μ = (IP + EA)/2, (eV) (5)
ω = μ2/2η, (eV) (6)
ω = (IP + 3EA)2/16(IP - EA), (eV)
+ (7)
ω- = (3IP + EA)2/16(IP - EA), (eV) (8)
Eg = ELUMO - EHOMO, (eV) (9)
The geometry optimization was performed in the gas phase. The optimized molecular
structures, HOMO and LUMO surfaces, were visualized using GaussView 05 program [49].

2.4. Molecular docking.

The molecular docking studies were performed by using the AutoDock/Vina tool [50].
It is a reliable protein-ligand docking tool that uses the Broyden-Goldfarb-Shanno algorithm,
which significantly improves the binding mode prediction's average accuracy. The crystal
structure of the target protein (PDB ID: 7CBT) (Figure 1) was downloaded from the Protein
Data Bank (http://www.rcsb.org/pdb) in PDB format and was prepared by AutoDock tools.
Visualization of the docked pose has been done using CHIMERA (www.cgl.ucsf.edu/chimera)
and Molegro Molecular Viewer 2.5 (www.clcbio.com/products/molegro/#molecular-viewer).
https://biointerfaceresearch.com/ 63
 https://doi.org/10.33263/BRIAC121.061073

Water molecules and amino acid that does not belong to the protein were removed by deleting
the lines that start with "HETATM" and "CONNECT". The file structure was saved and ready
for docking analysis. Manually initialized the protein molecule by adding hydrogen atoms and
kolmen charges using the edit option and saved the protein molecule as write PDB. A grid box
of 50 × 50 × 50 Å centered at (-27.325, 17.891, 76.447) Å for the SARS-CoV-2 main protease
was used in the docking experiments. Biovia Discovery Studio Visualizer v19.1.0.18287 [51]
was used to view the docking results and to convert the structures into pdb format. Binding
energies (ΔG, kcal/mol) of the docked ligands were obtained by ΔG = -RTLnKi, where R =
Gas constant (1.987∙10-3 kcal/mol); T = 298.15 K; Ki = Inhibition constant. PubChem
repository ("PubChem") was used to obtain the structure of the title organic acids required for
the analysis in pdb format (Figure 2).

Figure 1. The crystal structure of target protein (PDB ID: 7CBT).

CGA

EA

QA
Figure 2. The chemical structures of the title organic acids.

https://biointerfaceresearch.com/ 64
 https://doi.org/10.33263/BRIAC121.061073

3. Results and Discussion

3.1. Pharmacokinetic properties.

Drug-likeness estimated using the Lipinski rule of five, which is including of four
simple physicochemical parameter ranges (MWT ≤ 500, log P ≤ 5, H-bond donors ≤ 5, H-bond
acceptors ≤ 10) related to 90% of drugs with good oral bioavailability that have passed phase
II clinical trial. miLogP values of these compounds are observed to be < 5 (from -4.40 to 0.94)
showed their good permeability across the cell membrane. These compounds (Ellagic acid and
Quisqualic acid) were observed to have TPSA will be below 160 Å, molecular weight < 500,
No. of hydrogen bond donors ≤ 5, No. of hydrogen acceptor ≤ 10, n-violations 0, number of
rotatable flexible bonds >5. Solubility (logS) property of a drug in an aqueous solution affects
absorption and distribution characteristics. A compound's solubility is predicted using
ChemBioOffice 2018 software to identify the low solubility behavior and eliminate it from the
study based on logS value [52]. The preferred value is greater than -4. Solubility in water can
be considered as the number of hydrogen donors in molecules. A higher amount of hydrogen
bond donor translates a higher amount of water solubility, leading to high absorption into the
blood and action. The molecular weight of all compounds was found to be less than five
hundred, and thereby these compounds are predicted to be easily transported, diffused, and
absorbed than compared with the large molecules. Several hydrogen bond acceptors (notably
O and N atoms) and a number of hydrogen bond donors of the Ellagic and Quisqualic acids
were in agreement with Lipinski's rules (less 10 and 5, respectively). The numbers of rotatable
bands are important for conformational changes of the molecules. The oral bioavailability
criteria, the number of rotatable bands, should be less or equal to ten. All studied acids have a
number of rotatable bands between 0 and 5, consequently showing large conformational
flexibility. Topological polar surface area (TPSA) is correlated with the hydrogen bonding of
a drug molecule. Topological polar surface area is a very good indicator of the bioavailability
of the drug molecules. TPSA of the Ellagic and Quisqualic acids were observed in the range of
131.33 to 141.33 Å. The results of the calculations are presented in Table 1.
Table 1. Pharmacokinetic properties of the title compounds
Compound miLogP TPSA natoms MW nHBA nHBD nviolations nrotb LogS
CGA -0.45 164.74 25 354.31 9 6 1 5 -2.00
EA 0.94 141.33 22 302.19 8 4 0 0 -2.65
QA -4.40 131.33 13 189.13 8 4 0 3 1.69
*_mLogP: lipophilicity; TPSA: Total Polar Surface Area; MW: Molecular Weight; nHBA: number of
hydrogen bond acceptors; nHBD: number of hydrogen bond donors; n violations: number of violated
drug-likeness rules; nrotb: number of rotating bonds; LogS: solubility

