Journal of Biomolecular Structure and Dynamics
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/tbsd20
Identification of novel potential inhibitors of
varicella-zoster virus thymidine kinase from
ethnopharmacologic relevant plants through an
in-silico approach
Samuel Kojo Kwofie, Dorothy Gyamfua Annan, Cynthia Ayefoumi Adinortey,
Daniel Boison, Gabriel Brako Kwarko, Rachel Araba Abban & Michael Buenor
Adinortey
To cite this article: Samuel Kojo Kwofie, Dorothy Gyamfua Annan, Cynthia Ayefoumi Adinortey,
Daniel Boison, Gabriel Brako Kwarko, Rachel Araba Abban & Michael Buenor Adinortey
(2021): Identification of novel potential inhibitors of varicella-zoster virus thymidine kinase from
ethnopharmacologic relevant plants through an in-silico approach, Journal of Biomolecular
Structure and Dynamics, DOI: 10.1080/07391102.2021.1977700
To link to this article:  https://doi.org/10.1080/07391102.2021.1977700
View supplementary material Published online: 17 Sep 2021.
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JOURNAL OF BIOMOLECULAR STRUCTURE AND DYNAMICS
https://doi.org/10.1080/07391102.2021.1977700
Identification of novel potential inhibitors of varicella-zoster virus thymidine
kinase from ethnopharmacologic relevant plants through an in-silico approach
Samuel Kojo Kwofiea,b , Dorothy Gyamfua Annanb, Cynthia Ayefoumi Adinorteyc , Daniel Boisond ,
Gabriel Brako Kwarkob, Rachel Araba Abbanb and Michael Buenor Adinorteyd
aDepartment of Biomedical Engineering, School of Engineering Sciences, College of Basic and Applied Sciences, University of Ghana, Accra,
Ghana; bWest African Centre for Cell Biology of Infectious Pathogens, Department of Biochemistry, Cell and Molecular Biology, College of
Basic and Applied Sciences, University of Ghana, Accra, Ghana; cDepartment of Molecular Biology and Biotechnology, School of Biological
Sciences, University of Cape Coast, Cape Coast, Ghana; dDepartment of Biochemistry, School of Biological Sciences, University of Cape
Coast, Cape Coast, Ghana
Communicated by Ramaswamy H. Sarma
ABSTRACT ARTICLE HISTORY
Although Varicella or chickenpox infection which is caused by the varicella-zoster virus (VZV) has sig- Received 25 February 2021
nificantly been managed through vaccination, it remains an infection that poses threats to the nearest Accepted 3 September 2021
future due to therapeutic drawbacks. The focus of this research was geared towards in silico screening
for the identification of novel compounds in plants of ethnopharmacological relevance in the treat- KEYWORDS
ment of chicken pox in West Africa. The work evaluated 65 compounds reported to be present in Chickenpox; varicella zostervirus; thymidine kinase;
Achillea millefolium, Psidium guajava and Vitex doniana sweet to identify potential inhibitors of thymi- molecular docking;
dine kinase, the primary drug target of varicella zoster virus. Out of the 65 compounds docked, 42 of molecular dynamics
these compounds were observed to possess binding energies lower than 
7.0 kcal/mol, however only simulations
20 were observed to form hydrogen bond interactions with the protein. These interactions were eluci-
dated using LigPlotþ and MM-PBSA analysis with residue Ala134 predicted as critical for binding.
Pharmacological profiling predicted three potential lead compounds comprising myricetin, apigenin- 4’
-glucoside and Abyssinone V to possess good pharmacodynamics properties and negligibly toxic. The
molecules were predicted as antivirals including anti-herpes and involved in mechanisms comprising
inhibition of polymerase, ATPase and membrane integrity, which were corroborated previously in
other viruses. These drug-like compounds are plausible biotherapeutic moieties for further biochemical
and cell-based assaying to discover their potential for use against chickenpox.
Abbreviations: ADMET: absorption, distribution, metabolism, excretion and toxicity; AUC: Area Under
Curve; CYP: Cytochromes P450; DUD-E: Directory of Useful (Docking) Decoys- Enhanced; DUD-E:
Database of Useful (Docking) Decoys - Enhanced ¼; ESOL: Effective Solubility; GROMACS: GROningen
MAchine for Chemical Simulations; HPC: High Performance Computing; ID: Identification; Log P:
Logarithm of the octan-1-ol/water partition coefficient; MD: Molecular Dynamics; MM-PBSA: Molecular
Mechanics Poisson Boltzmann Surface Area; MW: Molecular Weight; P-gp: Permeability glycoprotein;
PASS: Prediction of Activity Spectra for Substance; PDB: Protein Data Bank; RCSB: Research
Collaboratory for Structural Bioinformatics; Rg: radius of gyration; RMSD: Root Mean Square Deviation;
RMSF: Root Mean Square Fluctuation; ROC: Receiver Operating Characteristic; SDF: Structure Data File;
SMILES: Simplified Molecular Input Line Entry System; TK: thymidine kinase; TPSA: Topological Polar
Surface Area; UFF: Universal Force Field; VZV: varicella-zoster virus
1. Introduction chicken pox and shingles (Andrei & Snoeck, 2011). Humans
become infected with the varicella zoster virus when the
Many viral infections associated with children include vari-
virus gets in contact with either the mucosa of the upper
cella or varicella-zoster, usually known as chickenpox infec- respiratory tract or conjunctiva (Cohen et al., 1999). With an
tion. Though this viral disease is mostly found in juveniles, incubation period of 14 days, the virus circulates through the
there are reports of its occurrence among adults (Civen et bloodstream to the skin in mononuclear cells, which causes
al., 2009; Marin et al., 2008; Singh et al., 2015). Varicella is a the vesicular rash associated with the infection (Cohen et al.,
well-recognized systemic highly contagious airborne disease 1999). Chickenpox is characterized by fever and may be intri-
caused by varicella zoster virus (VZV), a virus in the cate with secondary bacterial infections such as cellulitis and
Herpesviridae family that also causes shingles. The virus can necrotizing fasciitis, common among adults, adolescents and
also be transmitted via fomites from skin lesions present in immunocompromised individuals (Gershon, 2017). Following
CONTACT Michael B. Adinortey madinortey@ucc.edu.gh Department of Biochemistry, University of Cape Coast, Cape Coast, Ghana.
Supplemental data for this article can be accessed online at https://doi.org/10.1080/07391102.2021.1977700

 2021 Informa UK Limited, trading as Taylor & Francis Group
2 S. K. KWOFIE ET AL.
primary infection, VZV establishes latency in the sensory gan- presence of certain compounds or secondary metabolites
glia which can reactivate to cause shingles (herpes zoster) often produced by these plants to serve as defense against
(Andrei & Snoeck, 2011). Chickenpox can be complicated by herbivory, pathogen attack, abiotic stress and also inter plant
chronic pain and other serious neurological and oracular dis- competition (Mothana et al., 2010). Among the many plants
orders like vasculopathy, keratitis, and retinopathy as well as used in the treatment of chickenpox in West Africa are
multiple visceral and gastrointestinal disorders including pep- Psidium guajava (Ayitey-Smith, 1989), Vitex doniana sweet
tic ulcers, hepatitis and pancreatitis (Angamuthu et al., 2019). (Jean et al., 2019) and Achillea millefolium (Bonsu, 2012).
