ABSTRACT- P53 is a tumor suppressor gene with a well established role in causation of different human cancers. The
p53-MDM2 interactions have become the cornerstone of intensive cancer based research due to their effective anti-cancer
properties. These potential compounds are found in many traditional natural plant products. In the present context, there is
a tremendous level of enthusiasm to evaluate the pharmacological potential of various natural plants used in traditional
systems of medicine. The experimental efforts to carry out such biological screening of plants are still considerably high,
and therefore, computer-aided drug design approaches have become attractive alternatives. Virtual screening has
established itself as a dynamic and cost-effective technology to isolate compounds with pharmacological potential. The
main aim of the present study is to identify a novel or similar or better drug like compound in comparison with that of the
FDA approved drug Nutlin (potent MDM2-p53 inhibitor) from the Hamelia patens plant, through the Structure Based
Virtual Screening, Docking and Molecular Dynamic Simulation studies, for future anti-cancer therapy for future
implications as a therapeutic model.
Key-words- MDM2-p53 interaction, Natural Plant products, Virtual screening, Docking, Molecular dynamic simulation
INTRODUCTION-
Cancer is an abnormal growth of cells, capable of invading
surrounding tissue. This progression encompasses multiple
stages, owing to the malignant potential. Heritable genetic
mutation constitutes the nidus for uncontrolled
proliferation. These mutations alter the quantity (or)
function of the protein products that regulates cell growth
and division with DNA repair.
There are two major categories of mutated genes;
“oncogenes and tumor suppressor genes” [1].
Oncogenes regulate the growth of cells whereas tumor
suppressor genes suppress cell division through various
processes. Tumor suppressor genes act as a check points for
cell division and it is essential for cell division and their
normal function [2]. If it does not function properly, cells
can become awry leading to cancer. Inherited abnormalities
of these tumor suppressor genes have been detected in
some familial cancer syndromes. But most tumor
suppressor gene mutations are acquired, not inherited. For
example, acquired tumor protein gene (TP53 or p53)
mutations have a wide implication in cancer causation and
this defect has been detected in more than 50% of human
cancers [3]. p53, tumor suppressor gene, is in the center of
normal cell division and growth. When silent these cells
with spontaneous genetic mutation may progresses to
tumors [1].
TP53-
TP53 protein is a tumor suppressor protein and is related to
control of cell proliferation [4]. TP53 has a short half life. It
is localized in the nucleus of the cell, binding with DNA for
regulation of cell. In time of stress, related to toxic agents
and chemicals, this protein will be the determine factor to
decide whether the cell will undergo apoptosis or not.
Depending on the reparability, p53 fixes the damaged DNA
otherwise initiating apoptosis. This process halts the
progression of the cell with mutated and damaged DNA,
preventing future development of tumors. Based on this
function TP53 is referred as the “guardian of the genome”.
[5-6]
More than 50% of human cancer occurs as a result of
somatic mutation in TP53 gene. Most of these are single
point mutation, producing large amount of defective
proteins, which can build up preventing apoptosis and
leading to malignant proliferation. Thus the damaged cells
will keep on dividing in an uncoordinated way causing
cancers [7].
MDM2-
Mouse double minute 2 homolog [MDM2] protein, also
referred as E3 ubiquitin-protein ligase, is encoded by the
MDM2 gene in humans, visible in tumors only [8-9]. Being
an important regulator of p53 tumor suppressor protein,
MDM2 binds to N-terminal of TP53 suppressing its
transcription [6]. MDM2 central zinc finger binds to
ribosomal proteins degrading TP53, which is often
disrupted by cancer associated mutation [10]. The high
levels of MDM2 in many different human cancer types
support the role of MDM2 in cancer causation.
MDM2 and p53 Interactions-
TP53 can be turned “on and off” by direct gene altercation
or interaction with MDM2. Development of small
molecules capable of blocking MDM2-p53 interaction is a
suitable technique to treat p53 related tumors. It is absolute
necessary to have an in-depth understanding of MDM2-p53
interaction at molecular level to apply modern technique
for development of such compounds [11]. There has been
continuous search for the natural plant products with
chemotherapeutic properties [12]. The use of alternative
natural plants products to target cancer cells is a promising
field of research, because the conventional therapy alone is
unable to curb the spread of the cancer [13].