3.2. Bioactivity

These bioactivity scores for organic molecules can be interpreted as active (when the
bioactivity score is > 0), moderately active (when the bioactivity score lies between − 5.0 and
0.0), and inactive (when the bioactivity score < −5.0). That means that Quisqualic acid can be
considered bioactive as a GPCR ligand, Ion channel modulator, Nuclear receptor ligand,
Protease inhibitor, Enzyme inhibitor, and moderately active as a Kinase inhibitor. The Ellagic
acid can be considered bioactive as a Nuclear receptor ligand, Enzyme inhibitor, and
moderately active as a GPCR ligand, Ion channel modulator, Kinase inhibitor, Protease
inhibitor, and Enzyme inhibitor. The Chlorogenic acid can be considered bioactive as a GPCR

https://biointerfaceresearch.com/ 65
 https://doi.org/10.33263/BRIAC121.061073

ligand, Ion channel modulator, Nuclear receptor ligand, Protease inhibitor, Enzyme inhibitor,
and moderately active as a Kinase inhibitor. The bioactivity score profile of all structures is
given in Table 2.

Table 2. Bioactivity scores against different drug targets of the title compounds
Compound GPCR Ion channel Kinase Nuclear receptor Protease Enzyme
ligand modulator inhibitor ligand inhibitor inhibitor
CGA 0.29 0.14 0.00 0.74 0.27 0.62
EA -0.29 -0.27 -0.01 0.11 -0.18 0.17
QA 0.52 1.26 -0.55 0.22 0.81 1.18

3.3. DFT calculations.

The highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular
orbital (LUMO) are known as the frontier molecule orbitals (FMOs) (Figure 3) that participate
in electronic properties, optical properties, UV/Vis spectrum, and chemical reactions [36]. We
used FMO analysis and the title organic acids' electronic properties by CAM-B3LYP/MidiX
level of theory. The calculated results are reported in Table 3. A detail of quantum molecular
descriptors of the title compounds such as Ionization Potential (IP) and Electron Affinities
(EA), Hardness (η), Softness (S), Electronegativity (μ), Electrophilic Index (ω), Electron
Donating Power (ω-), Electron Accepting Power (ω+) and Energy Gap (Eg) have been
calculated. The energy of HOMO is directly related to the ionization potential (IP), while the
energy of LUMO is related to the electron affinity (EA) [53]. The nucleophilicity of the studied
organic acids can be expressed by the potential ionization value, which is calculated as the
necessary energy for an electron's abstractions in the molecule. IP shows the easiness of the
title molecules' electron-donating due to electron abstraction is the first antioxidant mechanism.
Therefore, structures with low IP values can undergo oxidation more easily (Chlorogenic acid
with IP = 0.2095 eV). The Electron Affinity (EA) of the Quisqualic acid is the lowest (0.0050
eV). The global Hardness (η) corresponds to the energy gap between LUMO and HOMO. A
molecule with a small energy gap has high chemical reactivity, low kinetic stability, and a soft
molecule, while a hard molecule has a large energy gap [54-56]. Quisqualic acid higher global
Hardness, and it is a hard molecule. Electronegativity (μ) is a measure of the power of an atom
or a group of atoms to attract electrons and the chemical softness (S). It describes the capacity
of an atom or a group of atoms to receive electrons. The Electrophilic Index (ω) represents the
systems' stabilization energy when it becomes saturated by electrons. The results show that
Quisqualic acid has the lowest value ω and is nucleophilic in nature, whereas the Ellagic acid
has the highest value ω and is strongly electrophilic. In addition, among the set of compounds,
the Ellagic acid has the highest Electron Accepting Power (ω+) and Electron Donating Power
(ω-) values (0.0661 and 0.2046 eV, respectively). As shown in Table 3, the value of Eg for the
Chlorogenic acid (0.1522 eV) is the lowest. Thus, this structure can act better as an antioxidant.