Vaccines are available in many countries to prevent the Psidium guajava commonly called guava, is a plant that is
onset of disease (Baxter et al., 2013; Park et al., 2013) include known due to its curative potentials especially as an antidiar-
VarilrixVR and VarivaxVR (Floret, 2005; Heininger & Seward, rheal agent as well as to treat stomach aches that arises as a
2006). Apart from vaccination existing for chickenpox infec- result of indigestion (Gutierrez et al., 2008). This plant has
tion, the condition is usually managed with some orthodox also been reported to be used for the treatment of chicken
pharmacotherapeutic agents, which are usually antiviral pox (Ayitey-Smith, 1989). Psidium guajava is a plant that
nucleoside analogues that require in vivo phosphorylation by grows in all subtropical and tropical area, and has the ability
thymidine kinase (TK). For many years, acyclovirVR has been to adapt to various climatic conditions, although it prefers to
the mainstay for the treatment of varicella infection, however grow in dry climates (Gutierrez et al., 2008). It belongs to the
other antiviral agents such as valacyclovir and famciclovir family Myrtaceae and grows about 10m high possessing a
have been developed to overcome the low oral bioavailabil- thin, but smooth, patchy and peeling bark (Gutierrez et al.,
ity of acyclovir and provide a more effective regimen 2008). Several bioactive compounds reported to be isolated
(Balfour et al., 2001; Chou & Lurain, 2019). The downside of from Psidium guajava, are responsible for its wide use as a
the use of these antivirals is the adverse side effects such as treatment for several infections. Some of these compounds
headache, vomiting, neurotoxic psychological effects, and include guajanerin, avicularin, kaemferol, myricetin, mecocya-
renal dysfunction (Chou & Lurain, 2019). These therapeutic nin, quercetin, leucocyanidin, guavin B, chlorogenic acid, lim-
shortfalls warrant more research in the drug discover pipe- onene, cuproel, caryophyllene, copaene, and zulene
line to identify potent alternatives with less adverse effects. (Gutierrez et al., 2008).
An essential drug target for this viral infection is varicella Another commonly used plant in the treatment of chicken
zoster virus thymidine kinase. The thymidine kinase is a pox in some West African countries is Vitex doniana sweet
phosphotransferase enzyme present in most living cells, (Ayitey-Smith, 1989; Bonsu, 2012; Jean et al., 2019). Vitex
responsible for catalyzing the transfer of phosphate groups doniana sweet can be said to be one of the most abundant
from ATP to deoxythymidine to form deoxythymidine mono- tree species usually found in Savannah regions of the world
phosphate (Hoffmann et al., 2017). The thymidine kinase is a (Leakey, 2001). It is a multiple-use plant with both nutritional
protein encoded by the varicella zoster virus that has both and medicinal importance (Eyog Matig et al., 2002). The fruit
thymidine and thymidylate phosphorylating activities of the plant is edible while the other parts are used as medi-
(Hoffmann et al., 2017). The protein is involved in the replica- cine in the treatment of ulcer, diabetes, and edema
tion of the viral DNA making it integrally involved in host (Osuagwu & Eme, 2013). It belongs to the family Verbenaceae
cellular infection mechanisms. Most drugs that are used and grows up to about 25m (Osuagwu & Eme, 2013).
against the varicella infection act competitively with the viral Bioactive compounds isolated from Vitex doniana Sweet
nucleoside triphosphates, mostly thymidine triphosphates, in include cupreol, campesterol, ecdysteron, loliolide, 4- pinore-
order to terminate the replication of the virus (Topalis et al., sinol, chrysin, Abyssinone V, galangin and catechol
2018). Acyclovir, for instance is first phosphorylated select- (Ajiboye, 2015).
ively by the viral thymidine kinase protein to form its mono- Achillea millefolium commonly known as yarrow, is
phosphate derivative, which is further metabolized by the another medicinal plant which is used to manage viral infec-
host cellular enzymes to form the triphosphate derivatives. tions and related diseases including chicken pox (Bonsu,
These then act as preferred substrates for the viral DNA poly- 2012). It belongs to the Asteraceae family (Benedek & Kopp,
merase and disrupt the DNA synthesis in the virus thereby 2007). Traditionally, the yarrow plant is used for the treat-
terminating its activity (Chou & Lurain, 2019). ment of inflammation and also for spasmodic gastrointestinal
Plants have served as a major reservoir of medicine for disorders and hepatobiliary complaints (Benedek & Kopp,
numerous diseases including viral infections. They are recog- 2007). In addition, it is also used as an appetite enhancing
nized as natural sources for the synthesis of medicinal com- drug, wound healing and against skin inflammations. Apart
pounds, and the characterization of these compounds have from the traditional uses, the yarrow plant is also contained
directed the discovery of new and economical drugs that in various industrial tea mixtures and other phytopharma-
have curative and prophylactic potentials (Huie, 2002). ceuticals (Benedek & Kopp, 2007). Several bioactive com-
According to World Health Organization, approximately 60% pounds have been isolated from different parts of yarrow.

 80% of the world population depends on medicinal plants These bioactive compounds include butain, choline, betano-
for their primary healthcare, and most drugs are derived cine, achilletin and azulene (Applequist & Moerman, 2011;
from unmodified natural products or semi-synthetic drugs Chandler et al., 1982)
obtained from natural sources (Mothana et al., 2010; W.H.O, Several cheminformatics studies have identified inhibitors
2002). The bioactivity of natural products is due to the against viral drug targets (Kadioglu et al., 2021; Kwofie,
JOURNAL OF BIOMOLECULAR STRUCTURE AND DYNAMICS 3
Broni, et al., 2019; Kwofie et al., 2021; Prasanth et al., 2020; 2.2. Selection of ligands
Yaeghoobi et al., 2016). The structure of the varicella zoster
A library composed of 65 isolated compounds obtained from
virus thymidine kinase has been solved using X-ray crystal-
Achillea millefolium, Psidium guajava and Vitex doniana sweet
lography and modelled using homology modeling, as well as
together with 2 known inhibitors of VZV thymidine kinase
molecular docking studies have been undertaken (Abo
comprising acyclovir and valacyclovir was generated. These
Almaali, 2018; Bird et al., 2003; Spadola et al., 2003).
ligands were obtained from PubChem (https://pubchem.ncbi.
In silico pharmacological screening of isolated compounds
nlm.nih.gov/) (Kim et al., 2019) and energy minimized using
of Psidium guajava, Vitex doniana Sweet and Achillea millefo-
OpenBabel environment via PyRx (Dallakyan & Olson, 2015).
lium plants used for the treatment of chickenpox could con-
The energy minimization was done by means of the
tribute to identifying novel VZV thymidine kinase inhibitors
Universal Force Field (UFF) (Artemova et al., 2016). The
of natural origin. Even though, many compounds have been
Universal Force Field (UFF) is applicable to almost all atom
isolated from these plants, there is dearth of literature per- types of the periodic table and such flexibility makes this
taining to their pharmacological utility with regards to force field a potential good candidate for simulations involv-
chicken pox. Therefore, this work used cheminformatics ing a large spectrum of systems (Artemova et al., 2016). This
approaches including molecular docking and dynamics simu- force field is non-reactive, i.e. the topology of the system
lation to screen bioactive constituents present in different under study is considered as fixed and no creation or break-
extracts of these plants against the drug target VZV-thymi- ing of covalent bonds is possible (Jaillet et al., 2017). The
dine kinase. In addition, it explored the propensity of the algorithm employed for the energy minimization using
potential novel leads to inhibit viral replication in chicken- OpenBabel environment in PyRx (Dallakyan & Olson, 2015)
pox. The study also elucidated new insights into the binding was the conjugate gradient optimization algorithm, and
mechanisms and identified residues critical to interactions as energy minimization was done for 200 steps, with the num-
well as for design of next-generation anti-VZV molecules. ber of updates for a step being one and also energy differ-
More so, this work identified mechanisms of actions and bio- ence for stop being 0.1. All ligands were converted to a
logical activity of identified natural products. (.pdbqt) formats.