Hamelia patens and secondary plants products-
There is a continuous trend of the use of plants products for
variety of disease process although little is known about
them. Hamelia patens is one of the natural plant commonly
used in many forms. It is a perennial shrub to tree and
commonly known as scarlet, fire or humming bird bush
(Fig 1). It has elliptical to oval whorled leaves and
gray-pubescent underneath with reddish veins and petioles.
Hamelia patens have been studied chemically. It is known
to contain pentacyclicoxiindole alkaloids. A number of
active compounds have been found in firebush, such as
apigenin, ephedrine, flavanones, isomaruquine,
isopteropodine, maruquine, narirutins, oxiindole alkaloids,
palmirine, pteropodine, rosmarinic acid, rumberine, rutin,
seneciophylline, speciophylline, isopteropodine,
stigmast-4-ene-3,6-dioneand tannin [14]. It has been used
traditionally to cure multiple common ailments like skin
lesion and inflammatory conditions. The objective of this
study is to identify the potent MDM2-p53 interaction
inhibitors for cancer therapy from the active compounds
extracted from the Hamelia patens leaf extracts by
methanol extraction by the structure based virtual
screening, docking and molecular simulation studies.
Fig 1: Hamelia patens plant
MATERIALS AND METHODS:
Collection and Preparation of Sample-
The leaves of
Hamelia patens were randomly collected
from Andhra Loyola College, Vijayawada, and the
experiment was performed in the pharmaceutical lab of Sri
Vasavi Institute of Pharmaceutical Sciences,
Tadepalligudem, India.
Extraction of active compounds-
Extraction is the crucial first step in the analysis of
medicinal plants, because it is necessary to extract the
desired chemical components from the plant materials for
further separation and characterization. Polar solvents, such
as methanol, ethanol or ethyl-acetate, are used for obtaining
hydrophilic compounds. Different sequences of events
were followed starting with washing, drying, freezing and
grinding of the plants to achieve a homogenous product.
Continuous extraction was applied to extract the alkaloid
through Soxhlet apparatus. Isolation and partial purification
of the alkaloid was done with thin-layer chromatography
(TLC).
Identification Test for the Presence of Alkaloids-
Dragendorff’s and Mayer’s reagents, on crude ethanol
extract of
Hamelia patens were used to indicate the
presence of alkaloids. This extract was converted into thick
syrup through evaporation. It was followed by addition of
2N HCL (5 ml), heated for 5 minutes with stirring in water
bath and cooled. 0.5g of NaCl was added to the mixture for
avoiding false positive outcome. The overall residue was
than stirred, filtered and washed with 2N HCL again, and
thereafter 5ml of final solution was obtained. The final
filtrate was divided into three test tubes, each with 1 mL of
solution. The first 1 mL of the filtrate was mixed with 2-3
drops of Mayer’s and second with Dragendorff’s reagent
respectively. The third test tube with 1 mL of the solution
was used as a control after comparing with that of the
known alkaloid compound (Morphine).
The isolation and partial purification of alkaloid- rich
fraction of Grounded leaves of
Hamelia patens were done
using Thin-Layer Chromatography by comparing with a
known alkaloid Morphine. The mobile phase used was
toluene: acetone: ethanol: ammonia (40:40:6:2).
Structure Based Virtual Screening, Docking and
Molecular Simulation Studies
Software and Program-
Schrodinger’s maestro visualization program (Maestro,
v9.6, 2013) and Accelry’s discovery studio 4.0 is utilized
for mapping the receptors, structure of ligand, hydrogen
bonding, to determine length of the bonds and to visualize
images. Autodock Vina is the primary docking program
used in this work for the structure based virtual screening
[15]. The Auto-Dock Tools version 1.5.6 (The Scripps
Research Institute, La Jolla, USA) was used to obtain the
ligands and proteins in pdbqt file and finding of the grid
box size [16- 17]. Schrodinger’s Desmond module
(Desmond v3.6, 2013) was used for molecular dynamic
simulation studies.
Preparation of protein structure-
The three-dimensional structures of MDM2-p53 complex
were retrieved from the Protein Data Bank [18]. These
structures were prepared by removing all bound crystal
water molecules and hetero atoms including ligands.
Missing hydrogen bonds were added. Obtained structures
were energy minimized using charms force field for
optimal docking results.