Table 3. The calculated electronic properties in eV of the title organic acids by CAM-B3LYP/MidiX level of
theory.
Structures IP EA η S μ ω ω+ ω- Eg
CGA 0.2095 0.0573 0.0761 0.0381 0.1334 0.1169 0.0597 0.1932 0.1522
EA 0.2149 0.0622 0.0763 0.0382 0.1386 0.1258 0.0661 0.2046 0.1527
QA 0.2463 0.0050 0.1206 0.0603 0.1256 0.0654 0.0177 0.1433 0.2413

https://biointerfaceresearch.com/ 66
 https://doi.org/10.33263/BRIAC121.061073

CGA CGA
93 HOMO (Е = - 0.20953 eV) 94 LUMO (Е = - 0.05731 eV)

EA EA
77 HOMO (Е = - 0.21490 eV) 78 LUMO (Е = - 0.06225 eV)

QA QA
49 HOMO (Е = - 0.24526 eV) 50 LUMO (Е = - 0.00501 eV)
Figure 3. Calculated frontier molecule orbitals (FMOs) of the Chlorogenic, Ellagic, and Quisqualic acids by
CAM-B3LYP/MidiX level of theory.

3.4. Molecular docking analysis.

To study potential inhibitor of SARS-CoV-2 Mpro, AutoDock/Vina (MGL tools –

1.5.6), CHIMERA, Molegro Molecular Viewer 2.5, and Biovia Discovery Studio 4.5 were
applied. The ligands were docked to the active site of the receptor protein molecule (Figure 4).
The docking and glide scores of the Chlorogenic, Ellagic, and Quisqualic acids were presented
in Table 4, which has binding energy, glide score, number of hydrogen bonds, and steric
interactions formed. The maximum number of hydrogen bonds and steric interactions validates
the strong binding energy.
It is seen from Table 4 that the binding energy of the Chlorogenic, Ellagic, and
Quisqualic acids with SARS-CoV-2 main protease Mpro are -12.980, -15.955, -10.476 kcal/mol
with an inhibition constant 1.206, 2.012.10-6 and 0.021 µM, respectively. It is observed that the
studied organic acids are taken for the investigations exhibit better binding energy and various
interactions involving hydrogen bonds and steric interactions with the SARS-CoV-2 main
protease Mpro. The scoring function is a mathematical method predicting the strength of binding
affinity between protein and ligand complex.

https://biointerfaceresearch.com/ 67
 https://doi.org/10.33263/BRIAC121.061073

(a)

(b)

(c)
Figure 4. (a) Chlorogenic acid; (b) Ellagic acid; (c) Quisqualic acid binding interactions with SARS-CoV-2
main protease Mpro.

https://biointerfaceresearch.com/ 68
 https://doi.org/10.33263/BRIAC121.061073

Table 4. Molecular docking analysis of the Chlorogenic, Ellagic, and Quisqualic acids with SARS- CoV-2 main
protease Mpro.
Binding Inhibition Glide Number Number of 7CBT Receptor
Steric
Ligands Energy, constant Score, of H- Steric amino acids forming
Interactions
kcal/mol (ki), µM kcal/mol bonds Interactions H-bonds with ligands
Arg 4, Lys 5,
Ser 284, Glu
CGA -12.980 1.206 -94.824 6 2 Ser 284, Asn 214,
288
Glu 288
2.012 Arg 4, Lys 5,
EA -15.955 -76.344 8 3 Lys 5
.10-6 Ser 284, Glu 288
Ser 158,
Asn 151,
Ser 158, Asn 151, Asp Asp 153,
QA -10.476 0.021 -65.758 6 6
153, Cys 156, Asp 155 Cys 156,
Lys 102, Lie
152

4. Conclusions

Density functional theory calculations were performed to investigate the Chlorogenic,

