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2,4-dichloro-6-(1,4,5-triphenyl-1 H -imidazol-2-yl) phenol: synthesis, DFT
analysis, Molecular docking, molecular dynamics, ADMET properties against
COVID-19 main protease (Mpro: 6...
Article in Molecular Physics · May 2024
DOI: 10.1080/00268976.2024.2353331
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Molecular Physics
An International Journal at the Interface Between Chemistry and
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ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/tmph20
2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol-2yl) phenol: synthesis, DFT analysis, Molecular
docking, molecular dynamics, ADMET properties
against COVID-19 main protease (Mpro:
6WCF/6Y84/6LU7)
S. Sonadevi, D. Rajaraman, M. Saritha, Peter Solo & L. Athishu Anthony
To cite this article: S. Sonadevi, D. Rajaraman, M. Saritha, Peter Solo & L. Athishu Anthony (13
May 2024): 2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol-2-yl) phenol: synthesis, DFT analysis,
Molecular docking, molecular dynamics, ADMET properties against COVID-19 main protease
(Mpro: 6WCF/6Y84/6LU7), Molecular Physics, DOI: 10.1080/00268976.2024.2353331
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MOLECULAR PHYSICS e2353331
https://doi.org/10.1080/00268976.2024.2353331
RESEARCH ARTICLE
2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol-2-yl) phenol: synthesis, DFT analysis,
Molecular docking, molecular dynamics, ADMET properties against COVID-19
main protease (Mpro: 6WCF/6Y84/6LU7)
S. Sonadevia , D. Rajaramana , M. Sarithaa , Peter Solob and L. Athishu Anthonyc
a Department of Chemistry, St. Peter’s Engineering College (Autonomous), Hyderabad, Telangana, India; b Department of Chemistry,
St Joseph’s College Jakhama (Autonomous), Nagaland, India; c Department of Chemistry, St Joseph University, Dimapur, Nagaland, India
ABSTRACT
ARTICLE HISTORY
New derivatives of 2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol-2-yl) phenol (DPIP) have been successfully synthesised and characterised using spectral methods such as FT-IR, 1 H NMR and 13 C
NMR. Density functional theory (DFT) approach at B3LYP/6-311 G (d, p) level of theory is used to
determine optimised bond parameters and single crystal XRD investigation of related derivatives
confirms the structure of DPIP bond parameters. The single crystal XRD measurements and the
optimised geometrical parameters produced by the DFT calculation agree well. The FT-IR bands
seen in the experiment were attributed to distinct normal modes of the molecule. Frontier molecular orbital computations described the molecule stability, chemical reactivity and charge transfer.
Atomic charges determined via Mulliken population analysis on the different DPIP atoms. MEP,
which is mapped to the electron density surfaces, has discovered potential reactive sites of the
molecule. The reported molecule is used as a potential NLO material since it has a high μβ0 value.
Binding affinities were discovered using molecular docking against the COVID-19 major protease
(Mpro: 6WCF/6Y84/6LU7). The behaviour of the complex structure formed by the Covid-19 protein
under in silico physiological conditions was then confirmed by a 100 ns molecular dynamic simulation which looked at the structure stability over time and revealed a stable conformation and binding
pattern in an environment of imidazole derivatives. Furthermore, favourable to moderate anti-viral
activity was revealed by an in-silico analysis that anticipated the compound absorption, distribution,
metabolism, excretion and toxicity profiles (ADMET).
Received 5 February 2024
Accepted 3 May 2024
CONTACT D. Rajaraman
Telangana 500043, India
rajaraman4389@gmail.com
Imidazole; DFT; molecular
docking; ADMET analysis;
dynamics simulation
Department of Chemistry, St. Peter’s Engineering College (Autonomous), Hyderabad,
Supplemental data for this article can be accessed online at https://doi.org/10.1080/00268976.2024.2353331.
© 2024 Informa UK Limited, trading as Taylor & Francis Group
KEYWORDS
2
S. SONADEVI ET AL.
1. Introduction
Within the realm of organic chemistry, the significance
of compounds featuring N-heterocycles is paramount.
Molecular structures incorporating C-N bonds play a
crucial role in numerous natural products and biological
activities. The synthesis of N-heterocycles, particularly
those comprising a five-membered aromatic structure,
becomes pivotal for diversifying their structural presence across various sectors. The creation of C-N bonds
emerges as an attractive method to introduce nitrogen
moieties, thereby broadening the applications and understanding of N-heterocycles [1–4]. Additionally, pharmaceuticals featuring imidazole exert an influence on
various receptor types, including adreno-receptors, histaminic receptors and dopamine receptors [5]. Moreover, the imidazole core has been identified as an essential isostere in the generation and synthesis of a diverse
range of physiologically active compounds, serving as
a necessary counterpart for pyrazole, triazole, tetrazole,
thiazole, amide and oxazole. Furthermore, imidazoles
exhibit the potential to address the limitations of current medications and present opportunities for development as anticancer agents [6]. 2-Thiohydantoin derivatives (2-thioxoimidazolidin-4-one) represent a significant category of imidazole analogs and are a preferred
framework in medicinal chemistry. This preference stems
from their diverse biological activities, making them crucial in the exploration of potential novel therapeutic
classes. Thiohydantoin derivatives have displayed a spectrum of biological actions, including anti-cancer properties [7,8], antiviral effects [9,10], anticonvulsant activity
[11], antimicrobial effects [12], efficacy against bacteria and fungi [13], antidiabetic [14], antineuroinflammatory [15], hypolipidemic activity [16], antiulcer and
anxiolytic properties [17], antioxidant attributes [18],
among others. Additionally, thiohydantoin serves as a
precursor for amino acid production and constitutes a
fundamental structure in several natural products [19].
Imidazole derivatives have gained significant interest in
the realm of preventing metal corrosion, driven by their
cost-effectiveness, straightforward synthesis, and motivating attributes [20]. These compounds are deemed
environmentally friendly corrosion inhibitors owing to
their diverse pharmacological, biological and chemical
properties [21–25]. Various studies have assessed imidazole molecules as efficient corrosion additives in diverse
scenarios [26, 27]. Understanding the physicochemical
behaviour of pharmaceuticals and their intermolecular
interactions is crucial for understanding drug action
in the fields of medical and pharmaceutical chemistry.
Drug physicochemical qualities, such as solubility, density, and volumes occupied by drug molecules and other
components in solution, are important considerations for
the development of pharmaceutical dosage forms and
drug development [28].
Density Functional Theory (DFT), a methodology
for computing electronic structures of atoms, molecules
and solids grounded in fundamental quantum mechanics principles, has proven effective in elucidating material
properties. Since the 1970s, it has been a widely favoured
quantum-mechanical tool in solid-state physics, finding
applications in both physics and chemistry. However, a
surge in its utilisation occurred during the 1990s due to
advancements in quantum-chemical calculations, resulting in improved precision and acceptance. Its success is
attributed to a favourable price/performance ratio compared to electron correlated wave function-based methods such as linked cluster, enabling accurate investigations into more intricate and significant molecular systems. Consequently, DFT stands out as the most widely
employed approach for electronic structure analysis. The
analysis of Frontier Molecular Orbitals (FMOs) through
DFT for chemical compounds is pivotal in medicinal
design, playing a crucial role in determining reactivity
[29,30]. As an illustration, two essential factors pivotal
for assessing pharmacological attributes involve the energies associated with the Highest Occupied Molecular
Orbital (HOMO) and the Lowest Unoccupied Molecular
Orbital (LUMO). An acceptor molecule with appropriately low energy levels and unoccupied molecular orbitals
has the capacity to accept electrons from a molecule possessing the HOMO. Research has established a correlation between the energies of Frontier Molecular Orbitals
(FMOs) in certain newly developed active compounds,
their structural refinement and their biological mechanisms [31,32]. Enhancing comprehension of molecular properties, including aspects like hydrogen bonding, chemical reactivity, dipole moment and the presence of partial positive and negative charges, is facilitated
through the utilisation of electrostatic potential maps.