Virtual screening-
Virtual screening based on the structure of MDM2 inhibitor
was carried out. Autodock Vina was utilized to search for
potential inhibitors amongst the compounds found through
ligand based virtual screening, targeting MDM2 active site
(p53 binding site). AutoDock is very effective in locating
docking modes in relation to the X-ray crystal structures. A
spacing of 0.4 Å between the grid points was used.
Lamarckian Genetic Algorithm (LGA) was selected as
docking engine with the default parameters. Flexibility of
the ligand helps in exploring the spatial degrees of freedom
for rotation and translation, for given number of torsional
degrees of freedom. Interaction energy for every new
location and conformation of the ligand is evaluated by
applying a random perturbation for each time step.
The grid box was set to 28.81; -18.40 and -3.87 Å (x, y, and
z) cube at MDM2 active site. After each LGA run,
Autodock reports the best docking solution (lowest docked
free energy), and results are reported based on cluster
analysis and Gibbs free energy. The summation of
hydrogen bonding, dispersion/repulsion, electrostatic
interactions and deviation from covalent geometry, internal
ligand torsional constraints, and desolvation effects
accurately gives the Gibbs free energy (?G). The lowest
energy docking mode was selected from each docking
simulation after obtaining a total of 10 docking modes
represented by LGA cluster analysis.
Molecular dynamic simulations-
‘‘Desmond v3.6 Package’’ was used to study the thermo
dynamical stability of the receptor-ligand system.
OPLS2005 force field was used to simulate water
molecules using predefined TIP3P water model [19-20].
The exact shape and size of the repeating unit buffered
distanced at 10 Å distances were specified by
orthorhombic periodic boundary. The calculation and
minimization of the boundary conditions box volume was
performed simultaneously.
In order to neutralize the system electrically, appropriate
counter Cl-/Na+ ions were added to balance the system
charge and were placed randomly in the solvated system.
After building the solvated system containing protein in
complex with the ligand, the system was minimized and
relaxed using default protocol integrated within Desmond
module using OPLS 2005 force field parameters.
Molecular dynamic simulations were carried out with the
periodic boundary conditions in the NPT ensemble [21].
Nose-Hoover temperature coupling and isotropic scaling
were used to maintain the temperature and pressure at
300K and 1 atmospheric respectively; it was followed by
10ns NPT production simulation, saving the configurations
thus obtained at 5ps intervals.
RESULTS:
Identification of the presence of alkaloids in the
Hamelia patens leaf extract-
Thin-layer Chromatography (TLC) on pre-coated silica gel
60F254 plate with toluene: acetone: ethanol: ammonia
(40:40:6:2) solvent system afforded five alkaloids (Table
1). Alkaloid 1, 2, 3 and 4 had a smaller Rf value which is
0.16, 0.26, 0.35 and 0.46 respectively. All of them exhibited
lesser affinity towards the mobile phase. On the other hand,
alkaloid 5 had Rf value of 0.52, higher than the previous
alkaloids and showed greater affinity toward the eluent. All
alkaloids produced orange-brown spots when sprayed with
Dragendorff’s reagent. These spots fluorescent were blue at
U.V. light at 366 nm, indicating the presence of alkaloids.
Table 1: Retention factor (Rf) of the extract compound of the HpLEt
S. No | Compound’s Name | Rf Value | Observation |
1 | Alkaloid -1 | 0.16 |
Produced orange-brown spot with Dragendorff’s reagent;
fluoresced blue light at U.V. 366 nm |
2 | Alkaloid -2 | 0.26 |
Produced orange-brown spot with Dragendorff’s reagent;
fluoresced blue light at U.V. 366 nm |
3 | Alkaloid -3 | 0.35 |
Produced orange-brown spot with Dragendorff’s reagent;
fluoresced blue light at U.V. 366 nm |
4 | Alkaloid -4 | 0.46 |
Produced orange-brown spot with Dragendorff’s reagent;
fluoresced blue light at U.V. 366 nm |
5 | Alkaloid -5 | 0.52 |
Produced orange-brown spot with Dragendorff’s reagent;
fluoresced blue light at U.V. 366 nm |
6 | Morphine | 0.34 |
Produced orange-brown spot with Dragendorff’s reagent;
fluoresced blue light at U.V. 366 nm |
This observation established the presence of the five alkaloids from the extracted sample of HpLEt compared to that of the
known alkaloid called morphine. These five alkaloids are: Palmirine, Rumberine, Alakaloid A, Isopteropodine, and
Maruquine (Fig 2). There have been multiple reported extractions of different chemical compounds from HpLEt in the
past. Based on the chemical analysis, the leaf extracts of
Hamelia patens has also revealed the presence of other chemical
constituents like essential oils, alkaloids, tannins, saponins, carotenoids, flavonoids and triterpenes [22-23].