Ellagic and Quisqualic acids' molecular structure by CAM-B3LYP/MidiX level of theory. The
ionization Potential (IP) of the Chlorogenic acid is 0.2095 eV, and this structure can act better
as an antioxidant. The global Hardness (η) of the Quisqualic acid is 0.1206 eV, and it is the
hardest molecule. The Ellagic acid has the highest Electron Accepting Power (ω+) and Electron
Donating Power (ω-) values (0.0661 and 0.2046 eV, respectively). miLogP values of these
compounds are observed to be < 5 (from -4.40 to 0.94) showed their good permeability across
the cell membrane. The Ellagic and Quisqualic acids were observed to have TPSA will be
below 160 Å, molecular weight < 500, number of hydrogen bond donors ≤ 5, number of
hydrogen acceptor ≤ 10, n-violations 0, number of rotatable flexible bonds >5. The Quisqualic
acid can be considered bioactive as a GPCR ligand, Ion channel modulator, Nuclear receptor
ligand, Protease inhibitor, Enzyme inhibitor, and moderately active as a Kinase inhibitor. The
Ellagic acid can be considered bioactive as a Nuclear receptor ligand, Enzyme inhibitor, and
moderately active as a GPCR ligand, Ion channel modulator, Kinase inhibitor, Protease
inhibitor, and Enzyme inhibitor. The Chlorogenic acid can be considered bioactive as a GPCR
ligand, Ion channel modulator, Nuclear receptor ligand, Protease inhibitor, Enzyme inhibitor,
and moderately active as a Kinase inhibitor.
It was found that the investigated ligands show good affinity towards of the SARS-
CoV-2 main protease Mpro compared to other known antiviral drugs: Colistin, Valrubicin,
Icatibant, Bepotastine, Epirubicin, Epoprostenol, Vapreotide, Aprepitant in which the binding
energy for SARS-CoV-2 main protease Mpro and them is -11.206, -10.934, -9.607, -10.273, -
9.091, 10.582, -9.892 and -11.376 kcal/mol. The binding energies for SARS-CoV-2 main
protease Mpro and the Chlorogenic, Ellagic, and Quisqualic acids are -12.980, -15.955 and -
10.476 kcal/mol with an inhibition constant 1.206, 2.012.10-6 and 0.021 µM, respectively in
which show the good binding affinity between them and SARS-CoV-2 main protease Mpro.

Funding

This research received no external funding.

https://biointerfaceresearch.com/ 69
 https://doi.org/10.33263/BRIAC121.061073

Acknowledgments

The authors acknowledged the technical support provided by prof. Siyamak Shahab at
Belarusian State University. The authors also highly thankful to the Editor of this Journal for
their valuable suggestions for strengthing this MS.

Conflicts of Interest

The authors declare no conflict of interest.