By employing partial positive and negative charges, we
can tentatively predict the sites of nucleophilic and electrophilic additions on molecules [33,34]. Consequently,
the electrostatic potential mapping (ESP) of the compound is conducted using Density Functional Theory
(DFT).
The current study effectively synthesised novel imidazole with a good yield. FT-IR, 1 H, and 13 CNMR spectroscopy were employed to investigate the molecular
structure and spectroscopic features. Furthermore, Density Functional Theory (DFT) is employed to compare
the geometrical and electrical properties of the chemical under consideration with experimental data, hence
improving understanding of these aspects. However, in
MOLECULAR PHYSICS
order to ascertain whether the material that was synthesised for the first time in this work could be a viable
antiviral medication for use in the treatment of SARSCoV-2, we conducted in-silico research. The intermolecular interactions between produced DPIP chemical and
receptor molecules were ascertained through research
utilising molecular docking and molecular dynamic simulation.
2. Experimental
3
142.76 (C = N carbon). 115.53, 121.91, 122.63, 124.36,
126.57, 127.86,129.09, 129.19, 129.34, 129.58, 129.77,
130.30, 130.47, 131.76, 132.75, 134.50,136.40 (aromatic
and ipso carbon), Chemical Formula: C27H18Cl2N2O,
Exact Mass: 456.08, Molecular Weight: 457.35, m/z:
456.08 (100.0%), 458.08 (64.3%), 457.08 (30.0%), 459.08
(18.9%), 460.07 (10.2%), 458.09 (4.2%), 461.08 (3.1%),
460.08 (2.9%), Elemental Analysis: C, 70.91; H, 3.97;
Cl, 15.50; N, 6.13; O, 3.50, (Cal.m/z): 430.17 (100.0%),
431.17 (32.4%), 432.17 (5.4%), (Cal. Elemental Analysis):
C, 80.91; H, 5.15; N, 6.51; O, 7.43.
2.1. Materials and methods
All the solvents utilised were of high spectral purity.
The compound melting point was determined using
open capillaries and remains uncorrected. Infrared (IR)
spectra were acquired using an AVATAR-330 FT-IR
spectrometer (Thermo Nicolet) with potassium bromide
(KBr) in pellet form. Proton nuclear magnetic resonance (1 H NMR) spectra were recorded at 400 MHz, and
carbon-13 nuclear magnetic resonance (13 C NMR) spectra were recorded at 100 MHz on a BRUKER model, with
CDCl3 serving as the solvent. Tetramethyl silane (TMS)
was employed as the internal reference for NMR spectra,
and chemical shifts were reported in δ units (parts per
million) relative to the standard. The 1 H NMR splitting
patterns were denoted as singlet (s), doublet (d), doublet
of doublet (dd), triplet (t), quartet (q), and multiplet (m).
Coupling constants were expressed in Hertz (Hz).
2.3. Computational method
2.2. Synthesis of
2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol-2-yl)
phenol derivatives
2.4. Molecular docking studies
A blend comprising 20 ml of 100% ethanol, 6.0 mmol
of benzil, 24.0 mmol of ammonium acetate, 27.0 mmol
of aniline, and 9.0 mmol of 3,5-dichlorosalicylaldehyde
was prepared and the catalyst C4 H10 BF3 O (2/3 drops)
was added [35]. The reaction mixture underwent reflux
at the boiling point of ethanol (78°C) for approximately
12 hours. Thin-layer chromatography (TLC) progress
was monitored using ethyl acetate: benzene (2:8) as
the eluent. The reaction mixture was extracted using
dichloromethane, and column chromatography was
employed for the purification of the resulting product.
The final product, 2,4-dichloro-6-(1,4,5-triphenyl-1Himidazol-2-yl) phenol derivatives (DPIP), was obtained
in a pure form through the gradual evaporation of the
solvent. White solid: m.p. 240-244°C and yield 87%.
IR (KBr) (cm−1 ): 2406–3053 (C-H stretching), 1594
(C = N stretching), 1256 (C-O ring stretching), etc. 1 H
NMR (ppm): 6.379 (s, OH-proton) 6.385-7.521 (m, 17H
aryl protons), 13 C NMR (ppm): 142.76 (C-O carbon),
Theoretical investigations on compound DPIP were conducted utilising the Gaussian 09W programme package,
employing the density functional theory (DFT) method
at the B3LYP/6-311G (d, p) level of theory. The optimised
bond parameters were determined using the same basis
set. Theoretical calculations were employed to ascertain
the dipole moment, polarizability, and first-order hyperpolarizability of the molecule, providing insights into
its nonlinear optical (NLO) activity. Additionally, Natural Bond Orbital (NBO) analysis was carried out to
elucidate both intermolecular and intramolecular interactions within the compound. Furthermore, calculations
at the same level of theory were utilised to determine
HOMO-LUMO energy, Mulliken charges, and molecular
electrostatic potential [36–38].
Currently, the predominant tool for predicting proteinligand interactions is molecular docking studies [39].
These studies elucidate the interactions between a drug
and proteins by introducing a small molecule into
the binding site. In this investigation, molecular docking reconstruction was carried out using Argus Lab
4.0.1. [40]. The 3D structures of the 6WCF, 6Y84, and
6LU7 proteins were obtained from the protein databank
(http://www.rcsb.org/pdb). Subsequently, the ligand was
introduced, and docking calculations were performed
using shape-based tracking and the A-score scoring capability. The evaluation function, responsible for assessing
the affinity between the ligand and the protein target,
was employed. The adaptive design allowed docking of
grids at the protein coupling sites, and a function-based
connection was designed for ligand molecules lacking
rotatable bonds. During the docking process, torsions
and adjustments (postures) were generated for each pivot
point. Ten free runs were conducted for each configuration, and one pose was returned for each run. The
best docking model was selected based on the lowest
4
S. SONADEVI ET AL.
binding energy calculated by the Argus Lab software,
and the most suitable binding conformation was chosen, assuming a hydrogen bonding interaction between
the ligand and the protein near the substrate binding
site. Lower energy conformations indicate a stronger tendency to form bonds, as higher energy causes structural adjustments. The receptor model, presented in
the Brookhaven PDB document, showcases 2D and 3D
connections, viewable in Discovery Studio 4.5 versions
[41–43].
involve assessing physicochemical, pharmacokinetic, and
drug-like criteria. Predictions for absorption, distribution, metabolism, excretion, and toxicity are then made
for future considerations. The potential medicinal similarity of the specified compound was determined using
rule-based Lipinski filters [48]. Drug-likeness properties,
along with absorption, distribution, metabolism, excretion, and toxicity considerations, as well as pharmacokinetic characteristics, were generated using the pkCSM
web server [49] and SwissADME [50].
2.5. Molecular dynamics simulation
3. Results and discussion
For the MD simulation, the optimal conformer was
chosen based on intermolecular interactions and docking score values obtained from the docking analysis.
Topology files for all complexes were generated using
AMBERTOOLS20 with the AMBER19ffSB force field
through the LEAP module [44]. The complex structure
was established utilising a TIP3P water model within
a 10 × 10 × 10 water box on each side, and the system
was neutralised by introducing Cl-/Na + ions [45]. Subsequently, all complex systems underwent minimisation
using steepest descent and conjugate gradient methods
with 500 and 1500 steps, respectively. An annealing process was carried out at a temperature ranging from 0 to
310 K, lasting 500 picoseconds (ps) with NVT ensembles. Equilibration was achieved through NPT ensembles
over a period of 500 ps. Finally, the production step for
each complex extended up to 100 ns using NPT ensembles, maintaining a temperature of 310 K and a pressure
of 1 bar via Langevin thermostat and Berendsen barostat methods [46]. MD trajectories were extracted every 2
femtoseconds using VMD software from the production
output files for subsequent analysis [47].
