Abstract
Plant-derived antioxidants are a large group of natural products with
the capacity to reduce radical-scavenging. Due to their potent
therapeutic and preventive actions, these compounds receive a lot of
attention from scientists, particularly pharmacologists. The
pharmacological activities of the Azima tetracantha Lam. (AT) plant,
belonging to the Salvadoraceae family, reported here justifies its
traditional use in treating several diseases or disorders. This study
aims to look at the propensity of certain plant compounds found in
natural AT plant extracts that might play a critical role as a
secondary metabolite in cervical cancer treatment. There is a shortage
of information on the plant’s phytochemical and biological
characteristics. Methanol (MeOH) solvent extracts of the dried AT plant
were screened phytochemically. Its aqueous extract was tested for
antioxidant, antiseptic, anti-inflammatory, and anticancerous
properties. Absorption Distribution Metabolism and Excretion (ADME/T),
Docking, and HPLC were also performed. In clinical treatment, the plant
shown no adverse effects. The antioxidant activity was evaluated and
showed the highest concentration at 150 µg/mL (63.50%). MeOH leaf
extract of AT exhibited the highest and best inhibitory activity
against Staphylococcus aureus (15.3 mm/1000) and displayed a high
antiseptic potential. At a 200 µg/mL concentration, MeOH leaves-extract
inhibited red blood cells (RBC) hemolysis by 66.56 ± 0.40, compared
with 62.33 ± 0.40 from the standard. Albumin’s ability to suppress
protein denaturation ranged from 16.75 ± 0.65 to 62.35 ± 0.20
inhibitions in this test, providing even more support for its favorable
anti-inflammatory properties. The ADME/T studies were considered for a
potential cancer drug molecule, and one of our compounds from MeOH
extract fills the ADME and toxicity parameters. The forms of compound 4
showed a strong hydrogen-bonding interaction with the vital amino acids
(ASN923, THR410, LEU840TRY927, PHE921, and GLY922). A total of 90% of
cell inhibition was observed when HeLa cell lines were treated with 300
µg/mL of compound 4 (7-acetyl-3a^1-methyl-
4,14-dioxo-1,2,3a,3a^1,4,5,5a,6,8a,9b,10,11,11a-tetradecahydro-2,5a
epoxy5,6a
(methanooxymethano)phenaleno[1′,9′:5,6,7]indeno[1,7a-b]oxiren-2-yl
acetate). The polyphenol compounds demonstrated significant advances in
anticancer drug properties, and it could lead to activation of cancer
cell apoptosis.
Keywords: antiseptic, antioxidant, anti-proliferative,
anti-inflammatory, docking, hela, polyphenol, phytomolecules
1. Introduction
Naturally, there is a dynamic balance between the number of free
radicals produced in the body and the antioxidants to scavenge or
quench them for the body’s protection against harmful effects [[42]1].
Antioxidant components in plants are derived from constituent nutrients
with a proven radical-scavenging property. Thus, plant-based
medications may include flavonoids, polyphenols, and flavoproteins, in
addition to alpha-tocopherol, ascorbate, carotenoids, and zinc.
Additionally, some plants or combinations of herbs may function as
antioxidants by scavenging superoxide or boosting superoxide dismutase
activity at different tissue regions [[43]2]. Bacteriological
infections are widespread in immuno-cooperated patients with the
substantial expense of care and can be lethal. The increasing
percentage of infectious rehabilitation of clinical agents and their
effect on managing contagious diseases have started to present an
extraordinary health challenge [[44]3]. The possibility of pandemic
disease increases the risk of medicinal resistivity for highly
drug-resistant invasive bacterial pathogens. The reality is that many
antiseptic agents are often produced through differing pathways and may
produce transmutations that cause the resistance. Staphylococcus aureus
is the most commonly occurring methicillin-resistant impurity formed by
clinical microorganisms. The development of bacterial confrontations
with antimicrobial agents explains the quest to seek new antimicrobials
therapy [[45]4].
In recent decades, cancer was believed to be associated with
inflammation. This impression has been waning for a lengthy period.
However, recent years have witnessed a resurgence of interest in the
inflammation–cancer link, fueled by many lines of research and
culminating in a widely recognized paradigm [[46]5,[47]6]. In recent
times, several studies have highlighted the importance of swelling in
tumor conditions. The intact macrophage cells are responsible for
recognizing and eliminating infectious pathogen and apoptotic cells by
synthesizing various bio-active pro-inflammatory mediators that monitor
constant microbe invasion and unusual reactive oxygen species (ROS)
development. Recurrent pro-inflammatory moderators at the injured
tissue area resulted in the irregular or dysfunctional activation of
inflammations. It is worth noting that irregular pro-inflammatory
mediator secretions are primarily for tissue injuries, the
transformation of the cell, and cancer [[48]7]. The positive control of
deregulated inflammatory pathways is aided by the repression of
increased ROS production, pro-inflammatory mediators, and
anti-inflammatory mediator secretion [[49]8]. Compounds with a solid
propensity to function as antioxidants and anti-inflammatory factors
provide further benefits; in other words, an overabundance of
inflammatory response will favor irregular ROS formation and cellular
transition. Thus, phytoconstituents with multi-therapeutic properties
in chronic diseases, including inflammation and cancer, play a vital
role [[50]9]. These phytoconstituents have multi-step action without
side effects because the plant produces them as a normal response
(secondary metabolite). Indeed, the previous report suggests the
naturalistic phytoconstituents are successful in fighting against
cancer [[51]10].
Cancer is an uncontrolled growth of uncharacteristic cells, which can
spread and appear in different body tissues, and sometimes if
unnoticed, may cause mortality. It is a major problem disturbing
people’s health worldwide [[52]11]. Tumor cells perpetuate the
disparate normal cells that use specific switches for controlling
cellular growth and proliferation. Thus, identifying cancer cells
targets, active sites, and revealing the target-lead interactions is
vital for scheming new and effective therapeutics for tumors.