References

1. Sepay, N.; Sekar, A.; Halder, U.C.; Alarifi, A.; Afzal, M. Anti-COVID-19 terpenoid from marine sources: A
docking, admet and molecular dynamics study. Journal of molecular structure 2020, 1228, 129433,
https://doi.org/10.1016/j.molstruc.2020.129433.
2. Gioia, M.; Ciaccio, C.; De Simone, G.; Fasciglione, G.F.; di Masi, A.; Di Pierro, D.; Bocedi, A.; Ascenzi, P.;
Coletta, M. Role of proteolytic enzymes in the COVID-19 infection and promising therapeutic approaches.
Biochemical Pharmacology 2020, 182, 114225, https://doi.org/10.1016/j.bcp.2020.114225.
3. Zhu, H.; Wei, L.; Niu, P. The novel coronavirus outbreak in Wuhan, China. Global health research and policy
2020, 5, 1-3, https://doi.org/10.1186/s41256-020-00135-6.
4. Choudhary, J.; Dheeman, S.; Sharma, V.; Katiyar, P.; Karn, S.K.; Sarangi, M.K.; Chauhan, A.K.; Verma, G.;
Baliyan, N. Insights of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) pandemic: a current
review. Biological procedures online 2021, 23, 1-22, https://doi.org/10.1186/s12575-020-00141-5.
5. da Silva, S.; Jefferson R.; Silva, C.T.A.; Guarines, K.M.; Mendes, R.P.G.; Pardee, K.; Kohl, A.; Pena, L.
Clinical and laboratory diagnosis of SARS-CoV-2, the virus causing COVID-19. ACS infectious diseases
2020, 6, 2319-2336, https://doi.org/10.1021/acsinfecdis.0c00274.
6. Marinho, E.M.; de Andrade Neto, J.B.; Silva, J.; da Silva, C.R.; Cavalcanti, B.C.; Marinho, E.S.; Junior,
H.V.N. Virtual screening based on molecular docking of possible inhibitors of Covid-19 main protease.
Microbial Pathogenesis 2020, 148, 104365, https://doi.org/10.1016/j.micpath.2020.104365.
7. Osipiuk, J.; Azizi, S.A.; Dvorkin, S.; Endres, M.; Jedrzejczak, R.; Jones, K.A.; Kang, S.; Kathayat, R.S.; Kim,
Y.; Lisnyak, V.G. Structure of papain-like protease from SARS-CoV-2 and its complexes with non-covalent
inhibitors. Nat Commun 2021, 12, 1-9, https://doi.org/10.1038/s41467-021-21060-3.
8. Wang, H.; He, S.; Deng, W.; Zhang, Y.; Li, G.; Sun, J.; Zhao, W.; Yu, G.; Yin, Z.; Li, D. Comprehensive
insights into the catalytic mechanism of middle east respiratory syndrome 3C-Like protease and severe acute
respiratory syndrome 3C-Like protease. ACS catalysis 2020, 10, 5871-5890,
https://doi.org/10.1021/acscatal.0c00110.
9. Amin, S.A.; Banerjee, S.; Ghosh, K.; Gayen, S.; Jha, T. Protease targeted COVID-19 drug discovery and its
challenges: Insight into viral main protease (Mpro) and papain-like protease (PLpro) inhibitors. Bioorganic
& Medicinal Chemistry 2020, 29, 115860, https://doi.org/10.1016/j.bmc.2020.115860.
10. Jin, Z.; Zhaom, Y.; Sun, Y, Zhang, B.; Wang, H.; Wu, Y.; Zhu, Y.; Zhu, C.; Hu, T.; Du, X. Structural basis
for the inhibition of SARS-CoV-2 main protease by antineoplastic drug carmofur. Nature structural &
molecular biology 2020, 27, 529-532, https://doi.org/10.1038/s41594-020-0440-6.
11. Zhang, L.; Lin, D, Sun, X.; Curth, U.; Drosten, C.; Sauerhering, L.; Becker, S.; Rox, K.; Hilgenfeld, R. Crystal
structure of SARS-CoV-2 main protease provides a basis for design of improved α-ketoamide inhibitors.
Science 2020, 368, 409-412, https://doi.org/10.1126/science.abb3405.
12. Naveed, M.; Hejazi, V.; Abbas, M.; Kamboh, A.A.; Khan, G.J.; Shumzaid, M.; Ahmad, F.; Babazadeh, D.;
FangFang, X.; M.G, Faezeh. Chlorogenic acid (CGA): A pharmacological review and call for further
research. Biomedicine & Pharmacotherapy 2018, 97, 67-74, https://doi.org/10.1016/j.biopha.2017.10.064.
13. Tajik, N.; Tajik, M.; Mack, I.; Enck, P. The potential effects of chlorogenic acid, the main phenolic
components in coffee, on health: a comprehensive review of the literature. European Journal of Nutrition
2017, 56, 2215-2244, https://doi.org/10.1007/s00394-017-1379-1.
14. Lu, H.; Tian, Z.; Cui, Y.; Liu, Z.; Ma, X. Chlorogenic acid: A comprehensive review of the dietary sources,
processing effects, bioavailability, beneficial properties, mechanisms of action, and future directions.
Comprehensive Reviews in Food Science and Food Safety 2020, 19, 3130-3158,
https://doi.org/10.1111/1541-4337.12620.
https://biointerfaceresearch.com/ 70
 https://doi.org/10.33263/BRIAC121.061073