Fig 2: Structures of Hamelia patens compounds
Active constituents of Hamelia patens as promising
anti-cancer drug candidates targeting MDM2:
A. Docking of the compounds with MDM2 active
site-
The experiment was followed by performing the docking
studies for the extracted compounds from
Hamelia patens
with the MDM2 protein, targeting its active p53 binding
site, in order to know whether these compounds are capable
of binding at the same binding site of MDM2 protein where
active p53 peptide binds. It will also help us to find the
binding energy involved in this complex formation along
with molecular interactions responsible for this target
specific inhibition.
All the five compounds studied in this present work have
shown to successfully dock inside the same active binding
site of MDM2 protein where p53 peptide binds with a
binding energy in a range of -7.42 to -6.79 Kcal/mol.
Among the five tested compounds Palmirine has shown to
be the best MDM2 inhibitor with a binding energy -7.42
Kcal/mol, whereas Maruquine compound showed the least
binding affinity towards MDM2 with a binding energy
-6.79 kcal /mol. When the docked conformation of MDM2
protein in complex with Palmirine compound was
investigated, it was revealed that this compound is a single
hydrogen bond with HIS96 residue. Apart from hydrogen
bonds, this compound was found to be forming
hydrophobic interactions with ILE99, TYR100, LEU54,
ILE61, LEU57; ILE103, PHE86, VAL93 and PHE91
residues (Fig 3). Along with above interactions, HIS96
residue was also found to be forming pi-pi interaction with
Palmirine compound contributing towards stabilizing the
docked compound inside the active site of MDM2 protein.
(A)
(B)
(C)
Fig 3: Docking snapshots of Palmirine compound with
MDM2 drug target showing A) surface binding
B) 2d interactions, and C) 3d interactions
B. IC50 prediction-
In order to understand the plausible experimental
anti-cancer activity of the present studied compounds from
Hamelia patens plant, we have carried out the half maximal
inhibitory concentration (IC50) value predictions. IC50
value is a reliable tool to quantitatively measure the
usefulness of the compound to inhibit a given biological
process by half and is widely applied to symbolize the
inhibitory effect of given compounds. The predicted IC50
values for the compounds were within a range of 3.66 to
10.59 micro molar. Among which Palmirine compound has
shown the best possible inhibitory potential with 3.66
micro molar. IC50 values obtained clearly demonstrated
plausible high inhibitory potential of Palmirine compound
among the five studied compounds from
Hamelia patens
plant with MDM2 protein.
C. Molecular Dynamics simulations of MDM2
protein in complex with palmirine compound-
Based on the promising inhibitory potential shown by
Palmirine compound towards MDM2 protein as evident
with docking and IC50 value predictions, we have taken
this compound for further analysis to reveal underlying
molecular interactions which might not have been revealed
during docking studies and to better understand the effect
of Palmirine compound binding with MDM2’s p53 binding
active site. The MDM2- palmirine protein-ligand binding
complex with the binding energy of -7.42 kcal/mol
obtained using AutoDock calculations was used for
carrying out MD simulations (Table 2). The predicted IC50
values for the compounds were within a range of 3.66 to
10.59 micro molar. Among which Palmirine compound has
shown the best possible inhibitory potential with 3.66
micro molar. IC50 values obtained clearly demonstrated
plausible high inhibitory potential of Palmirine compound
among the five studied compounds from
Hamelia patens
plant with MDM2 protein.