In the 21st century, the flare-up of diseases and discovery of
protecting agents that deal via recognized, proposal, amalgamation, and
resulting clinical trials poses actual challenges. In the past, drug
design entailed a single or a few biological entities to curtail the
study time and achieve high specificity and selectivity to avoid side
effects arising from mistargeting [[53]12,[54]13]. Fortunately,
computer-aided design and drafting (CADD) systems and recent
state-of-the-art systematical tools have proven to be very beneficial
for quickly judging the active molecules and extensive organic records
[[55]14,[56]15]. These systems accelerate the precise identification of
hopeful applicants before the start of any extensive chemical
synthesis, biological testing (in vivo or in vitro), and clinical
trials. Furthermore, it reduces cost and time [[57]16,[58]17]. The role
of systematic tools in pharmacodynamics and pharmacokinetics is vital
for the success of drug development. It cannot be ignored because
properties such as solubility, hydrophobic effect, bioavailability,
absorption, metabolism, and toxicity of the lead compounds are the
parameters used to decide how good and safe the drugs are
[[59]18,[60]19]. AT has been traditionally used for many diseases,
including renal disease. It belongs to the Salvadoraceae family and is
known as mulchangu in Siddha and kundali in Ayurveda [[61]20]. The
present investigation aims to design and screen molecules of five
derivatives as a potential multi-target drug against cancer
pharmacokinetics. In this study, we have used a natural antioxidant
therapeutic agent, Azima tetracantha extract, that displays potential
antiseptic and anticancerous properties. In addition, we believe that
the target drugs screened herein could be potential therapeutics for
bacterial infection and cervical cancer treatment.
2. Materials and Methods
2.1. Plant Material Collection and Extraction
The Azima tetracantha Lam. was obtained from Athamangalam, Nagapattinam
Distt, Tamilnadu, India, from August to September 2018. The herbarium
was maintained in the Department of Botany, Annamalai University (Plant
authentication number AUBOT 262). One hundred grams of crushed leaf
materials were extracted in a soxhlet apparatus for 8 h with solvent
MeOH (99.35%, Sigma Aldrich, Bangalore, India). Later the extracts were
sieved, and the solvent was evaporated by a rotatory evaporator
(Heidolph, Germany) under a concentrated temperature at 40 °C, and the
extracts were kept at 4 °C for further examination.
2.2. DPPH Radical-Scavenging Assay
Antioxidants scavenge the 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical
by donating a proton, forming the reduced DPPH, and were evaluated by
using the methodology [[62]21]. Various concentrations (50, 75, 100,
and 150 µg/mL) of the sample (4.0 mL) were mixed with 1.0 mL of a
solution containing the DPPH radical (Sigma Aldrich, Bangalore, India),
resulting in the final concentration of DPPH being 0.2 mM. The mixture
was shaken vigorously and left to stand for 30 min, and the absorbance
was measured at 517 nm. Ascorbic acid (20% Sigma Aldrich, Bangalore,
India) was used as a positive control.
2.3. Evaluation of Antiseptic Properties
The antiseptic properties of methanol extract were tested against seven
clinical bacterial strains (Gram + Ve: S. aureus, B. cereus, B.
subtillis, and Gram-Ve: S. typhi, K. pneumoniae, E. coli). Bacteria
were grown in a pure culture on a Luria broth medium. Using a cotton
swab, the bacterial strains were placed onto agar plates. Next, the
leaf extract was sprayed onto sterile discs with deionized
chloramphenicol (Sigma Aldrich 98%, Bangalore, India), which serves as
a positive control. The plates were then incubated overnight (35 °C)
before being weighed on a standard scale [[63]22].
2.4. Inhibition of Albumin Denaturation
In this procedure, an inhibitor of the albumin denaturation strategy
was adapted with minor changes [[64]23]. A 0.05 mL of distilled water
and 0.45 mL of bovine serum albumin (5% aqueous solution, Sigma
Aldrich, Bangalore, India) were used to make the reaction blend (0.5
mL; pH 6.3). A minimal volume of 1 N HCl (36% HiMedia, Mumbai, India)
was used to adjust the pH to 6.3. Various plant extract concentrations
were added to the reactants and incubated at 37 °C for 20 min before
being heated at 7 °C for 5 min. After cooling the samples, 2.5 mL of
phosphate buffer (Sigma Aldrich, Bangalore, India) saline was added. At
600 nm, turbidity was calculated spectrophotometrically.
[MATH:
Percentage Inhibition
(%)=
AbsControl-AbsSample
AbsControl×100 :MATH]
(1)
2.5. HRBC Membrane Stabilization Method
Blood (2 mL) was obtained from healthy volunteers (From Rajamuthaia
Medical college, Chidambaram, India on 20 July 2020) and diluted with
an equivalent amount of sterile Alsevers solution (2% dextrose, 0.8%
sodium citrate, 0.5 % citric acid, and 0.42% NaCl in purified water;
HiMedia, Mumbai, India) and centrifuged at 3000 rpm. The loaded cells
were cleaned with a saline solution and stored undisturbed at 4 °C in
the 10% v/v saline. Various herbal extracts (62.5, 125, 250, 500 mg/mL)
and Aspirin (as a regular and positive control agent, distilled water
used rather than hypo saline to achieve 100% hemolysis) were added then
combined with 2 mL of hyposaline, 1 mL of phosphate buffer, and 0.5 mL
of 10% HRBC suspension (Sigma Aldrich, Bangalore, India). The blends
were incubated at 37 °C for 30 min, and then centrifugation for 20 min
at 3000 rpm, and the supernatant hemoglobin solution was analyzed
spectrophotometrically at 560 nm [[65]24].
[MATH:
Stabilization (<
mo>%)=AbsControl-AbsSampleAbsControl<
/mrow>×100 :MATH]
(2)
2.6. HPLC Analysis
2.6.1. Extraction Solvent
A mixture of alcohol, water, and hydrochloric acid (50:20:8) was
prepared. Subsequently, a methanol, water, and phosphoric acid
(100:100:1) mixture was prepared for the mobile phase.
2.6.2. Standard Solutions
Accurately weighed quantities of Rutin (94%, Sigma Aldrich, Bangalore,
India) were transferred to separate volumetric flasks. Each was
dissolved quantitatively with MeOH to obtain a standard solution of 1
mg per mL, respectively.