3.1. Spectroscopic techniques
2.6. Drug likeness and ADMET prediction
The DPIP compound structure was drawn using ChemDraw software version 12, 1986-2009, Cambridge Soft
Corp., USA. The structure was checked and cleaned up
through pressing the structure icon, saved as an MDL
Mol file (∗.mol), and were ready for uploading into the
SwissADME server; http://www.swissadme.ch/ (accessed
on 15 April 2020). In the SwissADME server, the import
icon in the molecular sketcher was clicked and a new window opened to select the prepared structure, presented
on the molecular sketcher, then transferred this structure to the SMILES format. After that, the icon ‘Run’
was pressed to give the ADMET parameters and related
values. Therapeutic similarity and ADMET serve as crucial methods in identifying potential therapeutic candidates. Initial evaluations in the drug development process
The synthesis route is depicted in Scheme 1. The FT-IR
spectral analysis of the compound DPIP is elaborated
below. Generally, imines exhibit a robust C = N stretching vibration within the 1500-1600 cm−1 range. In the
DPIP compound, the C = N stretching band is observed
at 1459 cm−1 , demonstrating a high absorption band.
This presence supports the imidazole ring framework.
Additionally, the OH stretching frequency is observed at
3431cm−1 , while the C-Cl stretching frequency is noted
at 696 cm−1 . The aromatic C-H stretch band appears in
the broad range of 2406-3053 cm−1 . The imine, aliphatic,
and aromatic C-H stretching frequencies observed confirm the characteristics of the DPIP compound.
The 1 H NMR spectra of DPIP were recorded in
CDCl3. The obtained signals were assigned and determined based on their positions, multiplicities, and integral values. Generally, aromatic proton signals manifest
in the higher frequency range at 7.00 ppm due to the
magnetic anisotropic effect. In the 1 H NMR spectrum of
DPIP, a singlet at 6.379 ppm corresponds to the OH proton of the 3,5-dichlorosalicylaldehyde moiety. Signals in
the range of 6.385–7.521 ppm represent seventeen protons, integral due to aromatic protons. The 13 C NMR
spectra of 2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol2-yl) phenol derivatives were recorded at 100 MHz. In
the 13 C-NMR spectrum of DPIP, the C-O carbon signal
is observed at 153.07 ppm, and the C = N carbon signal
of the imidazole compound appears at 142.76 ppm. Aromatic and ipso-carbon signals are evident in the range of
121.91–136.40 ppm. Figures 1–3 present the FT-IR, 1 HNMR, and 13 C-NMR spectrum of the DPIP compound.
3.2. Density functional theory study
3.2.1. Conformational and molecular geometry
analysis
The different DPIP conformers have been derived
by minimising the potential energy in all geometrical
MOLECULAR PHYSICS
5
Scheme 1. Synthesis of 2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol-2-yl) phenol derivatives
parameters by rotating the dihedral angle C8-C20-O30H50 from 0°−360° in 10° intervals using B3LYP/6311G (d,p) level of theory. Figure 1 displays the different conformers obtained from the potential energy
surface scan of the DPIP molecule. The conformers at
10° and 180° exhibited potential energies of −2110.8635
and −2110.8677 hartree, respectively. Three conformers exhibit maximal potential energies −2110.8568,
−2110.8587 and −2110.8583 at torsion angles of -80°,
80° and 250°. The chemical structure at 180 degrees
has reached its minimum energy of −2110.8677 hartree
on the potential surface, making it a stable structure
for further exploration. Table S1 displays the relative
energies of potential conformers of DPIP. Optimisation of 2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol-2yl) phenol has been performed by DFT at the B3LYP/6311G (d, p) level of theory. The optimised parameters,
namely bond lengths, bond angles and dihedral angles
are slightly higher than those of XRD values of reference compound because the theoretical calculations are
of an isolated molecule in the gaseous phase and the
XRD results are of the molecule in the solid state [51,52].
The optimised structure of DPIP is shown in Figure
4. In the title compound, the bond lengths observed
in various pairs, such as C2-N4, N4-C5, C5-N3, C1N3, C36-N3, C9-Cl47, C11-Cl48, C8-O49, and H50-O49
are found to be 1.47, 1.30, 1.47, 1.46, 1.47, 1.75, 1.76,
1.43, and 0.95 Å, respectively. Correspondingly, the bond
angles in various groups, such as C14-C2-N4, C1-C2N4, C2-N4-C5, N4-C5-N3, N4-C5-C6, C1-N3-C36, C5N3-C36, N3-C5-C6, 37C37-C36-N3, C38-C36-N3, H50O49-C8, O49-C8-C6, O49-C8-C11, Cl48-C11-C8, Cl48C11-C12, C12-C9-Cl47 and C7-C9-Cl47 are measured
at 125.68°, 108.98°, 106.22°, 111.57°, 124.16°, 113.51°,
113.88°, 124.25°, 119.87°, 120.15°, 109.42°, 120.03°,
119.98°, 119.98°, 120.01°, 120.07°, and 119.92°, respectively. Meanwhile, dihedral angles at C15-C14-C2-N4,
C14-C2-N4-C5, C2-N4-C5-C6, C2-N4-C5-N3 and N4C5-N3-C36 are determined as −0.61°, −178.02°, 166.65°,
−12.89°, and 140.72°, respectively. The results indicate
that the synthesised imidazole derivatives DPIP exhibit
planar geometry. Comparison with the bond lengths,
bond angles, and dihedral angles of the title compound
with the single crystal X-ray structure [53] reveals slightly
higher values in the theoretical calculations.
3.2.2. Vibrational assignments
Using the acquired FT-IR data, which are displayed in
Figure 1, the fundamental modes of the DPIP molecule
were examined and given vibrational assignments. At
the appropriate optimised structure, the harmonic vibrational wavenumbers were computed using the DFT
6
S. SONADEVI ET AL.
Figure 1. Combined experimental (FT-IR) and theoretical (IR) spectra of DPIP.
method. As a result, a scale factor was utilised to provide a generous result that is better in line with the
experimental data. The DFT/B3LYP approach has thus
been evenly scaled using the scale factor 0.9608 [54].
In the present investigation C5-N4 stretching frequency
observed at 1459 cm−1 is very strong band in FT-IR its
theoretical frequency is about 1466 cm−1 . The experimental and theoretical value for C = N band coincides
well with literature [55]. Aromatic C = C stretching
vibrations of the phenyl ring appeared in the range of
1526-1666 cm−1 . In our study, the frequencies were calculated at 1578-1550 cm−1 in IR and its experimental
frequency observed at 1594 cm−1 . The identification of
C-N vibration is a very difficult task, since mixing of several bands are possible in this region. However, with the
help of theoretical calculation B3LYP 6-311G (d, p) the
C-N stretching vibrations are calculated. In this study,
the band at 1256 cm−1 in IR spectrum is assigned to CN stretching vibration. In the present investigation the
calculated N3-C36, N3-C5 and N3-C1 stretching vibration appeared at 1399, 1370, 1246 cm−1 show excellent
agreement with experimental data.
The aromatic C-H stretching vibrations are normally
found between 3100 and 3000 cm−1 [56]. 2,4-dichloro-6(1,4,5-triphenyl-1H-imidazol-2-yl) phenol, these modes
were calculated in the range of 3054-3120 cm−1 . Most of
these calculated frequencies find a correlation with the
strongly observed infrared bands in the range 3053 cm−1 .
The band at 3431 (Experimental) and 3500 (B3LYP)
cm−1 is due to O-H stretching. The vibrations due to
the halogen atom attached to aromatic ring are significance to discuss here, Mooney assigned vibrations of
C-X group (X = Cl, Br and I) in the frequency range
1129-480 cm−1 [57]. In present study C-Cl stretching
MOLECULAR PHYSICS
7
Figure 2. 1 H NMR spectrum of compound DPIP.
vibration was observed at 509 cm−1 in FT-IR and was
in good agreement with the theoretically calculated value
397 cm−1 . It is seen from Table S2 that the calculated IR
spectral data were slightly higher than the experimental
values. The suggested reason is that the theoretical calculation assumes harmonic nature of vibrations, whereas
the experimental frequencies may involve anharmonicity. (Table 1)
3.2.3. Natural bond orbital (NBO) analysis
In the Natural Bond Orbital (NBO) analyses of the compound (DPIP), numerous donor-acceptor interactions
are observed. Among the strongly occupied NBOs, the
pivotal delocalisation sites are identified within the π
system and the lone pairs (n) of oxygen and nitrogen,
located on the imidazole and chlorosubstituted phenyl
moiety. The σ system also exhibits some contribution
to the delocalisation, with the donor-acceptor interactions being largely consistent across these compounds.