2. Materials and methodology 2.3. Molecular docking of compounds against VZV
The methodology schema describing the step-by-step techni- thymidine kinase receptor
ques used for the study is described (Figure 1). The work Known active site residues were selected within a grid box
involved the generation of the library from ethnopharmaco- of dimensions X: 58.75 Å, Y: 36.22 Å, and Z: 25 Å; and center
logical plants which were screened against VZV Thymidine X: 49.04 Å, Y: 32.84 Å, and Z: 67.09 Å within AutoDock Vina
Kinase Receptor to identify potential leads using environment which uses the gradient optimization algorithm
cheminformatics. (Trott & Olson, 2010). Molecular docking was then carried
out to ascertain the binding affinity between the protein and
2.1. Pre-processing of VZV thymidine kinase receptor the ligands. The resulting docked poses of the ligands within
the protein structure were visualized using PyMol.
The 3D crystal structural of VZV thymidine kinase with reso-
lution of 3.2 Å was retrieved from Protein Data Bank (www.
rcsb.org, PDB ID: 1OSN). The BVDU-MP and ADP ligands as 2.4. Mechanism of binding characterization
well as all water molecules were detached from the protein LigPlotþ (v1.4.5) (Laskowski & Swindells, 2011; Wallace et al.,
structure using PyMol (version 1.7.4.5) (Schrodinger, 2010). 1995) was used to characterize the binding mechanisms
SwissPDB viewer (Guex et al., 2009) was used to replace all between the target protein structure and selected com-
missing residues before the topology of the protein was gen- pounds based on their hydrogen and hydrophobic
erated. The final molecule was then saved in a (.pdb) file for interactions.
molecular dynamics (MD) simulations. The MD simulations of
the receptor were performed using a high-performance com-
puting (HPC) server. The MD was done using the down- 2.5. Validation of docking protocol
loaded crystal structure of the receptor by means of LigAlign (Heifets & Lilien, 2010) was employed in validating
GROMACS (Lemkul, 2019). Energy minimization was done at the docking protocol. The ligand was removed from the co-
25,000,000 steps and position restraints were applied to crystalized complex and re-docked. The redocked and co-
1OSN, thereafter a temperature equilibration at 300 K fol- crystallized complexes were superimposed using LigAlign to
lowed by a pressure equilibration at 1 bar was carried out for calculate the deviation between them. LigPlotþ was used to
100ps each. The production MD was then run for 100 ns, obtain co-occurring interaction residues from both com-
keeping the temperature at 300 K and the pressure at 1 bar. plexes for further validation of the docking protocol. The
Xmgrace (Turner, 2005) was used to plot the graphs gener- Receiver Operating Characteristic (ROC) curve was plotted via
ated from the MD simulations. The final (.gro) file was con- easyROC (Goksuluk et al., 2016) and the Area Under Curve
verted back to (.pdb) file for molecular docking. (AUC) was subsequently computed. Twelve active
4 S. K. KWOFIE ET AL.
Figure 1. Methodology schema employed in the In silico studies for predicting potential anti-VZV thymidine kinase compounds. Natural compounds from three
medicinal plants used traditionally in Ghana against chicken pox were downloaded from the PubChem Database and were docked against the VZV thymidine kin-
ase receptor. Compounds with binding affinities of -7.0 kcal/mol against the receptor were selected for downstream analysis. The methods include the character-
izations of protein-ligand complexes, biological activity predictions and MD simulations.
compounds comprising satabacin, sattazolin, valacyclovir, deoxyuridine (Migliore, 2010) were used to generate a total
acyclovir, brivudine, sorivudine, CF-1743, adefovir, cidofovir, of 600 decoys. Each active compound was used to generate
penciclovir, 5- bromothienyldeoxyridine and chlorovinyl- 50 decoys via the Directory of Useful (Docking) Decoys-
JOURNAL OF BIOMOLECULAR STRUCTURE AND DYNAMICS 5
Enhanced (DUD-E) (Mysinger et al., 2012). All the compounds PKCSM (Pires et al., 2015) (http://biosig.unimelb.edu.au/
were then docked against the receptor (1OSN). pkcsm/prediction).
2.6. MD simulations and MM-PBSA calculations of
receptor-ligand complexes 2.8. Prediction of biological activity of
Complexes with optimum binding affinities were further sub- selected compounds
jected to molecular dynamics simulation to investigate flexi- Prediction of Activity Spectra for Substance (PASS) (Filimonov
bility and stability. All molecular dynamics (MD) simulations et al., 2014) was used for the prediction of the biological
were performed for 100 nanoseconds using GROMACS ver- activity of selected compounds based on a training dataset
sion 2018 with the force field, GROMOS96 43a1 and SPC of known substrate present in its database. Simplified
water model. MDs were carried out on a Dell EMC high per- Molecular Input Line Entry System (SMILES) of the com-
formance computing (HPC) system that comprises CentOS 7 pounds were used as inputs.
operating systems, 6 nodes, 12 GPUs, 216 CPUs and storage
of 277 TB, located at the West African Centre for Cell Biology
of Infectious Pathogens (WACCBIP), University of Ghana,
Accra. The simulations were done in a dodecahedron box of 3. Results and discussion
size 1.0 nm, solvated with SPC water and neutralized by add-
ing 4 chlorine ions. For the MD of the docked complex, the The focus of the work was to screen the constituents of
topology file for the potential leads, the co-crystallized ligand three ethnopharmacological plants which are used to treat
and the known drug inhibitor, was generated using varicella-zoster virus infections in Ghana against VZV thymi-
PRODRG2 server (Schu€ttelkopf & Van Aalten, 2004) with the dine kinase receptor to identify potential novel bioactive
settings herein (Chirality: Yes, Charges: Full, EM: No). Energy compounds. A total of 65 compounds presents in Achillea
minimization was done at 50000 steps using the steepest millefolium, Psidium guajava and Vitex doniana sweet plants
descent algorithm. Position restrains were applied to both were used for in silico studies. In general, the properties of
the proteins and ligands using the holonomic restrain algo- potential novel lead compounds include low binding energy
rithm, after which a temperature equilibration at 300 K fol- (high binding affinity) to the target, reasonably good ADMET
lowed by a pressure equilibration at 1 bar was performed for properties and strong intermolecular interactions between
50,000 ps each. Temperature and pressure coupling were protein receptors and the ligands (Prasanth et al., 2020).
performed with Berenson-thermostat and Parrinello-Rahman
barostat, respectively. Particle Mesh Ewald (PME) (Essmann et
al., 1995) was used for calculating long-range electrostatics.
A short range cut off of 1.0 nm was set for van der Waals 3.1. Molecular docking analysis
interaction. Moreover, time-step value was set to 2 fs. The The VZV thymidine kinase is observed to be a homo tetra-
production MD runs were then performed for 100 ns, keep- meric protein having its active site present within each sub-
ing the temperature at 300 K and the pressure at 1 bar.
unit and not at the interface of the interacting subunits (Bird
Xmgrace (Turner, 2005) was used to plot the graphs gener-
et al., 2003). Therefore, it was ideal to select any one of the
ated from the MD simulations.
chains (chain B) of the entire protein for docking analysis.