2.6.3. Test Solution
About 10.0 g of the given sample was finely powdered, accurately
weighed, and transferred to a 250 mL flask fitted with a reflux
condenser. Next, 78 mL of extraction solvent were added and refluxed on
a hot water bath for 135 min after cooling at room temperature and
transferred to a 100 mL volumetric flask. Finally, 20 mL of MeOH was
added to the 250 mL flask and sonicated for 30 min. After filtration,
the filtrate was collected in a 100 mL volumetric flask. The residue on
the filter was washed with MeOH, and it is collected in the same 100 mL
volumetric flask.
2.6.4. Chromatographic System and Procedure
The liquid chromatography is equipped with a 270 nm detector and a
4.6-mm × 25-cm L1 Octadecyl silane column. The flow rate is about 1.5
mL per minute. Standard solution 1 was chromatographed, and the peak
responses were recorded. About 20 µL of the standard solutions with an
equal volume of test solution were injected into the chromatograph
separately. Chromatograms were recorded for the measurement of the
areas for the major peaks.
2.7. GC-MS Analysis
Gas chromatography-mass spectrometry (GC-MS) was performed on an Azima
tetracantha MeOH sample (“JEOL GCMATE II GC-MS-Agilent 6890 N Network
GC” system). Two milliliters of active fractions were dissolved in HPLC
grade MeOH (Sigma Aldrich, Bangalore, India) before being exposed to MS
and GC on a JEOL GC mate fitted with the secondary electron multiplier.
The column (HP5) was made of fused silica and had a 50 mm_0.25 mm I.D.
The experiment lasted 20 min at 100 °C. The temperatures of the column
and injector were fixed to 235 and 240 °C, respectively. Helium was
used as the carrier gas in this protocol, with a split ratio of 5:4. In
a splitless injector, a sample volume was evaporated with 2 mL. The run
time was 22 min at 300 °C, and the detection of the compound was
accomplished using GC combined with mass spectrometry. An established
specification was run concurrently for reference. The test fraction’s
molecular weight, mathematical formula, compound composition, and peak
area were quantified by comparing them to established compounds in the
spectral library (NIST 05).
2.8. Computational Analysis
2.8.1. Drug-Likeness Studies
All the molecules studied were analyzed in silico for their molecular
properties and drug-likeness limits. It was constructed using
hypothetical approaches with the aim of identifying molecules that meet
the ideal criteria for exhibiting as drug-like molecules as described
by Lipinski’s rule of five [[66]25], and other physicochemical
parameters were considered using the Biovia DS vs. 4.5 software module
“Calculation of Molecular Properties”. Additionally, specific
properties were predicted using open web-based resources, such as
Molsoft ([67]http://www.molsoft.com/, accessed on 15 February 2021) and
the computer app Molinspiration.
2.8.2. Swiss ADME/Toxicity
ADME (Absorption, Distribution, Metabolism, Excretion) and Toxicity of
the calculated compounds were predicted along with a massive database
on the swiss ADME/T web server ([68]http://www.swissadme.ch/, accessed
on 16 February 2021), and the server can hypothesize high-precision
therapeutic and medicinal properties [[69]26].
2.8.3. Molecular Docking
The construction of the compounds and proteins was prepared as per the
prearrangement. Auto Dock vina 4.2 was selected for docking studies by
the standard procedure [[70]27]. The amalgams originated were
established into a 3D model. A 2D display of the target compounds was
performed to verify their structures and the formal charges of their
atoms. Then, the energy minimization was extended to all conformers.
The minimization processes were carried out until a 0.01 kcal mol 1
root mean square deviation (RMSD) gradient and the 0.1 AR MMFF94X force
field distance were reached. Then, the partial expenditures were
determined automatically. The database was saved as MDB- (Mongo,
Database) for further docking calculations.
2.8.4. Enrichment and Network Analysis
STRING ([71]https://string-db.org, accessed on 12 August 2021) was used
to search the list of possible targets [[72]28]. A database was created
for organic evolution, molecular role, and cellular mechanisms, and a
protein interaction enrichment study was conducted. Further, the
potentially moderated pathways were indented in relation to the KEGG
pathway record. The network between plants, their phytoconstituents,
changed proteins, and organized pathways were hypothesized. The network
was viewed as oriented, and the node size was set to “low values to
tiny sizes,” node color was set to “low values to bright colors,” and
the whole structure was examined using edge count.
2.9. Cell Line
The HeLa cervical cancer cell lines were collected from the “National
Centre for Cell Science” (NCCS) Pune, India. The HeLa cell lines were
cultured in “Dulbecco’s Modified Eagle’s Medium” (DMEM) supplemented
with 10% fetal bovine serum (Sigma Aldrich, Bangalore, India) (FBS) and
antimycotic and antibiotic reagent (1%) at 37 °C in the presence of 5%
moistened CO[2].
2.10. Cell Viability Assay by Enzyme-Linked Immunosorbent
The cell viability was evaluated using the 3-(4,
5-dimethylthiazol-2-yl) -2,5-diphenyl tetrazolium bromide (MTT, Sigma
Aldrich, Bangalore, India) assay. Briefly, HeLa cells in the log phase
at a concentration of 1.0 × 10^4/well were cultured in 96-well plates
and incubated in 5% CO[2] at 37 °C for 24 h. Throughout the
cultivation, the cells were constantly treated by the addition of MeOH
at varying concentrations (18.75, 37.5, 75, 150, and 300 g/mL). The
control group was kept under the same conditions with 0.1%
dimethyl-sulfoxide (DMSO, Sigma-Aldrich, Bangalore, India). After
incubation for 24 h, 10 µL of 5 mg/mL MTT was added to each well and
incubated for an additional 4 h. Then, the supernatant was discarded,
and 100 µL of DMSO was added to each well, and the 96-well plates were
vortexed for 10 min. An enzyme-linked immunosorbent assay (ELISA)
reader was used to record the optical density (OD, Sky technology,
Ahmedabad, Gujarat, India) at 570 nm.
2.11. Statistical Analysis
The experiments were carried out three times. The findings were
analyzed by SD, mean assays, and they were subjected to One-Way ANOVA,
Dunnett’s multiple evaluation experiments, and PRISM program version
5.2. (Graph Pad Software Inc, San Diego, California, USA).