The most significant interaction energies associated with
charge transfer primarily involve stabilisation energies of
177.07 and 118.66 kJ/mol, along with electron densities of
1.57 and 0.39e, respectively. These bonds’ orbitals result
in intramolecular charge transfer (ICT), contributing to
the system’s stabilisation. The LPO46/C41-C42/C42-C44
is determined as 106.61 and 104.31 kJ/mol, with electron
densities of 1.71 and 0.27e, respectively. Notably, π -π∗
electron transitions are predominantly operated between
the π C31-C34 to π ∗C32-C36 anti-bonding orbital, stabilised by 90.25 kJ/mol and an electron density of 1.66e.
These interactions manifest as an increase in electron
density (ED) in the C-C antibonding orbital, consequently weakening their respective bonds [56]. In NBO
analysis, large E(2) values signify intensive interactions
between electron donors and electron acceptors. The
potential intensive interactions are detailed in Table 2.
3.2.4. Molecular electrostatic potential
The Molecular Electrostatic Potential (MEP) serves as a
visual tool to comprehend the molecule’s relative polarity. MEP is a valuable instrument for predicting and
analysing molecular interactions, such as drug-receptor
and enzyme-substrate interactions. It proves highly beneficial for qualitatively elucidating electrophilic and nucleophilic reactions in the study of the biological discovery
process, as well as for understanding hydrogen bonding interactions [57]. An electron density iso-surface,
mapped with an electrostatic potential surface, provides
8
S. SONADEVI ET AL.
Figure 3. 13 C NMR spectrum of compound DPIP.
insights into the size, shape, charge density, and sites
of chemical reactivity within the molecule. Different
colours on the surface represent various values of the
electrostatic potential, with red surfaces indicating areas
of high electron density, while blue surfaces correspond
to regions of the lowest electron density. The MEP map
with an electron contour graph for DPIP is depicted in
Figure 5, featuring a colour range from −5.068e-2 (deepest red) to 5.068e-2 (deepest blue). The MEP highlights
the negative potential site over the nitrogen atom, while
positive potential sites surround the hydrogen atoms.
The regions over the rings appear neutral, represented
by green colour. These sites provide information about
regions where the molecule can engage in intermolecular
interactions [58].
stability and electrical transport properties. In the molecular orbital diagram, the colours red and green denote the
positive and negative phases, respectively. The HOMO
exhibits charge density concentrated over the chlorosubstituted phenyl ring, excluding hydrogen and three
phenyl rings [62,63]. On the other hand, the LUMO component is situated on the C-2 substituted phenyl ring,
excluding C1, N3, and the chlorosubstituted phenyl rings.
Charge transfer occurs from the C-2 substituted phenyl
ring (LUMO) to HOMO (chlorosubstituted phenyl ring).
The energy difference between the HOMO and LUMO
is measured at 6.14 eV. A smaller band gap energy indicates greater stability for the molecule. The DPIP frontier molecular orbitals (HOMO-LUMO) are depicted in
Figure 6.
3.2.5. Frontier molecular orbital study
The absorption of electrons, corresponding to the transition from the ground state to the first excited state,
is primarily explained by one-electron excitation from
the Highest Occupied Molecular Orbital (HOMO) to the
Lowest Unoccupied Molecular Orbital (LUMO), as per
wave function analysis [59–61]. The energy gap between
the Lowest Unoccupied Molecular Orbital (LUMO) and
the Highest Occupied Molecular Orbital (HOMO) plays
a pivotal role in determining a molecule’s chemical
3.2.6. Mulliken atomic charge analysis
Mulliken population analysis provides a summary of the
charge distribution values across the molecular framework, showcasing the charges on each atom in the
molecule. Table 3 highlights that molecules O49 (−0.35),
N3 (−0.38) and N4 (−0.33) possess the most significant
negative charges, functioning as electron acceptors and
contributing to electrophilic reactivity. H20 atoms, with
a higher number of electronegative nitrogen and oxygen
atoms, exhibit greater atomic charges (0.34), rendering
MOLECULAR PHYSICS
9
Figure 4. Optimised structure of DPIP.
them the most positively charged carbons. The electropositive regions, acting as electron donors, are associated with nucleophilic reactivity. As there are fewer
positive and negative charges in the remaining carbon
and hydrogen atoms, a molecule containing both acceptor and donor atoms is expected to be more reactive
during substitution operations [64]. Table 3 presents the
results of the Mulliken charge calculation for the compound using the B3LYP/6311G (d, p) method. (Tables 4
and 5)
3.2.7. Non-linear optics (NLO)
The first hyperpolarizabilities (β, α, and µ) of the compound DPIP are determined using the B3LYP/6-311G
(d, p) level of theory through the finite-field approach.
This investigation highlights that the π -π∗ interaction
can induce a more substantial intra-molecular interaction, consequently enhancing the molecule’s polarizability. The reduced band gap energy is identified as a factor
contributing to the increased Nonlinear Optical (NLO)
properties of the molecule [65].
The physical properties of these conjugated molecules
are influenced by the extensive electronic charge delocalisation along the charge transfer axis and the low
band gaps. The calculated hyperpolarizability of DPIP
(β 0 = 1.089 × 10−30 esu) is three times greater than that
of urea (β 0 = 0.37 × 10−30 esu). This comparison leads
to the conclusion that the title molecule exhibits superior nonlinear optical properties. The molecular electric dipole moments (µ), polarizability (α 0 ), and hyperpolarizability (β 0 ) values for DPIP are presented in
Table 6.
10
S. SONADEVI ET AL.
Table 1. Selected bond length (A)˚, bond angle (°) and torsional
angles (°) of the DPIP compound by DFT.
Bond length
Cal
Dihedral Angle
Cal
C4-O14
C10-O14
C3-O15
C11-O15
C28-O26
C25-O26
C23-O24
C23-N21
H22-N21
N21-N20
C18-N20
Bond Angle
H31-C28-O26
C29-C28-O26
C27-C25-O26
C23-C25-O26
C25-C23-O24
C25-C23-N21
N21-C23-O24
C23-N21-H22
C23-N21-N20
N21-N20-C18
N20-C18-H19
N20-C18-C1
C5-C4-O14
C4-O14-C10
C3-C4-O14
O14-C10-H12
O14-C10-H16
O14-C10-C10
C4-C3-O15
C3-C15-C11
C2-C3-O15
O15-C11-H13
O15-C11-C10
O15-C11-H17
1.43
1.42
1.43
1.42
1.45
1.45
1.25
1.47
1.00
1.4
1.29
Cal
124.25
111.49
111.49
124.25
120.00
120.00
120.00
109.47
109.47
120.00
120.00
120.00
118.82
112.55
121.45
108.83
110.63
108.54
121.45
112.55
118.82
108.83
108.54
110.63
H31-C28-O26-C25
C28-O26-C25-C23
C28-O26-C25-C27
O26-C25-C23-O24
O26-C25-C27-C29
O26-C25-C27-H30
O26-C25-C23-N21
C25-C23-N21-N20
C25-C23-N21-H22
C27-C25-C23-O24
O24-C23-N21-H22
O24-C23-N21-N20
C23-N21-N20-C18
H22-N21-N20-C18
N21-N20-C18-H19
N21-N20-C18-C1
N20-C18-C1-C6
20N-18C-1C-2C
H8-C3-C4-O14
6C-5C-4C-14O
C2-C3-C4-O14
C1-C2-C3-O15
7H-2C-3C-15O
C3-C4-O14-C10
C4-O14-C10-H12
C4-O14-C10-H16
C2-C3-O15-C11
C4-C3-O15-C11
C3-O15-C11-H13
C3-O15-C11-H17
H12-C10-C11-O15
O15-C11-C10-O14
O14-C4-C3-O15
H8-C5-C4-O14
H13-C11-C10-O14
H17-C11-C10-O14
167.81
−167.82
12.05
−0.07
−7.83
172.87
179.92
150.00
30.00
−179.92
−150.00
−30.00
150.00
−90.00
0.00
−179.99
0.08
179.92
−3.54
176.14
−174.62
176.14
−3.54
−22.03
170.31
−69.51
158.73
−22.03
170.31
−69.51
174.14
−66.80
6.15
−3.54
174.14
53.97
Table 2. Significant delocalisation energies of second order perturbation theory analysis of Fock matrix in NBO for the title compound DPIP.