Molecular Mechanics Poisson Boltzmann Surface Area
(MM-PBSA) computations of the complexes were carried out This approach is also seen to be employed in a study that
using g_mmpbsa (Kumari et al., 2014) MM-PBSA calculates involved identical subunits for docking (Minai-Tehrani et al.,
the binding free energy components and the discrete energy 2015). In determining novel potential leads against the VZV
contributions of the residues. This is achieved primarily by thymidine kinase, molecular docking studies was performed
using a thermodynamic path that includes solvation using a total of 65 natural products together with two
(Genheden & Ryde, 2015). Graphs of binding free energies known inhibitors comprising acyclovir and valacyclovir (Arvin,
were obtained with the R programming package. 1996). Ligands possessing binding energies less than

7 kcal/mol were selected for downstream analyses
(Prasanth et al., 2020) with a total of 42 complying with this
2.7. Pharmacological and toxicity profiling of threshold. Details of the binding energies of the ligands with
selected compounds the protein and the biomolecular interactions are described
The pharmacological properties of all the ligands selected (Table 1 and Supplementary Table 1). Residues comprising
were analyzed using the SwissADME (Daina et al., 2017). The Ala20, Tyr21, Gly22, Ile23, Gly24, Thr26, Thr27, Glu48, Trp53,
compounds were then filtered using the Lipinski’s rule of Ile62, Tyr66, Gln90, Phe93, His97, Asp129, Arg130, Ser135,
five (Lipinski, 2016), Bioavailability Score (Martin, 2005) and Phe139, Arg143, Arg183 and Pro302 were identified in the
the Veber’s rule (Veber et al., 2002). In addition, the pharma- active site of the structure of VZV thymidine kinase (Bird et
cokinetic properties absorption, distribution, metabolism, al., 2003), therefore molecular docking of the ligands against
excretion (ADME) were predicted using SwissADME (Daina et the receptor was done in the active site pocket of the pro-
al., 2017). The toxicity of the ligands was predicted using the tein (Figure 2).
6 S. K. KWOFIE ET AL.
Table 1. Binding energies and molecular interactions of two known inhibitors against VZV thymidine kinase, the co-crystallized ligand (BVDP-MU) and the three
potential lead compounds. The ligand names, PubChem CIDs, plant sources and the intermolecular bonds are included.
Source
Binding affinity Interacting residues Hydrogen bond Hydrophobic
Ligand Pubchem CID (kcal/mol) Length(Å) Part of plant length & residues interactions
BVDU-MP 
8.9 Co-crystalized ligand Gly22(3.01); Tyr21, Glu48, Trp53,
Tyr66(3.22) Ile62, Phe93,
Gln90(3.05, 3.14); His97, Ala134,
Arg130(2.91); Ser135, Phe139,
Acyclovir 135398513 
6.5 Standard drug Tyr66(3.05,3.93); Tyr21, Glu48, Trp53,
Gln90(3.08) Phe93, Arg130,
Ser135, Phe139,
Valacyclovir 135398742 
7.0 Standard drug Lys25(3.21,3.28); Tyr21, Gly22, Gly24,
Thr26(2.85) Tyr66(3.24); Glu48, Phe93,
Arg130, Phe139
Apigenin-40-Glucoside 5491384 
10.2 Achillea millefolium Leaf and Gly22(3.23); Gly24(2.88); Tyr21, Ile23, Lys25,
flower head Gln90(2.70, 3.30) Thr26, Glu48,
Trp53, Phe93,
Arg130, Ala134,
Ser135, Phe139
Abyssinone V 6548074 
9.6 Vitex doniana sweet Fruit Gln90(3.33, 2.70) Tyr21, Gly22, Lys25,
Glu48, Trp53,
Ile62, Phe93,
Arg130, Ala134,
Ser135, Phe139,
Val184, Glu192
Myricetin 5281672 
9.3 Psidium guajava Flower Gly22(3.26), Gln90(2.86) Tyr21, Glu48, Leu50,
Trp53, Phe93,
Arg130, Ala134,
Ser135, Phe139,
experimentally determined ones shared mutual interactions
with specific amino acid residues present within the active
site of the protein. When the redocked ligand pose of BVDU-
MP of structure 1OSN was superimposed with the co-crystal-
ized ligand (BVDU-MP) (Figure 3a), there were overlaps of
hydrogen bonds involving three critical active site residues
comprising Arg130, Tyr66 and Gln90 (Figure 3b). In addition,
there were overlaps of hydrophobic contacts involving seven
residues Ser135, Phe93, Phe139, Ile62, Glu48, Tyr21 and
Trp53. These overlaps support the ability of AutoDock Vina
to reproduce the experimental binding pose. The RMSD
obtained was 0.990 Å (Figure 4), which was within the 2 Å
Figure 2. A cartoon representation of the structure of varicella-zoster virus thy-
midine kinase with abyssinone V (Red stick), myricetin (Cyan blue stick) and api- threshold (Alves et al., 2014).
genin-4’-glucoside (Yellow stick) docked in its binding pocket presented
as surface.
3.2.2. Receiver operating characteristic (ROC) curve
The AutoDock Vina docking protocol used was validated using
the ROC curve. The ROC curve is useful when measuring the
3.2. Validation of docking protocol ability of a docking model to clearly decipher between active
compounds from inactive ones with respect to the protein
3.2.1. Alignment and superimposition
receptor under study (Kwofie, Enninful, et al., 2019). After the
Validation of docking protocol is essential in evaluating the
efficiency and performance of the AutoDock Vina (Granchi et ROC curve was generated, the Area Under Curve (AUC) was
al., 2015; Heifets & Lilien, 2010). Therefore, the focus of re- computed to measure the performance of docking protocol
docking and superimposition was to validate the docking (Mandrekar, 2010). The AUC computed for the study was
protocol used. LigAlign (Heifets & Lilien, 2010) script 0.8099, which is closer to 1, indicating an efficient docking
embedded in the PyMol environment was used in validating (Mandrekar, 2010). From the results, AutoDock Vina reasonably
the protocol. LigAlign uses superimposition of ligands in vali- distinguished active from inactive compounds (Figure 5).
dating the docking protocol by calculate the Root Mean
Square Deviation (RMSD) between the two ligands. This tech- 3.3. Characterization of binding mechanism
nique is widely adopted for structural analysis of the protein-
ligand complex (Heifets & Lilien, 2010). After the redocking, After the molecular docking studies, the ligands were filtered
it was observed that these predicted binding poses and the using the LigPlotþ (Laskowski & Swindells, 2011) prediction
JOURNAL OF BIOMOLECULAR STRUCTURE AND DYNAMICS 7
Figure 3. Surface representation of 1OSN with co-crystallized BVDU-MP (red) and re-docked BVDU-MP (blue) its binding pocket (A) and superimposed LigPlotþ
showing overlapped interactions between the co-crystallized and re-docked ligands (BVDU-MP) (B). The circled residues in red show the overlapped molecular
interactions.
Figure 4. A PyMol representation of the superimposed re-docked BVDU-MP lig-
and with 1OSN (in cyan blue) and co-crystalized the BVDU-MP ligand of 1OSN
with BVDU-MP (in yellow). The RMSD was calculated to be 0.990 Å.