3. Results
3.1. Azima Tetracantha Exhibits Antioxidant Properties
The antioxidant activity of Azima tetracantha was determined by its
DPPH free-radical-scavenging ability. The DPPH radical-scavenging
activity of MeOH leaf extract was evaluated and compared with positive
control ascorbic acid. The percentage of inhibition (% inhibition
measured at various concentrations as (50, 75, 100, and 150 µg/mL) of
the sample as well as standard were measured ([73]Figure 1). The
highest concentration was found at 150 µg/mL (63.50%), which was
followed by 50 µg/mL (22.11%) as sample inhibition values, and the
highest concentration of standard was 50 µg/mL (68.35%) and the lowest
was 50 µg/mL (26.50%). Polyphenolic compounds are considered to be very
important plant constituents that are responsible for free
radical-scavenging ability owing to their hydroxyl groups.
Figure 1.
[74]Figure 1
[75]Open in a new tab
DPPH radical-scavenging ability of methanol extract of Azima
tetracntha. The values are Mean ± SD. One-way ANOVA was used to analyze
the significant difference among groups. The symbol (***) indicate the
significant difference (p < 0.001).
3.2. Antiseptic Properties of Azima Tetracantha
The antiseptic properties of MeOH of the leaf of Azima tetracantha
against bacterial pathogens and results are presented in ([76]Table 1).
Table 1.
Antibacterial activities of MeOH leaf extract from the AT (500
µg/disc).
Mean Zone of Inhibition ^a (mm) ^b
S. No Microorganism Methanol Extract (MeOH)
500 µg/Disc
1 Staphylococcus aureus 15.3 ± 0.15
2 Bacillus cereus 11.4 ± 0.20
3 Bacillus subtilis 11.1 ± 0.10
4 Escherichiacoli 8.2 ± 0.05
5 Klebsiellapneumonia 10.0 ± 0.00
6 Salmonella typhi 10.0 ± 0.11
[77]Open in a new tab
^a—diameter of zone of inhibition (mm) including disc diameter of 6 mm,
^b—mean of three assays; ± standard deviation; Ciprofloxacin (5
µg/disc)—antibacterial drug between 19 and 23 mm; Ketoconazole (10
µg/disc)—antifungal drug between 13 and 14 mm.
The minimum zones of inhibition for MeOH ranged from 8.2 to 15.3 mm.
The methanol extract of the AT leaf exhibited the highest and best
inhibitory activity against Staphylococcus aureus (15.3 mm/500 µg/disc)
([78]Figure 2). Thus, the screenings of AT medicinal plants indicate
their antibacterial properties.
Figure 2.
[79]Figure 2
[80]Open in a new tab
Antiseptic activity is indicated as a zone of inhibition by MeOH leaf
extract of Azima tetracantha Lam. Numbers in the Petri dish are as
follow: (1) 500, (2) 125, (3) 50 µg/disc, (4) negative control DMSO,
and (5) positive control chloramphenicol.
3.3. In Vitro Anti-Inflammatory Activity
3.3.1. Inhibition of Albumin Denaturation
The effects of anti-inflammatory behavior assessed towards the
denaturation of egg albumin are outlined ([81]Figure 3A). This figure
describes the observations of in vitro flow cytometry of the
anti-inflammatory properties assessed against the denaturation of egg
albumin. At a concentration of 200 μg/mL, the highest inhibition
obtained was 67.20 ± 0.10. Aspirin used as a standard drug showed a
60.69 ± 0.10 inhibition at a 200 μg/mL concentration. In addition, the
results of the anti-inflammatory examination for the human red blood
cell membrane were revealed. The AT MeOH extract produced a 62.56 ±
0.40 inhibition of RBC hemolysis at a 200 μg/mL concentration, compared
with 62.33 ± 0.40 produced as standard by the standard drug Aspirin
([82]Figure 3B). From the data, it can be concluded that MeOH leaf
extract of AT showed a greater response than Aspirin.
Figure 3.
[83]Figure 3
[84]Open in a new tab
Anti-inflammatory activity of Azima tetracantha. (A) Protein
denaturation by using egg albumin. (B) Human red blood cell (HRBC)
membrane stabilization of assay. Aspirin is used as a standard drug.
3.3.2. GC-MS Analysis of Azima tetracantha
The findings of GC-MS analysis of AT MeOH extract led to the
identification of a number of chemicals. Five major peak compounds
(3,4-Dimethyl-5-oxo-2,5-dihydro-1H-
pyrrol-2-yl)-[4,4-dimethyl-5-[2,3,3-trimethyl-5-methylthio-3,4-dihydro-
2H-pyrrolyl methylene] pyrrolidin-2-ylene] -thioacetic acid,
S-[tert-butyl] ester (12.15%), 1H-Inden-
1-one,2,3-dihydro-5,6-dimethoxy-3-methyl (12.65%),
5-(p-Aminophenyl)-4-(O-tolyl)-2- thiazolamine (14.27%),
92-(3-acetoxy-4,4,10,13,14 pentamethyl
2,3,4,5,6,7,10,11,12,13,14,15,16,17-tetradecahydro-1H-cyclopenta[a]phen
anthren-17-yl) propanoic acid (16.05%), and
3,9a;14,15-Diepoxypregen-16-en-20-one,3,11a;18-triacetoxy (23.24%) were
present in the MeOH extracts of AT. The existence of multiple
components with varying retention periods was verified by the GC-MS
spectra ([85]Figure S1). The mass spectrometer examines the chemicals
eluted at various intervals to determine their type and structure. The
big compound breaks into tiny compounds, causing peaks with various m/z
ratios to emerge. These mass spectra represent the compound’s
fingerprint, which may be recognized using the data library.
3.3.3. High-Performance Liquid Chromatography Analysis
HPLC analysis of the MeOH leaf extract of AT showed that several peaks
correspond to flavonoids at 650 nm. The flavonoid presence was
validated by contrasting the samples’ retention period to the Rutin and
comparing Rutin’s resulting peak heights in the methanol extract
([86]Figure S2). The sample chromatograms revealed many peaks that did
not correlate to the flavonoid criteria we used, mainly at retention
times ranging from 2.071 to 8.814 min. These peaks may be flavonoid
peaks. The ascorbic acid, gallic acid, and resorcinol found in the
extract will act synergistically in metabolizing the biological
activities. Polyphenol compounds have made significant advances in
anticancer drug production, with the ability to kill cancer cells by
inducing apoptosis.