Type
Donor (i)
Acceptor(j)
E(2)
E(j)-E(i)
F(i,j)
π-σ ∗
π-σ ∗
σ -π∗
n-π∗
n-π∗
σ -σ ∗
n-π∗
σ -σ ∗
π-π ∗
π-π ∗
π-π ∗
n-σ ∗
σ -σ ∗
π-π ∗
C27-C30
C14-C16
C27-H31
LP(1)-N3
LP(2)-O49
C16-H20
LP(1)-N3
C27-H31
C6-C8
C25-C26
C28-C32
LP(1)-O49
C1-C2
C36-C38
C16-H20
C27-H31
C14-C16
N4-C5
C6-C8
C16-H20
C1-C2
C27-H31
N4-C5
C1-C2
C27-C30
C8-C11
C1-N3
C25-C26
63.1
52.92
38.2
20.56
19.58
16.85
15.56
14.43
13.48
12.09
10.26
5.95
0.99
0.57
0.76
0.76
0.4
0.35
0.36
0.87
0.38
0.84
0.31
0.31
0.34
0.96
1.08
0.33
0.21
0.18
0.12
0.08
0.08
0.11
0.07
0.10
0.06
0.06
0.05
0.07
0.03
0.01
3.2.8. Temperature and pressure dependence of
thermodynamic properties and Partial Density of
States (PDOS)
Shermo calculations employ computational techniques
to determine a material’s thermodynamic properties.
These calculations utilise the principles of quantum
Figure 5. Potential energy surface scan with varying dihedral
angle (180 degree) for DPIP.
Table 3. Mulliken Atomic Charges of DPIP.
Atom
Charge
Atom
Charge
C1
C2
N3
N4
C5
C6
C7
C8
C9
H10
C11
C12
H13
C14
C15
C16
C17
H18
C19
H20
C21
H22
H23
H24
C25
0.15
0.07
−0.38
−0.33
0.34
−0.13
0.08
0.28
−0.24
0.19
−0.24
0.12
0.14
−0.04
−0.04
−0.33
−0.09
0.11
−0.10
0.29
−0.10
0.10
0.09
0.10
−0.10
C26
C27
C28
H29
C30
H31
C32
H33
H34
H35
C36
C37
C38
C39
H40
C41
H42
C43
H44
H45
H46
C47
C48
O49
H50
−0.05
−0.24
−0.10
0.15
−0.07
0.26
−0.09
0.10
0.10
0.10
−0.07
−0.13
−0.05
−0.07
0.13
−0.09
0.15
−0.09
0.12
0.11
0.11
0.07
0.04
−0.35
0.26
mechanics and statistical mechanics to model the interactions between particles in a system and facilitate the
determination of crucial parameters such as enthalpy,
specific heat, and entropy. The precision and dependability of Shermo computations depend on the correctness of input parameters and the selection of a suitable
theoretical model.
Shermo utilises information from Density Functional
Theory (DFT) calculations to compute the temperature or pressure dependency of thermodynamic parameters for DPIP: Electron energy (E): −2145.19286800 a.u.
Total mass: 456.079690 amu. Principal moments of inertia: 11132.926258, 20320.336584, 27693.703317. Rotational temperature (K): 0.007780, 0.004262, 0.003128.
MOLECULAR PHYSICS
11
Figure 6. Molecular electrostatic potential of DPIP.
Table 4. The molecular electric dipole moment μ (Debye), polarizability (α 0 ) and hyperpolarizability (β 0 ) values of compound
DPIP.
Parameters
B3LYP/6-31G (d,p)
Dipole moment Debye
µx
µy
µz
µ
Polarizability x10−24
−0.3958
−4.9609
−0.1995
4.9807
α xx
α yy
α zz
α xy
α xz
α yz
αo
Hyperpolarizability x 10−30 esu
426.496
−5.390
379.271
13.713
5.069
232.160
0.883X10−24
β xxx
β yyy
β zzz
β xyy
β xxy
β xxz
β xzz
β yzz
β yyz
β xyz
βo
−17.5158
−54.3598
−10.1401
−35.6330
−15.8694
16.7817
−17.1711
−0.3081
−12.4108
−27.7248
1.089X10−30
Zero-point energy (ZPE): 991.69 kJ/mol. A comprehensive investigation has revealed the complex molecular
properties of DPIP. Additionally, a systematic derivation of DPIP’s thermodynamic data has been conducted, integrating input from various sources. Thermodynamic properties of compound are given in Table 6.
Table 5. Thermodynamic Property values of compound DPIP.
Property
V q(V = 0)
V q(bot)
V U(T)-U (0)
VU
VS
V CV
ZPE
Total q(V = 0)
Total q(bot)
Total q(V = 0)/NA
Total q(bot)/NA
Total CV
Total CP
Total S
-TS
ZPE
Thermal correction to U
Thermal correction to H
Thermal correction to G
Electronic energy
Total number of EE and ZPE,
namely U/H/G at 0 K
Total number of EE and TC to U
Total number of EE and TC to H
Total number of EE and TC to G
Value
Units
2.106600 × 1011
3.869069 × 10−163
61.324
1053.012
422.470
402.699
991.69
1.38 × 1051
2.53 × 10−123
2.29 × 1027
4.20 × 10−147
427.642
435.957
762.72
−54.351
991.688
1060.449
1062.928
835.523
−2145.192868
−2144.815154
–
–
kJ/mol
kJ/mol
J/mol/K
J/mol/K
kJ/mol
–
–
–
–
J/mol/K
J/mol/K
J/mol/K
kcal/mol
kJ/mol
kJ/mol
kJ/mol
kJ/mol
a.u.
a.u.
−2144.788964
−2144.78802
−2144.874634
a.u.
a.u.
a.u.
∗ZPE – Zero-point energy, ∗EE – Electron Energy, TC – Thermal Correction,
Moreover, the relationship between relative distribution
functions and thermodynamic parameters is comprehensively visualised using the Partial Density of States
(PDOS) generated from Shermo calculations [66]. The
molecular system is linked to the energy-dependent Partial Density of States (PDOS) depicted in the graph.
‘Energy [a.u.]’ is annotated on the horizontal axis, where
‘a.u.’ stands for atomic units, and ‘DOS’ is indicated on
12
S. SONADEVI ET AL.
Table 6. Molecule properties of compound DPIP.
Descriptor
Value
Molecular Weight
LogP
Rotatable Bonds
Acceptors
Donors
Surface Area
457.36
7.8857
4
3
1
195.699
the vertical axis. Two peaks in the PDOS correspond to
different fragments of DPIP (Catalytic Iron Manganese
Phosphonate): the first fragment is represented by the
lower energy peak, and the second fragment is represented by the higher energy peak. Understanding various
material qualities, such as electrical conductivity, optical features, and magnetic properties, is facilitated by
the PDOS. Specifically, DPIP material will exhibit strong
conductivity if it has a significant PDOS at the Fermi
energy, which is the energy level where there is a 50%
chance of finding an electron. Conversely, DPIP material
characterised by a diminished PDOS at the Fermi energy
will display insulating properties.
Density Functional Theory (DFT)-based Shermo calculations have clarified how thermodynamic parameters
for catalytic iron manganese phosphate (DPIP) depend
on temperature and pressure. Computational techniques
provide comprehensive molecular properties, including
vibrational contributions and thermodynamic information. Understanding the interaction between relative distribution functions and thermodynamic parameters in
DPIP is improved by the derived Partial Density of States
(PDOS). The molecular system is depicted by the energydependent PDOS graph, which has two peaks representing different DPIP fragments. The first fragment
is associated with the lower energy peak, and the second fragment is associated with the higher energy peak.