15. Lukitasari, M.; Rohman, M.S.; Nugroho, D.A.; Widodo, N.; Nugrahini, N.I.P. Cardiovascular protection
effect of chlorogenic acid: focus on the molecular mechanism. F1000Research 2020, 9, 1462,
https://doi.org/10.12688/f1000research.26236.1.
16. Williamson, G. Protection against developing type 2 diabetes by coffee consumption: assessment of the role
of chlorogenic acid and metabolites on glycaemic responses. Food & Function 2020, 11, 4826-4833,
https://doi.org/10.1039/D0FO01168A.
17. Yan, Y.; Liu, N.; Hou, N.; Dong, L.; Li, J. Chlorogenic acid inhibits hepatocellular carcinoma in vitro and in
vivo. The Journal of Nutritional Biochemistry 2017, 46, 68-73, https://doi.org/10.1016/j.jnutbio.2017.04.007.
18. Ji, L.; Jiang, P.; Lu, B.; Sheng, Y.; Wang, X.; Wang, Z.; Chlorogenic acid, a dietary polyphenol, protects
acetaminophen-induced liver injury and its mechanism. The Journal of Nutritional Biochemistry 2013, 24,
1911-1919, https://doi.org/10.1016/j.jnutbio.2013.05.007.
19. Nardini, M.; Cirillo, E.; Natella, F.; Scaccini, C. Absorption of phenolic acids in humans after coffee
consumption. Journal of Agricultural and Food Chemistry 2002, 50, 5735-5741,
https://doi.org/10.1021/jf0257547.
20. Konishi, Y.; Kobayashi, S. Transepithelial transport of chlorogenic acid, caffeic acid, and their colonic
metabolites in intestinal Caco-2 cell monolayers. Journal of Agricultural and Food Chemistry 2004, 52, 2518-
2526, https://doi.org/10.1021/jf035407c.
21. Hoelzl, C.; Knasmüller, S.; Wagner, K.H.; Elbling, L.; Huber, W.; Kager, N.; Ferk, F.; Ehrlich, V.; Nersesyan,
A.; Neubauer, O. Instant coffee with high chlorogenic acid levels protects humans against oxidative damage
of macromolecules. Molecular Nutrition & Food Research 2010, 54, 1722-1733,
https://doi.org/10.1002/mnfr.201000048.
22. Sapio, L.; Salzillo, A.; Illiano, M.; Ragone, A.; Spina, A.; Chiosi, E.; Pacifico, S.; Catauro, M.; Naviglio, S.
Chlorogenic acid activates ERK1/2 and inhibits proliferation of osteosarcoma cells. Journal of Cellular
Physiology, 2020, 235, 3741-3752, https://doi.org/10.1002/jcp.29269.
23. Evtyugin, D.D.; Magina, S.; Evtuguin, D.V. Recent advances in the production and applications of Ellagic
acid and its derivatives. A review. Molecules 2020 25, 2745, https://doi.org/10.3390/molecules25122745.
24. Alfei, S.; Marengo, B.; Zuccari, G. Oxidative Stress, Antioxidant Capabilities, and Bioavailability: Ellagic
Acid or Urolithins?. Antioxidants 2020, 9, 707, https://doi.org/10.3390/antiox9080707.
25. Baradaran, R.V.; Ghadiri, M.; Ramezani, M.; Askari, V.R. Antiinflammatory and anti‐cancer activities of
pomegranate and its constituent, ellagic acid: Evidence from cellular, animal, and clinical studies.
Phytotherapy Research 2020, 34, 685-720, https://doi.org/10.1002/ptr.6565.
26. Aslan, A.; Hussein, Y.T.; Gok O.; Beyaz, S.; Erman, O.; Baspinar, S. Ellagic acid ameliorates lung damage
in rats via modulating antioxidant activities, inhibitory effects on inflammatory mediators and apoptosis-
inducing activities. Environmental Science and Pollution Research 2020, 27, 7526-7537,
https://doi.org/10.1007/s11356-019-07352-8.
27. Wang, N.; Wang, Z.Y.; Mo, S.L.; Loo, T.Y.; Wang, D.M.; Luo, H.B.; Yang, D.P.; Chen, Y.L.; Shen, J.G.;
Chen, J.P. Ellagic acid, a phenolic compound, exerts antiangiogenesis effects via VEGFR-2 signaling
pathway in breast cancer. Breast Cancer Research and Treatment 2012, 134, 943–955,
https://doi.org/10.1007/s10549-012-1977-9.
28. Ahire, V.; Kumar, A.; Mishra, K.P.; Kulkarni, G. Ellagic Acid Enhances Apoptotic Sensitivity of Breast
Cancer Cells to γ-Radiation. Nutrition Cancer 2017, 69, 904–910,
https://doi.org/10.1080/01635581.2017.1339811.
29. Ceci, C.; Lacal P.M.; Tentori L.; De Martino, M.G.; Miano, R.; Graziani, G. Experimental evidence of the
antitumor, Antimetastatic and antiangiogenic activity of ellagic acid. Nutrients 2018, 11, 1756,
https://doi.org/10.3390/nu10111756.
30. Gupta, P.; Mohammad, T.; Khan, P.; Alajmi, M.F.; Hussain, A.; Rehman, M.T.; Hassan M.I. Evaluation of
ellagic acid as an inhibitor of sphingosine kinase 1: A targeted approach towards anti-cancer therapy.
Biomedicine & Pharmacotherapy 2019, 118, 109245, https://doi.org/10.1016/j.biopha.2019.109245.
31. Yousuf, M.; Shamsi, A.; Khan, P.; Shahbaaz, M.; AlAjmi, M.F.; Hussain, A.; Hassan, G.M.; Islam, A.;
Rizwanul, H.; Q.M, Hassan.; M. Ellagic acid controls cell proliferation and induces apoptosis in breast cancer
cells via inhibition of cyclin-dependent kinase 6. International Journal of Molecular Sciences 2020, 21, 3526,
https://doi.org/10.3390/ijms21103526.
32. Wang, N.; Wang, Q.; Tang, H.; Zhang, F.; Zheng, Y.; Wang, S.; Zhang, J.; Wang, Z.; Xie X. Direct inhibition
of ACTN4 by ellagic acid limits breast cancer metastasis via regulation of β-catenin stabilization in cancer
stem cells. J Exp Clin Cancer Res 2017, 36, 1-19, https://doi.org/10.1186/s13046-017-0635-9.