Table 2: Docking energies of Hamelia patens compounds
with MDM2 protein
S. No |
Drug target |
Compound
Name |
Docking
binding
energy in
Kcal/mol |
Predicted
IC50 value
in micro
molar |
1. | MDM2 | Palmirne | -7.42 | 3.66 |
2. | Rumberine | -7.3 0 | 4 . 4 8 |
3. | Alakaloid A | -7.09 | 6.34 |
4. | Isopteropo-dine | -7.04 | 6.92 |
5. | Maruquine | -6.79 | 10.59 |
After MD simulations, we calculated Root mean square Deviation (RMSD) for the trajectory MDM2 complexed with
Palmirine using its initial model as a reference structure (Fig 4). The results show that the protein
backbone RMSD [green] for the complex were always less than 1.7 Å, which is comparably equal to the RMSD of the
MDM2 in complex with Nutlin compound suggesting that this compound has similar confirmatory effect on the MDM2
similar to FDA approved drug Nutlin and also evidences the overall stability of our simulated system of protein (MDM2)
in complex with this Palmirine compound. On the other hand, ligand superimposed on itself throughout the simulated time
was quite stable in its binding conformation showing well below 0.2 Å RMSD hinting towards its adaptability with the
MDM2 active site conformational changes.
Fig 4: Root mean square Deviation [RMSD] graphs of MDM2 protein in complex with Palmirine compound
When MDM2 protein’s residue fluctuations were calculated in presence of ligand Palmirine compound, it was observed
that the backbone of the protein was quite stable throughout the simulation with well below 1.2 Å of fluctuating
distance (Fig 5).
Fig 5: Root mean square Fluctuations [RMSF] graphs MDM2 protein in complex with Palmirine compound
These results are highly in support to the strong inhibiting
and stabilizing potential of Palmirine compound on MDM2
protein when compared with residue fluctuations of MDM2
protein in presence of no ligand which was shown to
having highly fluctuating over 2.5 Å, whereas for MDM2
in presence of Nutlin was found to be fluctuating around
2.0 at initial 30 residues and at residues located at 80-90
position. 10ns of simulation time used in this present study
is of enough time for the side chain rearrangements in the
native as well as protein-ligand complexes in order to
facilitate the most stable binding conformation.
Radius of Gyration (ROG) graph (Fig 6) of the
MDM2-palmirine complex has evidenced the protein
MDM2 protein has slightly contracting as the simulation
progresses in presence of Palmirine compound by
maintaining an average of 12.92 Å within a range of 12.60
Å to 13.27 Å.
Fig 6: Radius of Gyration [ROG] graphs of MDM2 protein in complex with Palmirine compound
When this data is compared with MDM2 protein in presence of no ligand and in presence of Nutlin, it is evident that
MDM2 protein is expanding slightly in presence of Nultin similar to this Palmirine compound suggesting this compounds
ability to inhibit MDM2 in a similar manner of Nutlin compound.
We were also calculated the intra molecular hydrogen bonds present throughout the simulation time within the MDM2
protein in complex with Palmirine compound and found out that it is maintaining an average of 71 intra molecular
hydrogen bonds in a range of 60 to 83 throughout the simulation time accounting for its stability and evidenced the
increase in protein rigidity in presence of this ligand in comparison to MDM2’s averaged 67 intra molecular hydrogen
bonds in presence of no ligands (Fig 7). However, interestingly this compound was found to be maintaining similar intra
molecular hydrogen bonds 71 as of Nutlin compound.
Fig 7: Total number of intra molecular hydrogen bonds present in MDM2 protein in complex with Palmirine
compound
Finally, we have analyzed the total energy involved for the stabilized conformation of this MDM2 protein in complex with
Palmirine compound and it was observed to be maintaining an average of -2462.38 Kcal/mol of energy in a range of
-2947.56 to -2031.85 Kcal/mol, which is similar to MDM2’s averaged energy in its apo state and in presence of Nutlin
compound (Fig 8).
Fig 8: Total energy of MDM2 protein in complex with Palmirine compound
We have also monitored the effect of Palmirine compound on total Secondary structure elements (SSE) present in the
protein MDM2 throughout the simulation trajectory. From the analysis it was revealed that the protein MDM2’s SSE
composition of helices and strands over simulated time averaged at 50% is similar to that of the SSE composition of
MDM2 protein in presence of Nutlin compound (Fig 9).
Fig 9: Secondary structural elements of MDM2 protein in complex with palmirine compound
Molecular interactions of MDM2-palmirine complex during MD simulations-
We have used Simulation interactions diagram program integrated within Desmond module of Schrödinger for studying
the detailed inter-molecular interactions between MDM2 protein and Palmirine compound. There were about 22 contacts
found in between MDM2 protein and palmirine compound in total among which two hydrogen bonds were observed with
HIS96 and ARG97 residues and most of other contacts were found to be hydrophobic contacts followed by water bridging
and ionic bonds (Fig10).