Figure 5. Receiver Operating Characteristic (ROC) curve for varicella-zoster virus
thymidine kinase. The curve was obtained after docking 12 actives and 600 Figure 6. Ligplotþ representation of Apigenin-4’-Glucoside in complex with
decoys against the receptor. 1OSN showing the intermolecular bonds.
of intermolecular interactions between the ligands and the and 2.79 and 3.38 while hydrophobic interactions were
receptor. Ligands which did not have any interactions with formed between Tyr21, Lys25, Thr26, Glu48, Phe93, Arg130,
the receptor were excluded from further analysis. Twenty out Ala134, Ser135 and Phe139 (Figure 6). Also, for myricetin,
of the forty-two ligands predicted to have hydrogen bond hydrogen bonds were observed to be formed between
interactions were used for further analysis (Stilinovic et al., Gln90 and Gly22 with bond lengths of 2.86 and 3.26 respect-
2017) (Supplementary Table 1). For Apigenin-40-Glucoside, ively and hydrophobic interactions were formed with Tyr21,
three hydrogen bonds were observed to be formed with the Leu50, Trp53, Phe93, Arg130, Ala134 and Phe139
protein target. These bonds were identified to be Gln22, (Supplementary Figure S1). Hydrogen bonds with bond
Gly24 and Gln90 with respective bond length of 3.33, 2.88 lengths of 3.33 and 2.70 were formed between Abyssinone V
8 S. K. KWOFIE ET AL.
and Gln90 of the protein with hydrophobic interactions brain from any foreign substance present in the blood. It con-
involving Tyr21, Gly22, Lys25, Glu48, Trp53, Ile62, Phe93, sists of a barrier that physically separates the blood vessels of
Arg130, Ala134, Ser135, Phe139, Val184 and Glu192 the brain from the cells and all the other components of the
(Supplementary Figure S2) body (Armulik et al., 2010). It also consist of some enzymes as
well as transporters that maintains the integrity of the extracel-
lular environment of the central nervous system (Armulik et al.,
3.3. Drug likeness 2010). In summary, 9 of the ligands that were predicted to
The drug likeliness of potential lead compounds was eval- have good physiochemical properties were soluble, while 3
uated physicochemical parameters. The rules used included were identified to be poorly soluble, and both of the standard
the Lipinski rule of five (RO5), the Verber’s rule and bioavail- drugs were also predicted to be very soluble (Table 4).
ability score. According to the Lipinski rule of five, orally However, 8 were predicted as BBB impermeant, and 4 were
active compounds are defined by five parameters which are BBB permeant, while both standard drugs were impermeant to
molecular weight  500Da, LogP  5, Hydrogen bond the BBB. The four compounds, thus, pinoresinol, achillicin,
donors  5, hydrogen bond acceptors  10, and 40molar alpha terpineol and eugenol, that were predicted to be BBB
refractivity  140 (Lipinski, 2016). Seven out of the twenty permeant were excluded from further analysis. This is because,
ligands violated the rule, leaving only 13 compounds for fur- compounds that are known to be BBB permeant without hav-
ther analysis (Table 2). Standard drugs Acyclovir and violated ing any neurological roles can cause severe effects (Chen &
none of the rules (Table 2). The Verber’s rule suggests that Liu, 2012). Again, 12 compounds were found to be non-inhibi-
compounds that meet only the two conditions of ten or tors of the cytochrome P450 class of enzymes (Table 4). The 8
fewer rotatable bonds and a polar surface area lesser or compounds that were therefore taken for further analysis are
equal to 140 Å2 have a high probability of good oral bio- those that were non-inhibitors of the cytochrome P450 class of
availability (Veber et al., 2002). Results from our study indi- enzymes and also were BBB impermeant.
cated that, out of the 13 ligands that were evaluated with
Veber’s rule, 10 of them had a polar surface area less than
2 3.5. Toxicity of ligands140 Å while three had their polar surface area to be greater
than 140 Å2, thus apigenin-40-glucoside, myricetin and sabine The AMES toxicity, hepatotoxicity, skin sensitization, hERG I
had the polar surface area of 170.05 Å2, 151.59 Å2, 144.85 Å2 inhibitor and the maximum dose of the ligand tolerated in
respectively (Table 3). Also, valacyclovir, a standard drug had the human body a day were ascertained as a way of predict-
a polar surface area of 151.14 Å2 (Table 3). Bioavailability ing the toxicity of these ligands (Pires et al., 2015). Table 5
Score is also used to identify poorly and well absorbed com- provides a summary on these properties for each of the
pounds that have been tested in humans (Martin, 2005). compounds. Some of the ligands were predicted to have
Bioavailability Score is expressed as the likelihood that a hepatotoxicity, AMES toxicity, skin sensitization and can be
compound will have >10% bioavailability in rat or quantifi- tolerated in the body at average concentrations per day
able Caco-2 permeability (Martin, 2005). Bioavailability Score (Table 5). None of the compounds, including the standard
for anions is 0.11, for which TPSA is >150 Å2, 0.56 if TPSA is drugs was predicted to be an inhibitor of hERG I, a gene
between 75 and 150 Å2, and 0.85 if PSA is <75Å2, and for that codes for the alpha subunit of the potassium ion chan-
the remaining compounds, a bioavailability score is 0.55 for nel, best known for how it contributes to the electrical activ-
those compounds that obey the Lipinski rule of five and 0.17 ity of the heart (Hedley et al., 2009). A freely accessible web
for those that violate the law. (Martin, 2005). From our study, server, the pKCSM server, which provides an integrated plat-
a bioavailability score was only assessed on the compounds form to rapidly evaluate pharmacokinetic and toxicity prop-
that conformed to Lipinski rule of 5, and all of them had a erties was used to assess the toxicity of the ligands. The
bioavailability score of 0.55 (Table 3). This is a confirmation pKCSM online server uses the graph-based structural signa-
of the compounds’ conformity to the rule of 5. tures concept to study and predict a range of ADMET prop-
erties for new chemical entities (Pires et al., 2015). It builds
thirty (30) predictors which are divided into five major
3.4. Prediction of ADME properties classes: absorption (seven predictors), distribution (four pre-
The ADME studies of drug candidates are extensively used in dictors), metabolism (seven predictors), excretion (two pre-
drug discovery to heighten the balance of properties required dictors), and toxicity (10 predictors) however, in our study,
to convert leads into good drugs (Selick et al., 2002). The three this server was only used to predict the toxicity of the
potential leads do not inhibit all three isoforms of the cyto- ligands. The ten (10 toxicity predictors include; AMES toxicity,
chrome P450 enzymes, although some of them were observed maximum tolerated dose, oral rat acute toxicity (LD50), oral
to inhibit either one or two of the classes (Table 4). rat acute toxicity (LOAEL), hepatotoxicity, skin sensitization, T.
Cytochrome P450 is an important class of enzyme involved in Pyriformis toxicity and minnow toxicity.
the metabolism of drugs in the liver (Donato & Castell, 2003). If
a drug is predicted to inhibit all the classes of cytochrome 3.6. Anti-viral prediction with PASS
P450, it has the potential to impair the metabolism and may
lead to toxicity (Donato & Castell, 2003). The blood brain bar- The biological activity of the compounds was predicted
rier (BBB) is a protective element of the brain that protects the using the prediction of activity spectra for substances (PASS)
JOURNAL OF BIOMOLECULAR STRUCTURE AND DYNAMICS 9
Table 2. Physicochemical properties of active compounds present in Psidium guajava, Vitex doniana sweet and Achillea millefolium using the Lipinski rule of 5.