3.3.4. Scrutiny of Pharmacokinetic Properties
The lead molecules, which may be a potential inhibitor, should have
desirable pharmacokinetics to pass initial clinical trials. Thus, the
first screening of the lead molecules was performed based on their
physicochemical or ADME/T properties. All of the five derivatives
passed this test. The five derivatives ([87]Table 2, [88]Table 3 and
[89]Table 4) present that the lead molecules with physicochemical and
pharmacokinetic properties only have high scores against the five
targets and active molecules.
Table 2.
ADMET and physicochemical properties of the title compounds.
S.
No Formula MW Aromatic
Heavy
Atoms Rotatable
Bonds H-Bond
Acceptors H-Bond
Donors TPSA XLOGP
3 Ali
Log
S Ali
Class BBB CYP1A2
Inhibitor CYP2C19
Inhibitor CYP2C9
Inhibitor CYP2D6
Inhibitor CYP3A4
Inhibitor Bioavailability SA
1 C27H41N3O2S2 503.76 6 12 3 2 112.04 5.52 −7.63 Soluble No No Yes No
Yes Yes 0.55 5.07
2 C16H15N3S 281.38 15 2 2 0 57.89 4 −4.92 M.
soluble Yes Yes Yes Yes No No 0.55 3.11
3 C27H42O4 430.62 0 0 4 1 55.76 4.83 −5.73 M.
soluble Yes No No No No No 0.55 6.7
4 C12H14O3 206.24 6 2 3 0 35.53 1.96 −2.33 Soluble Yes Yes No No No No
0.55 1.99
5 C26H28O8 468.5 5 1 8 2 123.27 0.67 −2.84 Soluble No No No No No No
0.55 5.92
[90]Open in a new tab
MV= 150–500 g m/mol, TPSA (total polar surface area) = 20 A^2–130 A^2,
H-A = no. Of H-bond acceptors ≤ 10, H-D = no. of H- bond donor ≤ 5,
Rotatable bonds = 0–9, Log S = 0–6, In saturation +0.25–1, no. atoms
(number of atoms) = 20–70.
Table 3.
Shortlisted compounds with their drug parameters and toxicity report.
S. No. Formula MW Avian
Toxicity Biodegradation Crustacea
Aquatic
Toxicity Fish Aquatic Toxicity Honey Bee
Toxicity Tetrahymena Pyriformis Human
Intestinal
Absorption
1 C27H41N3O2S2 503.76 − + iii − − 1.18606 +
2 C16H15N3S 281.38 − + iii + − 1.0123 +
3 C27H42O4 430.62 − − iii − − 0.50823 +
4 C12H14O3 206.24 − − iii + − 0.85124 +
5 C26H28O8 468.5 − + i + − 1.7517 +
[91]Open in a new tab
The remaining parameters of Lipinski’s rule, namely the “number of
hydrogen bond acceptors” (NHA), number of hydrogen bond donors, and
“number of rotatable bonds” (nRotB), are also crucial to evaluate drug
likeliness.
Table 4.
Drug likeness (indicated by Lipinski properties) of the selected
bioactive compound of Azima tetracantha analyzed with Swiss ADME.
Bioactive Compounds Lipinski’s Parameters Mv nRotB
Molecular Weight Log P nHBA nHBD TPSA (A^2) N
Violations
(E)-S-tert-butyl
2-((E)-4,4-dimethyl-5-((2,3,3-trimethyl-5-(methylthio)-3,4-dihydro-2H-p
yrrol-2-yl)methylene)pyrrolidin-2-ylidene)-2-(3,4-dimethyl-5-oxo-2,5-di
hydro-1H-pyrrol-2-yl)ethanethioate 503.76 4.99 3 1 61.43 1 482.64 10
5,6-dimethoxy-3-methyl-2,3-dihydro-1H-indene-1-one 281.38 5.26 3 0
29.66 1 255.16 2
5-(4-aminophenyl)-4-(o-tolyl) thiazol-2-amine 430.62 5.01 4 1 57.51 1
427.78 3
2-(3-acetoxy-4,4,10,13,14
pentamethyl2,3,4,5,6,7,10,11,12,13,14,15,16,17-
tetradecahydro-1H-cyclopenta[a]phenanthren-17-yl) propanoic acid 206.24
1.86 2 0 35.41 0 193.6 2
7-acetyl-3a^1-methyl-4,14-dioxo-1,2,3a,3a^1,4,5,5a,6,8a,9b,10,11,11a-te
tradecahydro-2,5a^1-epoxy-5,6a(methanooxymethano)phenaleno[1′,9′:5,6,7]
indeno[1,7a-b]oxiren-2-yl acetate 468.5 0.91 8 2 123.28 0 406.2 2
[92]Open in a new tab
All compounds passed the pre-set criteria: MLogP ≤ 5, nON ≤ 10, and
nOHNH ≤ 5 with zero violation (i.e., N Violations ≤ 1) ([93]Table 4),
indicating that they may be good candidates for drug design.
3.4. Molecular Docking
Molecular docking was performed for the two protein targets with all
the inhibitors (leads) to identify ligand binding sites and binding
modes, followed by the best scores ([94]Figure 4).
Figure 4.
[95]Figure 4
[96]Open in a new tab
In silico docking studies representing 2 dimentional Azima tetracantha
complexes with ligand interaction. (A) Compound 1,
[5,6-dimethoxy-3-methyl-2,3-dihydro-1H-indene-1-oneintertaction 4AGD].
(B) Compound 2, [5-(4- aminophenyl)-4-(o-tolyl) thiazol-2-amine]. (C)
Compound 3, [2-(3-acetoxy-4,4,10,13,14-pentamethyl-
2,3,4,5,6,7,10,11,12,13,14,15,16,17-tetradecahydro-1H-cyclopenta[a]phen
anthren-17-yl) propanoic acid]. (D) Compound 4,
[7-acetyl-3a1-methyl-4,14-dioxo1,2,3a,3a1,4,5,5a,6,8a,9b,10,11,11a-tetr
adecahydro-2,5a1-epoxy5,6a(methanooxymethano)phenaleno[1′,9′:5,6,7]inde
no[1,7a-b]oxiren-2-yl acetate].