Understanding material qualities, such as electrical conductivity, magnetism, and optics, depends heavily on this
knowledge. A low PDOS at the Fermi energy indicates
insulating qualities in DPIP, while a high PDOS at the
energy represents strong conductivity. Shermo computations and PDOS provide a full understanding of the
material and thermodynamic properties of DPIP. Partial
Density States graph is given in Figure 7.
3.3. Molecular docking studies
We opted to perform a molecular docking analysis of the
DPIP compound, considering it as a potential remedy
against COVID-19. The molecular docking procedure
involved studying and assessing the interactions between
the DPIP ligand and the receptors COVID-19/6WCF,
COVID-19/6Y84, and COVID-19/6LU7.
Figure 7. Frontier Molecular Orbital diagram of compound DPIP.
3.3.1. Interactions of 6WCF receptor with DPIP ligand
ADP ribose phosphatase of NSP3 from SARS-CoV-2,
crystallized as 6WCF in association with MES, is crucial for the digestion of polyproteins translated from viral
RNA, playing a pivotal role in the survival and expansion of the virus [67]. In the docking analysis, a pi-anion
bond is established between ASP157 and the benzyl substituent, with a bond length of 3.68 Å. Additionally, one
of the other benzyl substituents forms a pi-sigma bond
with LEU160, exhibiting a bond length of 1.78 Å. The
remaining interactions are identified as pi-alkyl interactions with PHE156 and PRO16, with bond lengths of 4.59
and 4.20 Å, respectively, at various substituent sites of the
MOLECULAR PHYSICS
13
Table 7. Pharmacokinetic properties of compound DPIP.
Property
Model Name
Absorption
Water solubility
Caco2 permeability
Intestinal absorption (human)
Skin Permeability
P-glycoprotein substrate
P-glycoprotein I inhibitor
P-glycoprotein II inhibitor
VDss (human)
Fraction unbound (human)
BBB permeability
CNS permeability
CYP2D6 substrate
CYP3A4 substrate
CYP1A2 inhibitior
CYP2C19 inhibitior
CYP2C9 inhibitior
CYP2D6 inhibitior
CYP3A4 inhibitior
Total Clearance
Renal OCT2 substrate
AMES toxicity
Max. tolerated dose (human)
hERG I inhibitor
hERG II inhibitor
Oral Rat Acute Toxicity (LD50)
Oral Rat Chronic Toxicity (LOAEL)
Hepatotoxicity
Skin Sensitisation
T.Pyriformis toxicity
Minnow toxicity
Distribution
Metabolism
Excretion
Toxicity
ligand under investigation. VAL155 engages in an alkyl
bond interaction with the benzyl substituent, featuring a
bond length of 3.15 Å. The amino acid LEU126 creates
an unfavourable bump around the protein. In contrast,
conventional hydroxychloroquine shows mixed alkyl and
pi-alkyl interactions with the receptor. PHE132 (3.92 Å)
interacts with the chlorine atom through alkyl and pialkyl interactions. ALA38 (3.91 Å) forms a bond with the
phenyl group, and the alkyl and pi-alkyl groups on the
residues LYS102 (4.12 Å), ILE131 (4.81 Å), and PHE132
(4.63 Å) engage with the methyl group at varying distances. Hydroxychloroquine, the standard medication,
exhibits a binding energy of −7.20 kcal/mol, while compound DPIP demonstrates a higher binding value of
−11.81 kcal/mol. Figure 8 illustrates the docked 2D and
3D representations of the DPIP chemical and the standard medication (hydroxychloroquine) with the 6WCF
receptor.
3.3.2. Interactions of 6Y84 receptor with DPIP ligand
The primary unliganded active site of the COVID-19
protease corresponds to the 6Y84 receptor. This protease
is essential for the digestion of polyproteins translated
from viral RNA, playing a critical role in the survival
and spread of the virus [68]. In the docking analysis,
various interactions are observed between the DPIP ligand and the 6Y84 receptor. PHE A:294 forms conventional hydrogen bonds, Amide-Pi stacked interactions,
Predicted Value
−2.893
−0.392
84.089
−2.735
Yes
Yes
Yes
−0.22
0.356
0.233
−1.043
No
Yes
Yes
Yes
Yes
Yes
Yes
0.128
Yes
Yes
0.432
Yes
Yes
2.485
−1.022
No
No
0.285
−0.411
Unit
Numeric (log mol/L)
Numeric (log Papp in 10-6 cm/s)
Numeric (% Absorbed)
Numeric (log Kp)
Categorical (Yes/No)
Categorical (Yes/No)
Categorical (Yes/No)
Numeric (log L/kg)
Numeric (Fu)
Numeric (log BB)
Numeric (log PS)
Categorical (Yes/No)
Categorical (Yes/No)
Categorical (Yes/No)
Categorical (Yes/No)
Categorical (Yes/No)
Categorical (Yes/No)
Categorical (Yes/No)
Numeric (log ml/min/kg)
Categorical (Yes/No)
Categorical (Yes/No)
Numeric (log mg/kg/day)
Categorical (Yes/No)
Categorical (Yes/No)
Numeric (mol/kg)
Numeric (log mg/kg_bw/day)
Categorical (Yes/No)
Categorical (Yes/No)
Numeric (log ug/L)
Numeric (log mM)
and Pi-alkyl bonds with the benzyl substituents, featuring bond lengths of 4.28, 3.43, and 4.73 Å, respectively
as depicted in Figure 9. Additionally, GLN110, ARG298,
and ASP295 contribute van der Waals forces of interaction toward the compound. PRO293 engages in Pi-Pi
stacked interaction with the parent imidazole ring and
pi-alkyl interaction with the benzyl derivative, with bond
lengths of 5.82 and 4.07 Å, respectively. THR292 forms
a carbon-hydrogen bond with the oxygen atom, featuring a bond length of 3.62 Å. The benzyl substituent
of the compound establishes pi-alkyl interactions with
VAL297 and ILE249, exhibiting bond lengths of 4.43
and 5.08 Å, respectively. LEU253 and PRO252 also form
alkyl bond interactions with the benzyl substituent, with
bond lengths of 6.99 and 6.45 Å, respectively. In contrast,
conventional hydroxychloroquine demonstrates mixed
alkyl and pi-alkyl interactions with the receptor. Residues
PHE8 (5.17 Å) and MET6 (3.62, 4.27 Å) interact with the
quinoline moiety through alkyl and pi-alkyl interactions
at different distances. The methyl group binds to VAL303
(4.16 Å), ARG298 (3.06 Å), and other molecules. The
ethyl group in hydroxychloroquine is bound to residues
MET6 (4.35 Å) and PRO9 (4.34 Å). The binding energy
of the DPIP molecule is −11.26 kcal/mol, compared to
−7.28 kcal/mol for the reference drug hydroxychloroquine. Figure 9 illustrates the docked 2D and 3D representations of the DPIP chemical and the common drug
hydroxychloroquine with the 6Y84 receptor.
14
S. SONADEVI ET AL.
Figure 8. Partial Density States graph of compound DPIP.
3.3.3. Interactions of 6LU7 receptor with DPIP ligand
The DPIP molecule forms strong attachments to the
6LU7 receptor through interactions involving alkyl and
pi-alkyl groups, carbon-hydrogen bonds, pi-loan pairs,
pi-pi stacked interactions, and amide pi-stacked interactions [69]. Notably, amino acid PRO93 engages in
alkyl interactions with the benzyl substituents, displaying bond lengths of 3.17 and 4.67 Å. VAL297 also forms
an alkyl interaction with a bond length of 5.05 Å. Multiple pi-alkyl interactions with varying bond lengths are
observed between PRO252 and different positions of the
ligand. A pi-pi stacked interaction is noted with a bond
length of 4.04 Å. Additionally, pi-sigma and pi-lone pair
interactions occur between the ligand and amino acids
ASP248 and ILE249 at different positions, featuring bond
lengths of 3.30 and 2.85 Å, respectively. In contrast, the
standard hydroxychloroquine is bound by alkyl and pialkyl interactions, pi-sigma, and pi-loan pairs. Residues
PHE294 (2.79, 5.44 Å) interact with the chlorine atom,
quinoline, and ethyl moiety through pi-sigma and pilone pair interactions at various distances. PRO293 (4.52
Å), ILE249 (3.49 Å), and VAL297 (3.87 Å) form alkyl
and pi-alkyl bonds at varying distances to interact with
the methyl and ethyl groups. The binding energy of the
reference drug hydroxychloroquine is −7.09 kcal/mol,
whereas the binding energy of the test molecule is −11.82
kcal/mol. Figure 10 illustrates the docked 2D and 3D representations of the DPIP chemical and the widely used
drug hydroxychloroquine with the 6LU7 receptor.