Parameters assessed are molecular weight, number of hydrogen bonds donors, number of hydrogen bond acceptors, logP, and molar refractivity. The number
of violations for each compound is also shown.
Number of Number of
Molecular hydrogen hydrogen
Ligand weight (Dalton) bond donors bond acceptors LogPo/w (MLOGP) Molar refractivity Number of violations
Acyclovir 225 3 5 
1.83 55.68 0
Valacyclovir 324 3 7 
1.19 82.54 0
Campesterin 400 1 1 6.54 128.42 1
Cynaroside 448 7 11 
2.10 108.13 2
Apigenin- 432 6 10 
1.61 106.11 1
40-Glucoside
Luteolin 40- 448 7 11 
0.40 105.20 2
O-Glucoside
Isochlorogenic 516 7 12 
0.35 126.90 3
Acid B
Cupreol 414 1 1 6.73 133.23 1
3,5- 516 7 12 1.02 125.19 3
Dicaffeoylquinic
Acid
Abyssinone V 408 3 5 2.82 119.01 0
Pinoresinol 358 2 6 1.17 94.90 0
Quercetin 302 5 7 1.99 78.03 0
Rutin 610 10 16 
3.89 141.38 4
Achillicin 306 1 5 2.0 80.31 0
Myricetin 318 6 8 
1.08 80.06 1
Guaijaverin 434 7 11 
2.06 104.19 2
Avicularin 434 7 11 
2.06 104.19 2
Achletin 380 3 6 0.05 81.98 0
Sabine 495 7 8 0.60 134.05 1
Alpha terpineol 154 1 1 2.3 48.8 0
Millefin 350 0 6 2.38 92.13 0
Eugenol 164 1 2 2.01 49.06 0
Table 3. Prediction of the oral bioavailability of the ligands using the Veber’s rule and bioavailability Score.
Ligand Topological polar surface area (Å2) Number of rotatable bonds A bioavailability score
Acyclovir 119.05 4 0.55
Valacyclovir 151.14 8 0.55
Campesterin 20.23 5 0.55
Apigenin-40-Glucoside 170.05 4 0.55
Alpha Elemene 0.00 2 0.55
Cupreol 20.23 6 0.55
Abyssinone V 86.99 5 0.55
Pinoresinol 77.38 4 0.55
Quercetin 131.36 1 0.55
Achillicin 72.83 2 0.55
Myricetin 151.59 1 0.55
Achletin 135.12 2 0.55
Sabine 144.85 0 0.55
Alpha terpineol 20.23 1 0.55
Millefin 78.90 4 0.55
Eugenol 29.46 3 0.55
Table 4. Prediction of adsorption, distribution, metabolism and excretion (ADME) properties of selected ligands. Water solubility of the ligands, class of solubil-
ity, BBB permeability, gastrointestinal absorption, Cytochrome P450 inhibition and P-glycoprotein substrate were computed.
Water
solubility; Gastrointestinal CYP2C19 P-Glycoprotein
Ligand LogS (ESOL) Class of solubility BBB permeability absorption CYP1A2 inhibition inhibition CYP3A4 inhibition substrate
Acyclovir 
0.41 Very soluble No High No No No No
Valacyclovir 
1.23 Very soluble No Low No No No Yes
Campesterin 
7.54 Poorly soluble No Low No No No No
Apigenin- 
3.41 Soluble No Low No No No Yes
40-Glucoside
Cupreol 
7.90 Poorly soluble No Low No No No No
Abyssinone V 
6.35 Poorly soluble No High No No Yes No
Pinoresinol 
3.58 Soluble Yes High No No Yes Yes
Quercetin 
3.16 Soluble No High Yes No Yes No
Achillicin 
1.97 Very soluble Yes High No No No No
Myricetin 
3.01 Soluble No Low Yes No Yes No
Achletin 
2.64 Soluble No High No No No No
Alpha terpineol 
2.87 Soluble Yes High No No No No
Millefin 
3.01 Soluble No High No No No No
Eugenol 
2.46 Soluble Yes High Yes No No No
10 S. K. KWOFIE ET AL.
Table 5. Prediction of the toxicity of the selected ligands. The AMES toxicity, hepatotoxicity, the maximum tolerated dose per day of the ligand, skin sensitiza-
tion and hERG 1 inhibition were ascertained using pKCSM.
Ligand AMES toxicity Hepatotoxicity Max. tolerated dose (mg/kg/day) Skin sensitization hERG I inhibitor
Acyclovir Yes Yes 2.655 No No
Valacyclovir No Yes 3.556 No No
Apigenin-40-Glucoside No No 2.938 No No
Campesterol No No 0.348 No No
Cupreol No No 0.239 No No
Abyssinone V No No 1.706 No No
Quercetin No No 3.155 No No
Myricetin No No 3.235 No No
Achletin Yes Yes 2.254 No No
Millefin No No 2.213 No No
online server, which provides the probability of activity (Pa) 3.8. Molecular dynamic simulations and MM-PBSA
and the probability of inactivity (Pi). The PASS online soft-
MD simulation was carried out for the ligand-protein com-
ware product contains 31,000 biologically active substances
plexes and the Root Mean Square Deviation (RMSD), Root
in the training set and predicts biological activity for 319
Mean Square Fluctuation (RMSF) and radius of gyration (Rg)
types of pharmacological effects, biological mechanism of
(Peele et al., 2020) were computed for each of the three poten-
actions as well as specific toxicity of the substances with an
tial leads together with the co-crystalized ligand (BVDU-MP)
average accuracy above 95%(Lagunin et al., 2000). Biological and the known drug acyclovir (Figures 7–9). MD simulations
activities with Pa >Pi are considered as worthy of pharmaco- predicted how these potential lead compounds forms stable
logical evaluation (Goel et al., 2011). Our study considered complexes with the target protein (Al-Khafaji et al., 2020). The
the antiviral herpes activity of the molecules since the vari- RMSD computed for all complexes indicates stability of the
cella-zoster virus belong to the family Herpesviridae protein even after docking (Al-Khafaji et al., 2020). For the co-
(Camacho-Soto et al., 2021; Wang et al., 2020). Out of 9 com- crystallized ligand BVDU-MP, the RMSD curve predicts a very
pounds shortlisted, only 3 of them namely myricetin, apige-
0 high stability as the curve plateaued at 0.2 nm from 0.5 ns ofnin-4 -glucoside and Abyssinone V were predicted as having MD run (Figure 7) till the 100 ns run was done. The three
anti-herpes activity with Pa  0.5 (Table 6). However, the potential lead-complexes showed great stability with RMSD
known drugs were predicted to have Pa > 0.7. The two- and values ranging from 0.3 nm to 0.7 nm, mostly peaking after
three-dimensional structures of the potential leads are shown 20 ns. The most stable among the three however was apige-
in Table 7. nin-40-glucoside-complex with RMSD of 0.3 nm, followed by
myricetin with 0.5 nm, and then abyssinone V with 0.7 nm
(Figure 7). The RMSF values indicates flexibility in different
regions of the protein (Islam et al., 2021). For the co-crystal-
3.7. Binding mechanisms of the potential
lized ligand BVDU-MP, the highest fluctuation occurred in the
lead compounds region between atoms 600 and 700 (Figure 8), after which
The potential lead compounds identified were myricetin there was great stability till the end of the run. Also, highest
from the fruit Psidium guajava, apigenin-40-glucoside from fluctuations were observed between atoms 500 and 1000,
the leaf of Achillea millefolium, and Abyssinone V from the 1600 and 2000 for abyssinone V and myricetin, respectively
0
fruit Vitex doniana Sweet. Apigenin-40- glucoside exhibited (Figure 8). Apigenin- 4 - glucoside showed fairly little fluctua-
binding affinity of 
10.2 kcal/mol against the receptor by tions along such regions. Greater amounts of structural fluctu-
forming four hydrogen bond interactions (Table 1) with ation occur in regions known to be involved in ligand binding
active site residues Gly24, Gly22 and Gln90, and hydrophobic and catalysis (Dong et al., 2018). RMSF of abyssinone V showed
contacts Lys25, Thr26, Glu48, Tyr21, Phe139, Phe93, Ser135, exceptionally much greater fluctuations at these atomic
Arg130, Trp53, Ile23 and Ala134. This was followed by regions which depicts greater adaptive variations in flexibility
Abyssinone V with binding affinity of 
9.6 kcal/mol forming which can increase the conformational stability of abyssinone
two hydrogen bond interactions with Gln90 and hydropho- V as compared to the other lead compounds in the protein
bic contacts with Ser135, Ala134, Phe93, Trp53, Arg130, complex. The radius of gyration values indicates the compact-
Gly22, Lys25, Phe139, Ile62, Glu192, Val184, Tyr21 and Glu48 ness of the complex structures (Islam et al., 2021). Rg values
(Table 1). Finally, myricetin also had a binding affinity of ranged from 1.85 nm to 1.95 nm for the complexes of potential

9.3 kcal/mol and formed two hydrogen bonds with key res- leads and the known inhibitors (Figure 9), respectively, which
idues Gly22 and Gln90, while interacting via hydrophobic were similar to those reported previously (Kwofie et al., 2021).