The discovery of multi-target drugs is a hot topic, as studies revealed
that multi-target drugs have a safer therapeutic profile and
applications to more complex diseases. The detailed intermolecular
interactions and binding energy values of the molecules with VEGFC and
EFGR are listed in [97]Table 5.
Table 5.
Docking analysis of predicted compounds from the methanol extract of
Azima tetracantha leaf with 4AGD/2ITY Protein.
S. No. Compound Name 4AGD 2ITY
Docking Score (kcal/mol) Glide Energy
(kcal/mol) Docking Score (kcal/mol) Glide Energy
(kcal/mol)
1 5,6-dimethoxy-3-methyl-2,3-dihydro-1H-indene-1-one −4.91 −26.65 −5.58
−34.33
2 5-(4-aminophenyl)-4-(o-tolyl)thiazol-2-amine −4.48 −26.59 −6.80
−36.51
3
2-(3-acetoxy−4,4,10,13,14-pentamethyl-2,3,4,5,6,7,10,11,12,13,14,15,16,
17-tetradecahydro-1H-
cyclopenta[a]phenanthren-17-yl) propanoic acid −4.47 −39.05 −6.81
−43.53
4
7-acetyl-3a^1-methyl-4,14-dioxo-1,2,3a,3a^1,4,5,5a,6,8a,9b,10,11,11a-te
tradecahydro-2,5a^1-epoxy5,6a(methanooxymethano)phenaleno[1′,9′:5,6,7]i
ndeno[1,7a-b]oxiren-2-yl acetate −6.47 −52.25 −5.79 −44.60
[98]Open in a new tab
Among the four compounds, the compounds 37-acetyl-3a^1-methyl-4,14
dioxo1,2,3a,3a1,4,5,5a,6,8a,9b,10,11,11atetradecahydro2,5a1epoxy5,6a
(methanooxymethano)phenaleno[1′,9′:5,6,7]indeno[1,7a-b]oxiren-2-yl
acetate and (2-(3-
acetoxy-4,4,10,13,14-pentamethyl-2,3,4,5,6,7,10,11,12,13,14,15,16,17-te
tradecahydro-1H cyclopenta [a]phenanthren-17-yl) propanoic acid,
5-(4-aminophenyl)-4-(o-tolyl) thiazol-2-amine and
5,6-dimethoxy-3-methyl-2,3-dihydro-1H-indene-1-one) exhibit both
anti-cancer and anti-inflammatory properties. Compounds 4 (−52.25
kcal/mol), 3 (−39.05 kcal/mol), 2 (−26.65 kcal/mol), and 1 (26.59
kcal/mol) have better binding affinities and are well docked with the
EFGR enzyme. Compound 4 (−44.60 kcal/mol) gives the highest binding
energy values compared to the other compounds (compound 1 (34.3
kcal/mol), compound 2 (−36.51 kcal/mol), and compound 3 (−44.53
kcal/mol)) ([99]Figure 5). As a result, the newly developed compounds
were proven to have excellent natural accessibility, indicating that
they may be readily produced in the laboratory.
Figure 5.
[100]Figure 5
[101]Open in a new tab
In silico molecular docking studies representing 2 dimentional Azima
tetracantha complexes with ligand interaction. (A)
6-dimethoxy-3-methyl-2,3-dihydro-1h-indene-1-one interaction 2ITY
Ligplot. (B) 5,6-dimethoxy-3- methyl-2,3-dihydro- 1H-indene-1-one. (C)
2-(3-acetoxy-4,4,10,13,14-pentamethyl-2,3,4,5,6,7,10,11,12,13,14,15,16,
17- tetradecahydro-1H-cyclopenta [a]phenanthren-17-yl) propanoic acid.
(D) 7-acetyl-3a1-methyl-4,14-dioxo-
1,2,3a,3a1,4,5,5a,6,8a,9b,10,11,11a-tetradecahydro-2,5a1-epoxy5,6a
(methanooxymethano)phenaleno[1′,9′:5,6,7] indeno [1,7a-b]oxiren-2-yl
acetate.
Compound 4 forms a strong hydrogen-bonding interaction with the vital
amino acids (ASN923, THR410, LEU840, TRY927, PHE921, and GLY922)
compared with compound 3. The stabilization of compound 4 in VEGFC’s
active site is dependent on these interactions. With a combination of
growth factors and hypoxia, oncogene expression upregulates VEGF, a
central mediator of angiogenesis in cancer. They are also hemorrhagic
and leaky, resulting in a robust interstitial strain.
3.5. Protein–Protein Interaction (PPI) Network Analysis
Thirty-one primary hub nodes were selected and inserted into the STRING
database, establishing a connection between two distinct nodes
(proteins/genes). The PPI network (21 edges and 11 nodes) was
constructed ([102]Figure 6) and may play a key role in oncology’s
pharmacological impact phase.
Figure 6.
[103]Figure 6
[104]Open in a new tab
Protein–protein interaction network of targets related to cancer. The
colored nodes represent candidate proteins, and colored lines represent
protein interactions. Light green—represents text mining;
Black—represents co-expression; Light blue—represents known
interactions from curated databases; State blue—represents protein
homology; Magenta—represents experimentally determined known
interactions; Green—represents predicted interactions between
neighborhood genes; Red—represents predicted interactions of gene
fusion; and Blue—represents predicted interactions between co-occurred
genes.
Three targets, EGFR, EPGN, and BTC, did not communicate with each
other. High trust is described as a rating greater than or equal to
0.998. EREG, EGF, TGFA, and GRB2, as well as HRAS, were two separate
nodes with strong trust levels.