Fig 10: Protein-ligand interactions (or 'contacts') of MDM2-palmirine complex. The stacked bar charts are
normalized over the course of the trajectory. For example, a value of 0.7 suggests that 70% of the simulation time
the specific interaction is maintained
Finally, to examine and estimate the ligand torsion dynamics facilitating for the hydrogen bonds along with other
interactions between MDM2-palmirine complex; we have analyzed the torsional degree of freedom for the rotatable bonds
present in the ligand. For the Palmirine compound, a total of three rotatable bonds have been observed (Fig 11). From the
dial panels it is clear that the above mentioned rotatable bonds are consuming energy of 10.14; 10.00 and 7.83Kcal/mol of
energy respectively.
Fig 11: The ligand torsions of palmirine compound plot summarizing the conformational evolution of every
rotatable bond (RB) in the ligand throughout the simulation trajectory (0.00 through 10.00 nsec). A dial/bar plots
with the same color also represent these rotatable bonds torsion. Dial gives the manner of torsion formation
throughout the course of the simulation. Center of the radial plot denotes the beginning of the simulation against
the time, which is plotted radially outwards. The bar plots represent the dial plot by giving approximation of the
density of the torsion. The plot also gives the potential of the rotatable bond if available (by adding the potential of
the related torsions). Left Y-axis represents the values of the potential in Kcal/mol
To further analysis the binding mode similarities between the p53 and our proposed compound Palmirine, we have
performed the post docking analysis to check for the same via superimposing the docked conformation. From the analysis,
it is evident that proposed compound Palmirine mode of inhibition is very much similar to p53 peptide; especially
prominent alignments were observed with the p53 residues TRP23 and LEU26 (Fig 12).
From this analysis, it is evident that proposed compound Palmirine mode of inhibition is very much similar to p53
peptide; especially prominent alignments were observed with the p53 residues TRP23 and LEU26.
(a)
(b)
Fig 12: Superimposition of the Palmirine compound (yellow) with p53 peptide showing the alignments of the
compound’s side chain benzene rings almost in the same orientation as that of TRP23 and LEU26 residues of p53
showing the strong binding association. Above panels depicts the same in various orientations
DISCUSSION-
In the present study an investigation was carried out to find
out natural plant extract to act as an anti-cancer drug on the
mode of interaction between MDM2 and p53 at molecular
level. The p53 is an important tumor suppressor gene with
a known role in the later stages of cancer. MDM2 is a p53
responsive gene as its transcription can be activated by p53.
Thus inhibiting the MDM2-p53 interactions has been
proven to be most promising approach for cancer therapy.
The methanolic extract from
Hamelia patens was subjected
to structure based virtual screening approach to identify
target specific MDM2 inhibitors by docking studies. The
best extracted compound was subjected to molecular
dynamic simulations for further validating the docking
studies and to reveal interactions during the conformational
changes. The identified compounds were compared to that
of the FDA drug Nutlin compound that which has already
been proven. In this work, we discovered several
compounds from our case study with the
Hamelia patens
leaf extract, that are potentially able to inhibit the
MDM2-p53 interaction, proving their anti-cancer agents
similar to Nutlin. The present study provides a
rationalization to the ability of present studied compounds
as a valuable small ligand molecule with strong binding
affinity towards MDM2 protein for plausible anti-cancer
activity. Our computational analysis evidence shows that
the large value of binding energy is involved in binding of
present investigated five compounds (isopteropodine,
rumberine, palmirine, maruquine and alkaloid A) with the
MDM2 protein consolidating their complex’s
thermodynamic stability; moreover, predicted IC50 values
further substantiated our hypothesis that these compounds
have the potential to inhibit MDM2 protein.
Further, de novo simulations for 10 ns suggest that ligand
interaction with the residues of MDM2, all or some of
which fall under catalytic active site important residues for
its structurally stability and/or functionality, could be
critical for its inhibitory activity. This knowledge is very
important for computational screening of drugs targeting
MDM2. A little knowledge was gained through this study,
that it would further enhance the discovery of MDM2
target specific drug compounds by understanding the
molecular interaction basis between ligand and receptor.