interactions with Leu50, Glu48, Tyr21, Trp53, Ala134, Ser135,
Phe93, Phe139 and Arg130. From our study, Ala134 is also 3.8.1. Per-residue energy decomposition of VZV thymidine
predicted as likely to be a novel critical residue involved in kinase-ligand complexes
the activity of the protein since it formed intermolecular MM-PBSA was carried out on the complexes of the three
bonds with all the potential lead compounds, as well as the potential leads and two known inhibitors. Per-residue energy
known drugs and the co-crystallized BVDU-MP. decomposition of VZV TK-ligand enables the calculation of
JOURNAL OF BIOMOLECULAR STRUCTURE AND DYNAMICS 11
Table 6. Prediction of the biological activities of potential lead compounds using PASS determined with Probable activity (Pa) and
Probable inactivity (Pi).
Ligand Activity Probable activity (Pa) Probable inactivity (Pi)
Antiviral 0.309 0.033
Antiviral (Hepatitis B) 0.490 0.005
Antiviral (Herpes) 0.552 0.006
Apigenin-40-Glucoside Antiviral (Influenza) 0.730 0.004
Antiviral (Picornavirus) 0.301 0.226
DNA ligase (ATP) inhibitor 0.656 0.002
DNA polymerase I inhibitor 0.395 0.021
DNA repair enzyme inhibitor 0.319 0.004
DNA synthesis inhibitor 0.502 0.018
Antiviral (Hepatitis B) 0.384 0.017
Abyssinone V Antiviral (Herpes) 0.504 0.009
Antiviral (Influenza) 0.575 0.015
Antiviral (Rhinovirus) 0.590 0.007
DNA ligase (ATP) inhibitor 0.328 0.035
Antiviral 0.334 0.026
Myricetin Antiviral (Hepatitis B) 0.519 0.004
Antiviral (Herpes) 0.500 0.010
Antiviral (Influenza) 0.444 0.034
DNA ligase (ATP) inhibitor 0.564 0.004
Table 7. Ligand names, PubChem CIB, 2-Dimensional and 3-Dimensional structures of potential lead compounds predicted.
Ligand Pubchem CID 2_Dimensional structure 3_Dimensional sturcture
Myrecitin 5281672
Apigenin-40-Glucoside 5491384
Abyssinone V 6548074
energy contribution for each residue. Residues contributing Glu48(8.4539 kJ/mol) were immensely involved in contributing
binding free energy greater than 5 kJ/mol or less than 
5 kJ/ to the free binding energy of the complex (Figure 10).
mol are considered as critical for binding of a ligand to a pro- Hydrogen bond forming residues Gly22 (
0.7751) and Gln90
tein (Kwofie, Dankwa, et al., 2019). For the VZV TK-myricetin (
0.1436) did not contribute significantly. For the complex
complex, hydrophobic residues Tyr21 (
7.5619 kJ/mol) and VZV-TK-abyssinone V, the critical active site residues that
12 S. K. KWOFIE ET AL.
Figure 7. RMSD trajectories of the complexes calculated for the 100 ns simula-
tion timescale. Graphs are represented in different colors with black, red, green,
blue and yellow legend representing BVDU-MP, apigenin-4’-glucoside, abyssi-
none V, myricetin and known drug (acyclovir), respectively.
Figure 9. Radius of Gyration trajectories of the complexes computed for the
100 ns simulation timescale. Graphs are represented in different colors with
black, red, green, blue and yellow legend representing BVDU-MP, apigenin-4’-
glucoside, abyssinone V, myricetin and known drug (acyclovir), respectively.
Gly22 and Tyr66 formed hydrogen bonds with those which
also formed hydrophobic contacts. Identified critical active site
residues contributing significant free binding energy included
Try21, Gly22, Glu48, Trp53, Tyr66, Phe93 and Ser135.
3.8.2. Other energy terms
Van der Waals forces, electrostatic and polar solvation ener-
gies were useful in estimating the free binding energy of the
complex. The van der Waals refers to the weak attraction
existing between the intermolecular forces (Geesink & Meijer,
2021). The van der Waals energy observed in our study
Figure 8. RMSF trajectories of the complexes computed for 100 ns simulation ranged between 
165.737 kJ/mol and 
256.232 kJ/mol with
timescale. Graphs are represented in different colors with black, red, green, 0
blue and yellow legend representing BVDU-MP, apigenin-4’-glucoside, abyssi- apigenin-4 -glucoside having the least van der Waals energy
none V, myricetin and known drug (acyclovir), respectively. of 
256.232 kJ/mol among the potential lead molecules,
while myricetin exhibited the highest energy of 
165.737 kJ/
contributed to the free binding energy was observed to be mol (Table 8). Meanwhile, abyssinone V had van der Waals
Trp53 (
12.7773 kJ/mol), Phe93 (
14.973 kJ/mol) and Ser135 energy of 
206.928 kJ/mol. Among the known inhibitors,
(7.7566 kJ/mol), all of which formed hydrophobic interaction BVDU-MP and acyclovir close der Waals energy of
with the ligand. (Supplementary Figure S1). For the complex 
134.824 kJ/mol and 
135.341 kJ/mol, respectively.
VZV TK-apigenin-40-glucoside, Tyr21 (
10.1107 kJ/mol), Trp53 Electrostatic energy refers to the potential energy of a sys-
(
7.6053 kJ/mol), Phe93 (
12.7869 kJ/mol), Ser135 tem consisting of different electric charges (Tort, 2013).