3.6. Molecular Analysis
At the statistical level, the p-value was <0.65. AT was mostly
associated with the MF 34 and led to biological quality control,
prostate gland growth, control of prostate epithelial cell
proliferation found by transmission, and gene-set enrichment analysis
knowledge along with a gene analysis set improvement for these 122
genes. EREG, EGF, TGFA, GRB2, and HRAS proteins have common biological
functions as well molecular functions (specifically the characteristics
of protein homodimerization). The analysis of drug aims is among the
most recognized techniques for systematically discovering medicines
based on ligands. Our bio-active products were found to be exposed to
-acetyl-3a^1-methyl-4,14-dioxo-1,2,3a,3a^1,4,5,5a,6,8a,9b,10,11,11a-tet
radecahydro-2,5a^1nepoxy5,6a(methanooxymethano)phenaleno[1′,9′:5,6,7]
indeno [1,7a-b]oxiren-2-yl acetate (ASN923, THR410, LEU840TRY927,
PHE921, GLY922). The dock complex exchanges for each ligand were
analyzed and inspected with efficient remains.
3.7. KEGG and REATOME Pathways Enrichment Analysis
A total of 21 KEGG pathways (p-value < 0.05) have been mapped into
active compound objectives. The results showed that EREG, EGF, TGFA,
GRB2, and HRAS were substantially enhanced throughout the pathway. The
number of target mapping pathways was higher than ErbB signaling
pathways in cancer (hsa04012 number = 9), non-small cell lung cancer
(hsa05223, number = 7), and EGR Tyrosine kinase inhibitors (hsa05219,
number = 4). The objectives of active compounds were mapped to
twenty-one respite pathways (p-value < 0.05). The findings showed a
substantial rise in EREG, EGF, TGFA, and GRB2 in paths. The mapping
target paths were greater than the signaling paths (HSA 180336, number
= 5, HSA5638303 number = 2, HSA179812, number = 4, HSA212718 number =
2, and HSA6802953 number = 2).
3.8. Compound-Target-Pathway Interaction Network
The AT compounds not only work on the same target protein but have been
used on various target proteins through several pathways, reflective of
the synergistic effect of AT “various components and numerous
objectives”. Finally, our results reveal novel structures with
similarly functional structural features and two compounds with higher
binding energy than the active molecules. The active site residual was
mapped on the binding site, and the extracts were identified in each
target structure in the dynamic field. The analysis of molecular
structures is the most effective method to evaluate the molecular
mechanisms of the drug’s action. Our findings will also finally
demonstrate that the novel structures with comparable structural
features with similar activities are identified concerning the most
significant binding energy compounds inactive molecules.
3.9. Compound Induce an Anti-Proliferative Effect on Cervical Cancer Cell
Line
To evaluate the anti-proliferative effect of our compound, we
investigated the cell viability by using various concentrations (18.75,
37.5, 75, 150, and 300 µg/mL) in the HeLa cell line. We observed the
increased rate of cell inhibition with increasing concentrations.
Approximately 90% and 72% of cell inhibition were observed with the
concentration of 300 and 150 µg/mL, respectively. The maximum
inhibitory concentration (IC50) of these compounds against cervical
cancer cell lines was 96 µg/mL. The cytotoxicity tests of leaf removal
accomplished over half of the cell passing in a convergence of 37.5
µg/mL ([105]Figure 7). We also observed the morphological
transformation in cancer cell lines after using the various
concentrations of our compound. We observed the decreased cytoplasmic
ratio, which results in oval-shaped morphology in HeLa cells
([106]Figure 8).
Figure 7.
[107]Figure 7
[108]Open in a new tab
Cellular metabolic activity indicated by cell viability. (A)
Cytotoxicity assays of Azima tetracantha compound treated for 24 h in
HeLa cell lines. The symbol (***) indicate the significant difference
(p < 0.001). (B) Percentage cell inhibition of Log[10] concentration
(µg/mL) on HeLa cell lines.
Figure 8.
[109]Figure 8
[110]Open in a new tab
DMSO-treated control cells showed the density of the cells. (A) 18.75;
(B) 37.50; (C) 75; (D) 150; and (E) 300 µg/mL treatment showed gradual
cell toxicity compared to control. (F) Methanol low dose treatment.
Scale bars.10µm.
4. Discussion
Over the last decades, herbal medicinal floras for cancer therapy have
gained attention due to the metabolic quality of certain organic
practices in various plant compounds. Aromatic medicinal plants are a
rich source of bioactive compounds with anticancer action that cause
less damage in healthy cells than conventional medicine. The key goals
of studying crude plant extracts were to either isolate bioactive
agents for further use or to find bioactive compounds that could be
used as lead compounds to study semi-artificial drugs. In our study, we
have used only MeOH as a solvent because it is more used than ethanol
(EtOH), the boiling point of EtOH is 78.4 °C while the boiling point of
MeOH is 64.7 °C, so when you have a methanol extract, you need a lower
temperature to evaporate the solvent in the rotary vapor. By this, the
extract is less damaged than the EtOH one. Likewise, MeOH can extract
both polar and non-polar compounds [[111]29].
Anti-tumor effects of herbal extracts are essential for behavioral
inhibition [[112]30]. ROS have a direct relationship with the tumor
since the former is elevated in the tumor. Elevated ROS are quenched by
increased antioxidant enzymatically in the same tumor cells. DPPH has a
hydrogen donating ability in radical-scavenging activities that are
very important to prevent the deleterious role of free radicals in
different diseases, including cancer. DPPH-free radical-scavenging is
an accepted mechanism for screening the antioxidant activity of plant
extracts [[113]31]. Therefore, the extracts that have strong radical
scavengers are naturally good antioxidants, which is consistent with
the previous reports [[114]32]. In our study, we found that AT has good
antioxidant properties, which is consistent with the previous reports
[[115]20].
We also found out that the MeOH extract of AT reduces the cell growth
in HeLa cells dose-dependently. It was on similar lines where MeOH
extracts of Jatropha curcus and J. gossypifolia inhibited cell growth
in HeLa cells at low doses. Both plant extracts had IC50s of 98.18 and
110.6 g/mL for substantial suppression of HeLa cell proliferation in
vitro. These tests were performed on both HeLa and HPL cells using MTT
and LDH leaks. An inhibitory effect of MeOH extract on HeLa cell growth
(IC50 = 100g/mL) was found at low concentrations. To normal cells, the
extract was less harmful. Because of its chemoprotective properties,
the current research suggests that it may be utilized to treat cancer.