https://biointerfaceresearch.com/ 71
 https://doi.org/10.33263/BRIAC121.061073

33. Chang, S.; Li, B.; Chen, T.; He, X.; Wu, B. Determination of Quisqualic Acid in quisqualis fructus by Pre-
column Derivatization and High Performance Liquid Chromatography. Journal of Analytical Chemistry
2020, 75, 1018-1023, https://doi.org/10.1134/S1061934820080055.
34. Murakoshi I.; Kaneko M.; Koide C.; Ikegami F. Enzymatic synthesis of the neuroexcitatory amino acid
quisqualic acid by cysteine synthase, Phytochemistry 1986, 25, 2759-2763, https://doi.org/10.1016/S0031-
9422(00)83736-X.
35. Chase, L.A.; Roon R.J.; Wellman, L.; Beitz, A.J, Koerner, J.F. L-Quisqualic acid transport into hippocampal
neurons by a cystine-sensitive carrier is required for the induction of quisqualate sensitization. Neuroscience
2001, 106, 287-301, https://doi.org/10.1016/S0306-4522(01)00278-0.
36. Bitzer, M.; Schaeffel, F. Effects of quisqualic acid on retinal ZENK expression induced by imposed defocus
in the chick eye. Optometry and Vision Science 2004, 81, 127-136, https://doi.org/10.1097/00006324-
200402000-00011.
37. Rochford, J.; Sen, A.P.; Rousse, I. Welner S.A. The effect of quisqualic acid-induced lesions of the nucleus
basalis magnocellularis on latent inhibition. Brain Research Bulletin 1996, 41, 313-317,
https://doi.org/10.1016/S0361-9230(96)00191-8.
38. Rasool, N.; Akhtar, A.; Hussain, W. Insights into the inhibitory potential of selective phytochemicals against
Mpro of 2019-nCoV: a computer-aided study. Structural Chemistry 2020, 31, 1777-1783,
https://doi.org/10.1007/s11224-020-01536-6.
39. Shahab, S.; Sheikhi, M.; Alnajjar, R.; Al Saud, S.; Khancheuski, M.; Strogova, A. DFT investigation of
atazanavir as potential inhibitor for 2019-nCoV coronavirus M protease. Journal of Molecular Structure
2020, 1228, 129461, https://doi.org/10.1016/j.molstruc.2020.129461.
40. Agamah, F.E.; Mazandu, G.K.; Hassan, R.; Bope, C.D.; Thomford N.E, Ghansah, A.; Chimusa E.R..
Computational/In silico methods in drug target and lead prediction. Briefings in Bioinformatics 2020, 21,
1663-1675, https://doi.org/10.1093/bib/bbz103
41. D. Rognan, The impact of In silico screening in the discovery of novel and safer drug candidates,
Pharmacology & Therapeutics 2017, 175, 47-66, https://doi.org/10.1016/j.pharmthera.2017.02.034.
42. Sachdev, K.; Gupta, M.K. A. Comprehensive review of feature based methods for drug target interaction
prediction. Journal of biomedical informatics 2019, 93, 103159, https://doi.org/10.1016/j.jbi.2019.103159.
43. Lipinski, C.A.; Lombardo, F.; Dominy B.W.; Feeney, P.J. Experimental and computational approaches to
estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery
Reviews 1997, 23, 3-25, https://doi.org/10.1016/S0169-409X(96)00423-1.
44. Husain, A.; Ahmad, A.; Khan, S.A.; Asif, M.; Bhutani, R.; Al-Abbasi, F.A. Synthesis, molecular properties,
toxicity and biological evaluation of some new substituted imidazolidine derivatives in search of potent anti-
inflammatory agents. Saudi Pharmaceutical Journal 2016, 24, 104-114,
https://doi.org/10.1016/j.jsps.2015.02.008.
45. Frisch, M.J.; Trucks, G.W.; Schlegel, H.B.; Scuseria, G.E.; Robb, M.A.; Cheeseman, J.R.; Montgomery, J.A.,
Jr.; Vreven, T.; Kudin, K.N.; Burant, J.C.; et al. Gaussian 09 Revision, E01; Wallingford, CT, USA, 2009.
46. Yanai, T.; Tew, D.P.; Handy, N.C. A new hybrid exchange–correlation functional using the Coulomb-
attenuating method (CAM-B3LYP). Chemical Physics Letters 2004, 393, 51-57,
https://doi.org/10.1016/j.cplett.2004.06.011.
47. Lynch, B.J.; Truhlar D.G. Small basis sets for calculations of barrier heights, energies of reaction, electron
affinities, geometries, and dipole moments. Theoretical Chemistry Accounts 2004, 111, 335-344,
https://doi.org/10.1007/s00214-003-0518-3
48. Shahab, S.; Sheikhi, M. Antioxidant Properties of the Phorbol: A DFT Approach. Russian Journal of Physical
Chemistry B 2020, 14, 15-18, https://doi.org/10.1134/S1990793120010145.
49. Frisch, A.; Nielson, A.B.; Holder, A.J. GAUSSVIEW User Manual, Gaussian Inc., Pittsburgh, PA, 2000.
50. Trott, O.; Olson, A.J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring
function, efficient optimization, and multithreading. Journal of Computational Chemistry 2009, 31, 455-461,
https://doi.org/10.1002/jcc.21334.
51. Sudomova, M.; Hassan, S.T.S.; Khan, H.; Rasekhian, M.; Nabavi, SM. A multi-biochemical and In silico
study on anti-enzymatic actions of pyroglutamic acid against pde-5, ace, and urease using various analytical
techniques: unexplored pharmacological properties and cytotoxicity evaluation. Biomolecules 2019, 9, 9392,
https://doi.org/10.3390/biom9090392.