Molecular docking investigations are conducted to
assess the performance of compound DPIP when compared to derivatives of compound 1-(2,3-dihydrobenzo
[b][1,4]dioxin-6-yl)−2-(furan-2-yl)−4,5-diphenyl-1Himidazole (DDFDI) and azo imidazole (L5) against the
main protease of COVID-19 (PDB: 6WCF/6Y84/6LU7)
[70,71]. Binding Affinity: The binding affinity denotes
the intensity of reversible interaction between two or
more molecules. It is affected by several factors, such as
residual interactions, hydrogen bonding, and the matching of shapes between the ligand and receptor. A low
binding energy indicates strong interactions between
the protein and ligand. For instance, compound DPIP
exhibits binding energy values of −11.81 and −11.26
kcal/mol, while the reference compound DDFDI shows
-9.75 and -10.62 kcal/mol against receptors 6WCF and
6Y84. Moreover, the binding energy of DPIP is -11.82
kcal/mol, whereas the reference compound L5 has a binding energy of -8.1 kcal/mol against receptor 6LU7. The
enormous number of interactions such as alkyl, pi-alkyl,
pi-anion, pi-sigma, pi-loan pair, pi-pi stacked, conventional hydrogen bond and carbon hydrogen bond interactions are favourable in compound DPIP than DDFDI
and L5 reference compounds. The binding affinity of
compound DPIP is very high than reference DDFDI and
L5 compounds due to the less binding energy values.
Inhibitory Constant: The Inhibitory constant (Ki) is a
crucial term in the drug discovery process, representing
the concentration of a drug needed to occupy 50% of
MOLECULAR PHYSICS
15
Figure 9. 2D and 3D View of interactions of DPIP and standard drug with Covid-19/6WCF receptor by docking.
receptors. A lower Ki indicates stronger binding affinity
for a drug at a specific receptor. For instance, the compound DPIP has lower Ki values (0.1696, 0.1842, and
0.1694) compared to DDFDI (0.2312, 0.2028) and L5
(0.2962) against receptors 6WCF, 6Y84, and 6LU7. Even
the standard hydroxychloroquine has lower Ki values
(0.3391, 0.3350, and 0.3447). Ultimately, DPIP is considered a more effective antiviral agent than DDFDI, L5, and
hydroxychloroquine against these receptors.
3.4. Molecular dynamic simulation
To assess the binding stability of both the reference
drug and the synthesised molecules with the active site
of COVID-19/6WCF-6Y84-6LU7 receptors, crucial for
SARS-CoV-2 infection, MD simulations were conducted.
The RMSD (Root Means Square Deviation) and RMSF
(Root Means Square Fluctuation) plots were utilised to
illustrate the conformational stability and alterations in
amino acid residues of the proteins interacting with the
drug molecules throughout the MD simulations. Additionally, intermolecular interaction analyses were performed and compared with docking results to elucidate
the structural binding nature between drug molecules
and proteins.
3.4.1. Intermolecular interactions of compound DPIP
with 6WCF/6Y84/6LU7 receptors
Compound DPIP engages in pi-alkyl interactions with
residues LEU160 (4.63 Å) and PRO136 (4.31 Å) in the
6WCF receptor, forming interactions at varying distances
between its two phenyl rings. In contrast, the regular hydroxychloroquine medication does not exhibit any
interactions with amino acids and only forms hydrogen bond interactions with water. At the 6Y84 receptor, there are no interactions observed between the
DPIP molecule and the common medication hydroxychloroquine. For the 6LU7 receptor, DPIP engages in
16
S. SONADEVI ET AL.
Figure 10. 2D and 3D View of interactions of DPIP and standard drug with Covid-19/ 6Y84receptor by docking.
pi-pi stacked, pi-alkyl, and amide pi-stacked interactions. The imidazole and phenyl rings of DPIP attach to
residues PHE294 (3.91 Å) and PRO293 (4.57 Å) through
amide pi-stacked and pi-pi stacked linkages, respectively.
VAL297 (5.46 Å) residues form bonds with a phenyl ring
in DPIP. On the other hand, conventional pharmaceuticals exhibit a normal hydrogen bond between residues
ILE249 (1.99 Å) and the nitrogen atom. Alkyl and pialkyl bonds are formed between residues PRO293 (5.21
Å), LEU253 (4.66 Å), VAL297 (4.81, 4.27 Å), and PRO252
(4.94 Å) with the methyl and ethyl moieties present in the
standard medication. According to the results of molecular dynamics modelling, the developed DPIP molecule
demonstrates higher intermolecular interactions and stability with 6WCF/6LU7 receptors compared to conventional medicines. Refer to Figures 11–13 for 2D and
3D images illustrating the intermolecular interactions
between DPIP and the standard medication with the
6WCF/6Y84/6LU7 receptors.
3.4.2. Root mean square deviation (RMSD)
The RMSD plots for the complexes of DPIP and Hydroxychloroquine with proteins 6WCF/6Y84/6LU7 are presented in Figure 14. The DPIP complex exhibits a substantial deviation (approximately 2.5 Å) during the simulation time between 40-80 ns, but beyond 80 ns, the
complex stabilises. On the other hand, the complex with
hydroxychloroquine demonstrates an acceptable average RMSD of about 1.5 Å, and its structure remains
relatively stable between 10-100 ns. A notable fluctuation is observed around C-50 in the RMSD plot of
the hydroxychloroquine complex, while both complexes
exhibit similar RMSF plots. The low RMSF values in
the 6LU7-DPIP complex around C-292, C-294, C-295,
MOLECULAR PHYSICS
17
Figure 11. 2D and 3D View of interactions of DPIP and standard drug with Covid-19/ 6LU7 receptor by docking.
and C-298, corresponding to the protein backbone in
the binding pocket region, indicate effective interaction
of the ligand with the target protein at the binding site.
Similarly, the RMSF plot of 6LU7-hydroxychloroquine
exhibits low fluctuations around C-293, C-294, C-297,
and C-298, reflecting the stability of protein-ligand interaction at the binding site. Both complexes maintain stable
RMSD values from 20 ns to 100 ns, with the 6WCFDPIP complex showing an acceptable average RMSD
of around 1.3 Å, while the 6WCF-Hydroxychloroquine
complex displays a lower average RMSD of around
0.9 Å.
3.4.3. Root means square fluctuation (RMSF)
In the 6WCF-DPIP complex, notable fluctuations are
observed in the backbone regions of C-100 and C-130. In
contrast, the 6WCF-Hydroxychloroquine complex displays a lower average RMSF. Regions surrounding C126, C-155, C-156, and C-157 within the pocket site
show minimal fluctuations, suggesting interactions with
the DPIP ligand. The RMSD plot for the complexes of
DPIP and Hydroxychloroquine with the protein 6Y84 is
depicted in Figure 14. Both complexes exhibit a similar
RMSD plot, reaching stabilisation after 60 ns of simulation and maintaining a constant level until 100 ns, with
18
S. SONADEVI ET AL.
Figure 12. 2D and 3D View of interactions of DPIP and standard drug with Covid-19/6WCF receptor by MD simulation.
an average RMSD of 2.1 Å. While the plots may differ,
they both indicate a stable carbon backbone in the ligand binding pockets, signifying consistent protein-ligand
binding interactions at the docking site. (Figures 15
and 16)
3.5. Theoretical ADMET prediction
The computed molecular weight for the investigated
compound is estimated to be 457.36 g/mol, featuring 4
rotatable bonds, 3 acceptor atoms, and 1 donor atom.