It is a natural property of medicinal plants and herbs to exhibit far
stronger antioxidant activity compared to non-medicinal plants. This
solid antioxidant activity is driven by significantly higher levels of
phenolic compounds [[116]33,[117]34]. The application of an appropriate
extraction method in medicinal plants, including a selection of the
appropriate eluent to use these extracts in food production, is of
great importance in terms of obtaining valuable compounds (including
phenolic acids). This will increase the antioxidant activity of these
compounds and ultimately will be beneficial for the producers and
consumers.
Apart from antioxidant properties, the antiseptic effects of these
compounds are also important. These effects may be attributed to the
bioactive constituents’ varying chemical compositions and modes of
action [[118]35]. The distinction between Gram −Ve and Gram +Ve
bacterial strains may be attributed to morphological variations between
these microorganisms. G-Ve bacteria possess an outer phospholipidic
membrane containing structural components of lipopolysaccharide. This
makes the cell wall impermeable to lipophilic solutes, while porins
provide a selective barrier of approximately 600 Da (Dalton) for
hydrophilic solutes with an exclusion limit. Positive bacteria can be
more vulnerable since they only have an exterior peptidoglycan coating,
which is ineffective as a permeability buffer. The cell’s reaction to
inflammation will result in pathological symptoms, such as compromised
physiological functions [[119]36]. The inflammatory response has been
connected to the concept of various illnesses, including arthritis,
stroke, and cancer. Our study finds out that the capacity of MeOH
extract of AT to inhibit protein denaturation of albumin ranges from
16.75 ± 0.65 to 62.35 ± 0.20. It has shown promising evidence for its
anti-inflammatory properties. This was only the preliminary testing
where we have analyzed concentration-dependent percentage in membrane
protection. The research also offers solid support that AT leaves can
act as a potential anti-inflammatory agent in folkloric and tribal
medicine. As a result, the plant may be considered a renewable source
of membrane stabilizers, which can be an alternative treatment for
inflammatory disorders and diseases.
To detect the target protein of small molecules, it is important to use
the in silico molecular docking method. We used a small protein
molecule docking web service, SwissDock, to detect the ligand-protein
binding. It was found to be of great value for confirming prior fast
dockings in a two-step structure-based virtual screening (SBVS) process
[[120]37]. The mobility of a drug from the administration site into the
target site attributes to its physicochemical properties. Solubility is
a valuable parameter in rational drug design and is expressed in
MLog[P], where P is the partition coefficient in octanol-water, which
has implications on hydrophobic effect, bioavailability, and
absorption, interactions with receptors, metabolism, and toxicity of
the lead compounds. Similarly, the total polar surface area predicts
the transport capability of the leads and shows a correlation with the
human intestinal absorption, blood-brain barrier penetration, and
Caco-2 monolayers permeability [[121]38]. Furthermore, all of them pass
the important ADME/T properties concerned with the blood-brain barrier,
human oral bioavailability, human intestinal absorption,
carcinogenicity, etc. [[122]39]. Molecular docking and dynamics are the
core part of designing and screening new bioactive molecules
[[123]40,[124]41]. Molecular docking indicated that one of our
compounds (compound 4, 7-acetyl-3a^1-methyl-
4,14-dioxo-1,2,3a,3a^1,4,5,5a,6,8a,9b,10,11,11a-tetradecahydro-2,5a
epoxy5,6a
(methanooxymethano)phenaleno[1′,9′:5,6,7]indeno[1,7a-b]oxiren-2-yl
acetate) target EREG and is involved in cervical cancer. EREG is
down-regulated in cervical cancer; because of its critical function,
EREG is a good candidate for anticancer therapy. The protein–protein
interaction study indicates the interacting partners of EREG, and they
were EGF, TGFA, GRB2, and HRAS, and most of them regulate cervical
cancer [[125]42,[126]43,[127]44,[128]45]. Since our target proteins
were related to cervical cancer, we decided to use the most commonly
used human cervical cancer cells (HeLa cells) lines (the first human
cell line).
According to previous reports, HeLa cells that undergo shrinkage and
lose interaction with neighboring cells are distinguished by changes in
their morphology [[129]46,[130]47,[131]48]. Previous reports stated
that similar to AT, Jarong leaves also have cytotoxic properties, and
they are due to chemical compounds, such as alkaloids, flavonoids, and
terpenoids, which are shown to have anticancer effects. Flavonoids play
an essential function in cancer chemoprevention and chemotherapy since
it interacts with several various forms of genes and enzymes
[[132]49,[133]50]. Our results indicated that the MeOH extract of AT
reduced the cell growth in the HeLa cells line, and the reduction was
dose-dependent. It was similar to the previously reported studies,
where MeOH extracts of different medicinal plants Jatropha curcus and
J. gossypifolia also inhibited cell growth in HeLa cells in similar
manners [[134]51]. The results in our study indicate that the decreased
free radicals and oxidative stress by increasing antioxidants might
play a role in ameliorating the DNA damage by reducing the rate of
abnormal cell division and decreasing mutagenesis. It is the main
reason for many antioxidant-rich plants to possess antibacterial and
anticancer activity, such as AT [[135]52,[136]53].
5. Conclusions
The discovery of the well-known antioxidants in plants that might have
bioactive compounds has raised the hopes for their use to prevent and
treat the diseases mentioned above. The results in our study indicate
that the active compound 4 (7-acetyl-3a^1-methyl-
4,14-dioxo-1,2,3a,3a^1,4,5,5a,6,8a,9b,10,11,11a-tetradecahydro-2,5a
epoxy5,6a
(methanooxymethano)phenaleno[1′,9′:5,6,7]indeno[1,7a-b]oxiren-2-yl
acetate) of AT can be used as a novel bioactive natural product that
may serve as a leading molecule in the pharmaceuticals for its
anticancerous and antibacterial properties. However, a thorough in vivo
and pharmacological analysis will shed more light on its working
mechanism. Our finding paves the way for the future identification of
possible therapeutic compounds in AT that can be developed into a novel
modern drug.
Acknowledgments