https://biointerfaceresearch.com/ 72
 https://doi.org/10.33263/BRIAC121.061073

52. Ali, M.C.; Nur, A.J.; Khatun, M.S.; Dash, R.; Rahman, M.M.; Karim, M.M. Identification of potential SARS-
CoV-2 main protease inhibitors from Ficus Carica Latex: An in-silico approach. J Adv Biotechnol Exp Ther
2020, 3, 57-67, https://doi.org/10.5455/jabet.2020.d157.
53. Amati, M.; Stoia, S.; Baerends, E.J. The Electron Affinity as the Highest Occupied Anion Orbital Energy
with a Sufficiently Accurate Approximation of the Exact Kohn–Sham Potential. Journal of Chemical Theory
and Computation 2019, 16, 443-452, https://doi.org/10.1021/acs.jctc.9b00981.
54. Sheikhi, M.; Shahab, S.; Khaleghian, M.; Hajikolaee, F.H.; Balakhanava, I.; Alnajjar, R. Adsorption
properties of the molecule resveratrol on CNT (8, 0-10) nanotube: geometry optimization, molecular
structure, spectroscopic (NMR, UV/Vis, excited state), FMO, MEP and HOMO-LUMO investigations.
Journal of Molecular Structure 2018, 1160, 479-487, https://doi.org/10.1016/j.molstruc.2018.01.005.
55. Shahab, S.; Sheikhi M.; Filippovich L.; Anatol'evich, D.E.; Yahyaei H. Quantum chemical modeling of new
derivatives of (E, E)-azomethines: synthesis, spectroscopic (FT-IR, UV/Vis, polarization) and
thermophysical investigations. Journal of Molecular Structure 2017, 1137, 335-348,
https://doi.org/10.1016/j.molstruc.2017.02.056.
56. Shahab, S.; Sheikhi, M.; Filippovich, L.; Alnajjar, R.; Ihnatovich, Z.; Laznev, K.; Strogova, A.; Atroshko,
M.; Drachilovskaya, M. Quantum-chemical modeling, spectroscopic (FT-IR, excited states, UV/Vis,
polarization, and Dichroism) studies of two new benzo [d] oxazole derivatives. Journal of Molecular
Structure 2020, 1202, 127352, https://doi.org/10.1016/j.molstruc.2019.127352.

https://biointerfaceresearch.com/ 73