The surface area of the compound is evaluated to be
195.699 A⊃2. The Log P value is determined to be 7.8857,
representing a measure of the compound’s ability to transition from an aqueous phase to a lipid phase and, consequently, its potential to traverse the cell membrane. Log
P is a crucial metric in pharmacokinetics, indicating a
compound’s drug-like characteristics for oral administration. The Lipinski analysis employs physiochemical
properties to assess the drug-likeness of an oral therapeutic molecule, with the rule of five highlighting the
interrelation between pharmacokinetic indices and physiochemical properties. Notably, the compound violates
two aspects of the Lipinski rule, exceeding the stipulated
surface area and Log P value. The term ADMET encompasses Adsorption, Distribution, Metabolism, Excretion,
and Toxicity, constituting a comprehensive study of the
compound’s pharmacokinetics.
Absorption: The water solubility of the compound at
25°C is predicted, with drugs that are water-soluble generally being better absorbed than lipid-soluble ones [72].
The anticipated water solubility for the studied chemical
MOLECULAR PHYSICS
19
Figure 13. 2D and 3D View of interactions of DPIP and standard drug with Covid-19/6Y84 receptor by MD simulations.
is −2.893 mol/L, and its interpretation on the provided scale indicates that the compound is water-soluble.
The scale ranges from Insoluble < −10 < Poorly soluble < −6 < Moderately soluble < −4 < Soluble < −2
< Very soluble < 0 < Highly soluble. In terms of absorption, a molecule with less than 30% absorbance is considered poorly absorbed [73]. The investigated compound
demonstrates an intestinal absorption percentage of 84%,
suggesting rapid absorption by the human intestine. For
skin permeability, a value less than −2.5 is considered
to indicate low skin permeability [74]. The assessed
compound exhibits low skin permeability, with a value
obtained as −2.735 cm/h. The P-Glycoprotein transporter, functioning as an ATP binding cassette (ABC),
acts as a biological barrier by expelling toxins and xenobiotics from cells. It is anticipated that our chemical will
act as a substrate for P-glycoprotein. Distribution: The
volume of distribution (VDss) represents the theoretical volume needed for a drug’s complete dose to be
uniformly dispersed to the same concentration as blood
plasma. A higher VDss score suggests more dispersion
in tissue rather than plasma. VD is considered low if
below 0.71 l/kg and high if exceeding 2.81 l/kg [75].
The predicted VDss value for the investigated compound
is −0.22 l/kg, indicating poor distribution between tissues and plasma. Protein Binding: The extent to which a
compound binds to blood proteins can influence its effectiveness, as increased protein binding can hinder effective
dispersion or cell membrane penetration [76]. The anticipated ratio for the studied compound is 0.356. BloodBrain Barrier (BBB) Permeability: The ability of a drug
molecule to cross the blood-brain barrier can minimise
side effects and toxicities while enhancing pharmacological efficacy in the brain. A Log BBB value greater than 0.3
20
S. SONADEVI ET AL.
Figure 14. 2D and 3D View of interactions of DPIP and standard drug with Covid-19/6LU7 receptor by MD simulations.
suggests easy BBB penetration, while a value less than −1
indicates poor distribution in the blood. The investigated
compound has a projected BBB value of 0.233, indicating
easy passage through the blood-brain barrier. CNS Permeability: Compounds with Log Ps values greater than
−2 suggest permeability into the central nervous system
(CNS), whereas those with values less than −3 indicate
inability to enter the CNS [77,78]. The obtained value for
this attribute is −1.043, indicating high CNS permeability. Metabolism: The body’s essential cytochrome P450
enzyme, primarily found in the liver, plays a crucial role
in oxidising xenobiotics to facilitate excretion. Therefore,
assessing a compound’s potential to inhibit or act as a
substrate for cytochrome P450 is crucial. Models for various isoforms, including CYP2D6, CYP3A4, CYP1A2,
CYP2C19, CYP2C9, CYP2D6, and CYP3A4, are developed. These predictions help determine whether a given
molecule is likely to serve as a substrate or an inhibitor for
specific cytochrome P450 isoforms. Table 2 provides data
indicating whether the substance will act as a substrate
or not, along with details on the inhibition of certain
isoforms. Metabolism: The body’s essential cytochrome
P450 enzyme, primarily found in the liver, plays a crucial role in oxidising xenobiotics to facilitate excretion.
Therefore, assessing a compound’s potential to inhibit or
act as a substrate for cytochrome P450 is crucial. Models for various isoforms, including CYP2D6, CYP3A4,
CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4,
are developed. These predictions help determine whether
a given molecule is likely to serve as a substrate or an
inhibitor for specific cytochrome P450 isoforms. Table 2
provides data indicating whether the substance will act
as a substrate or not, along with details on the inhibition of certain isoforms. Toxicity: A common method
for assessing acute toxicity and comparing the relative
toxicity of multiple compounds is to use lethal dosage
values. The lethal dose represents the amount of a substance administered all at once that leads to the death
MOLECULAR PHYSICS
Figure 15. RMSD plots for Hydroxychloroquine and DPIP with 6WCF, 6Y84 and 6LU7 complexes obtained from the MD simulation.
21
22
S. SONADEVI ET AL.
Figure 16. RMSF plots for Hydroxychloroquine and DPIP with 6WCF, 6Y84 and 6LU7 complexes during the MD simulation.
MOLECULAR PHYSICS
of 50% of a test animal group. The calculated value for
this chemical is 2.485 mol/kg. Toxicity assessments often
employ T. Pyriformis, a protozoa bacterium, as a toxic
endpoint. It is considered harmful when the value for
a specific component exceeds −0.5 ug/L. The synthesised compound is predicted to be toxic to T. Pyriformis
bacteria, with a dosage value obtained as 0.285ug/L. Minnow toxicity is determined by lethal concentration values,
indicating the amount of a certain molecule required
to kill 50% of flathead minnows. If the value is greater
than 0.05 mM for a substance, it is deemed hazardous.
The estimated Minnow Toxicity value for the substance
under investigation is 0.411 mM. The Maximum Tolerated Dose (MTRD, human) serves as an estimation of the
hazardous dosage threshold for substances in humans,
provided by the maximum recommended tolerated dose.
The MTRD value for the examined substance is 0.432
mg/kg/day. Chronic exposure to low to moderate doses
of chemicals poses a significant problem in various therapeutic approaches. Chronic studies aim to identify the
lowest observed adverse effect level (LOAEL) at which
an unfavourable effect is apparent and the highest dose
where such effects are not observed. The LOAEL values need to be assessed in consideration of the required
treatment duration and bioactive concentration [79,80].
The chemical is anticipated to have an oral rat chronic
toxicity value of −1.022 mg/kg(bw)/day. Drug-induced
liver damage is a substantial contributor to drug attrition and a serious safety concern in medication development. A substance is considered hepatotoxic if it causes at
least one pathological or physiological liver event closely
linked to the disruption of the liver’s normal function
[81,82]. It is expected that our researched substance won’t
be hepatotoxic. Skin sensitisation refers to the negative
side effects of products used topically. Since some medications may cause adverse reactions when applied to the
skin, careful evaluation is required [83,84]. It is projected
that the synthetic substance, upon application to the skin,
will not cause any allergic reactions.
4. Conclusion
In conclusion, 1,2-diphenylethane-1,2-dione, phenylamine, 3,5-dichlorosalicylaldehyde, and ammonium
acetate were combined in this novel one-pot reaction to produce a desired compound with an impressive yield. Comprehensive characterisation of the synthesised chemical was carried out using FT-IR, 1 H
and 13 C-NMR spectroscopic techniques. Furthermore,
DFT/B3LYP/6-311G basic set calculations were used
to optimise the chemical structure. The calculated values and the expected outcomes were almost exactly
the same, indicating good agreement between theory
23
and experiment. According to studies from molecular
docking and molecular dynamics simulations, the DPIP
molecule may have antiviral properties against COVID19/6WCF/6Y84/6LU7 receptors. After a thorough in vivo
examination, the physicochemical and ADMET metrics
indicate that the disclosed analogues have an excellent
oral bioavailability and may therefore be favourable hit
prospects for the ongoing drug discovery of novel antiviral medicines.
Disclosure statement
No potential conflict of interest was reported by the author(s).
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