(
9.7755 kJ/mol), could be considered as the critical residues Electrostatic energy was observed between 
41.863 kJ/mol
that contributed immensely towards the binding energy of the and 
305.504 kJ/mol (Table 8). Among the potential lead
complex (Supplementary Figure S2). For acyclovir-VZV TK com- compounds, myricetin showed the least electrostatic energy
plex, residues Tyr21 (
6.7216 kJ/mol), Glu48 (7.5788 kJ/mol) of 
84.341 kJ/mol, followed by apigenin-40-glucoside with
and Tyr66 (
5.772 kJ/mol) were observed to interact with the 
58.034 kJ/mol, and then abyssinone with 
52.967 kJ/mol.
ligand from the docking analysis was corroborated after MM- For the known inhibitors, BVDU-MP had the least electro-
PBSA (Supplementary Figure S3). For the co-crystallized ligand static energy of 
305.504 kJ/mol whilst acyclovir had
BVDU-MP in complex with VZV-TK, Tyr21 (
10.9787 kJ/mol) 
41.863 kJ/mol. Polar solvation energy also represents the
and Glu48 (101.4915 kJ/mol) Tyr66 (
8.9697 kJ/mol) Phe93 electrostatic interaction that exists between the solute and
(
13.3358 kJ/mol) Ser135 (
55.7476 kJ/mol) contributed sig- the continuum solvent (Genheden & Ryde, 2015). The polar
nificant energies (Supplementary Figure S4). The residues solvation energy was between 113.934 kJ/mol and
JOURNAL OF BIOMOLECULAR STRUCTURE AND DYNAMICS 13
Figure 10. MM-PBSA plot of the binding free energy decomposition contribution per residue of VZV thymidine kinase-myricetin complex. Coded red lines repre-
sent surrounding active site amino acid residues.
Table 8. Energy component terms of the VZV thymidine kinase-ligand complexes calculated using MM-PBSA. The values are reported in average ± standard
deviation in kJ/mol.
Solvent accessible
van der Waals energy Electrostatic energy Polar solvation energy surface area (SASA)
Compounds (kJ/mol) (kJ/mol) (kJ/mol) energy (kJ/mol) Binding energy (kJ/mol)
Myricetin 
165.737 ± 16.432 
84.341 ± 20.423 160.018 ± 24.013 
14.445 ± 0.901 
104.505 ± 24.308
Apigenin-40-Glucoside 
256.232 ± 23.993 
58.034 ± 25.530 163.804 ± 35.412 
20.080 ± 1.309 
170.543 ± 28.435
Abyssinone V 
206.928 ± 17.607 
52.967 ± 20.513 150.983 ± 25.246 
18.762 ± 1.224 
127.673 ± 21.786
Acyclovir 
135.341 ± 13.993 
41.863 ± 18.458 113.934 ± 32.252 
13.152 ± 1.004 
76.422 ± 22.551
BVDU-MP 
134.824 ± 18.030 
305.504 ± 77.852 838.082 ± 59.272 
16.905 ± 0.724 380.850 ± 38.693
838.082 kJ/mol, and acyclovir had the least polar solvation Khan et al., 2020; Sang et al., 2021). This corroborate the pre-
energy of 113.934 kJ/mol. Abyssinone V, myricetin, apigenin- dictions made with PASS in the earlier addressed PASS
40-glucoside and BVDU-MP had polar solvation energies of results. Myricetin has been investigated act to reduce ATPase
150.983, 160.018, 163.804 and 838.082 kJ/mol, respectively. activity by inhibiting the nonstructural protein 13 (nsp13) of
Furthermore, Solvent Accessible Surface Area (SASA) coronaviruses (Yu et al., 2012). Also, it has been investigated
energy represents the non-polar solvation energy (Genheden in vitro to have potential activity against the Herpesviridae
& Ryde, 2015). This energy measures the interactions that family of viruses (Li et al., 2020), of which the varicella-zoster
exist between the complex and the solvents. The SASA ener- virus is a member. It has the ability to block the Herpes
gies obtained were 
13.152 kJ/mol, 
14.445 kJ/mol, Simplex Virus (HSV) I and II by directly interacting with the

16.905 kJ/mol, 
18.762 kJ/mol and 
20.080 kJ/mol for glycoprotein D (gD), a structural component of this family of
acyclovir, myricetin, BVDU-MP, abyssinone V and apigenin-40- viruses (Li et al., 2020). This activity interferes in the absorp-
glucoside, respectively (Table 8). tion as well as the membrane fusion of the virus, thereby
Acyclovir demonstrated the highest binding affinity with a inhibiting its replication (Li et al., 2020). Further investiga-
binding free energy of 
76.422 kJ/mol. This was followed by tions in vitro can therefore be carried out to corroborate the
myricetin, abyssinone V, apigenin-40-glucoside, and BVDU-MP predicted ability of myricetin to inhibit the activity of the
with binding free energies of 
104.505, 
127.673, 
170.54 varicella-zoster virus. Apigenin, a derivative of Apigenin-40-
and 380.850 kJ/mol, respectively (Table 8). The low binding Glucoside is a constituent in the genus Nepeta, and these
free energies exhibited by these compounds demonstrate plants have been extensively used for treating chicken pox
their propensity to be potential inhibitory molecules of VZV (Sharma et al., 2021). By increasing the membrane permeabil-
TK worthy of in vitro and in vivo studies. ity of protein, disrupting and depolarizing cell membrane
integrity, reducing the activity of enzymes bound to mem-
brane as well as inducing apoptosis, this genus of plants are
3.9. Exploring known mechanism of action and
able to exhibit cytotoxic effects, thereby impairing viral
biological activity of predicted leads
growth and subsequent replication (Sharma et al., 2021).
All three molecules identified in our study have been Abyssinone V, has also been reported to inhibit pneumococ-
reported to have antiviral activities (Grienke et al., 2016; cal neuraminidase (NA), a critical target for influenza with
14 S. K. KWOFIE ET AL.
IC50 ¼ 2.18 lM, and pneumococcal growth with MIC ¼ References
5.63lM, without causing any disadvantage to the lung epi-
Abo Almaali, H. (2018). Molecular docking of some peptides to varicella
thelial cells (Grienke et al., 2016). It is therefore imperative zoster virus drug targets. Albahir Journal, 7, 13–14.
and worth investigating these potential therapeutic mole- Ajiboye, T. (2015). Standardized extract of Vitex doniana Sweet stalls pro-
cules, since they can be of great relevance to the treatment tein oxidation, lipid peroxidation and DNA fragmention in acetamino-
of the chicken pox infection. phen-induced hepatotoxicity. Journal of Ethnopharmacology, 164,
273–282. https://doi.org/10.1016/j.jep.2015.01.026
Al-Khafaji, K., Al-Duhaidahawi, D., & Taskin Tok, T. (2020). Using inte-
4. Conclusion grated computational approaches to identify safe and rapid treatmentfor SARS-CoV-2. Journal of Biomolecular Structure and Dynamics, 39(9),
The study identified 3 potential lead compounds comprising 1–9. https://doi.org/10.1080/07391102.2020.1764392
0 Alves, M. J., Froufe, H. J. C., Costa, A. F. T., Santos, A. F., Oliveira, L. G.,myricetin, apigenin-4 -glucoside and abyssinone V out of a Osorio, S. R. M., Abreu, R. M. V., Pintado, M., & Ferreira, I. C. F. R.
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