This gives the basis of anti-cancer drugs, opening a wide
horizon of future opportunities. We have focused
particularly on four key steps: target validation and
selection; chemical hit and lead generation; lead
optimization to identify a clinical drug candidate by using
computational techniques. The novel computational
techniques have been developed to predict the interaction
models of protein- protein (p53-MDM2 interactions)
interactions from medium to high resolution. The discovery
of new and effective p53 activator/inhibitors opens the
broader spectrum of targeted therapy for treating cancers.
Collectively, these advances provide new opportunities to
use macromolecular structures in pharmaco-genomics and
systems pharmacology.
CONCLUSION-
MDM2 has been identified as a p53 interacting protein
which represses p53 transcriptional activity. Design of
non-peptide, small-molecule inhibitors, obtained from
secondary plant products, that block the MDM2-p53
interaction has been sought as an attractive strategy to
activate p53 for the treatment of cancer and other human
diseases. Major advances have to be made in the design of
these small-molecule inhibitors of the MDM2-p53
interaction as targeted therapies for advanced preclinical
development or clinical trials, justifying the use of plant in
traditional medicine practices. It is therefore recommended
that more work be conducted to help optimally extract all
the bioactive compounds in the plant and formulate into
appropriate doses for the treatment.
REFERENCES-
Chabner BA. Harrisons Manual of Oncology. 2nd edition.
McGraw-Hill Education / Medical;2013.
Fearon ER, Bommer GT. Progressing from Gene Mutations
to Cancer. In: Abeloff MD, ArmitageJO, Lichter AS,
Niederhuber JE. Kastan MB, McKenna WG eds. Clinical
Oncology. 4th ed. Philadelphia, Pa. Elsevier; 2008:207 -222.
Berger AH, Pandolfi PP, De Vita VT, Lawrence TS,
Rosenberg SA. In: De Vita, Hellman, and Rosenberg’s
Cancer: Principles and Practice of Oncology. 8th ed.;
2011:161–172.
Chang et al.Identification and Partial Characterization of
New Antigens from SV40- Transformed Mouse Cells.
J.Virol. 1979;31: 463-471.
Vogelstein et al. Surfing the p53 network. Nature. 2000;408
(6810):307-10.
Vassilev LT, Vu BT, Graves B et. al. In vivo activation of the
p53 pathway by small-molecule antagonists of
MDM2.Science303. 2004;844–848.
Levine .et.al.Cell death and differentiation.Cancer Res.
2006;52: 1-10.
Oliner JD, Kinzler KW, Meltzer PS, George DL, Vogelstein
B. Amplification of a gene encoding a p53-associated protein
in human sarcomas. Nature. 1992;358 (6381): 80–3.
Wade M, Wong ET, Tang M, Stommel JM, Wahl GM. Hdmx
modulates the outcome of p53 activation in human tumor
cells. J. Biol. Chem. 2006;281 (44): 33036–44.
Lindstrom.MS, Jin A, Deisenroth C, White Wolf G, Zhang Y.
Cancer-associated mutations in the MDM2 zinc finger
domain disrupt ribosomal protein interaction and attenuate
MDM2-induced p53 degradation. Mol Cell Biol. 2007;27:
1056–1068.
Chong Li, Min Liu, 2010. D-peptide inhibitors of the
p53-MDM2 interaction for targeted molecular therapy of
malignant neoplasms. PNAS. 2010;107:32.
Sharma S, Stutzman JD, Kelloff GJ, Steele VE. Screening of
potential chemopreventive agents using biochemical markers
of carcinogenesis. Cancer Res. 1994; 54: 5848–5855.
Rao CV, Rivenson A, Simi B, Reddy B S. Chemoprevention
of colon carcinogenesis by dietary curcumin, a naturally
occurring plant phenolic compound. Cancer Res. 1995; 55:
259–266.
J. Duke. Dr. Duke's phytochemical and ethnobotanical
databases - Hamelia patens. Retrieved 19 (2007).
Trott.O, A.J. Olson. AutoDockVina: improving the speed and
accuracy of docking with a new scoring function, efficient
optimization and multithreading. Journal of Computational
Chemistry. 2010;31: 455-461.
Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE.
Automated docking using a Lamarckian genetic algorithm
and an empirical binding free energy function. J Comput
Chem. 1998;19: 1639-1662.
Goodsell DS, Morris GM, Olson AJ. Automated docking of
flexible ligands. Applications of Autodock. J Mol.
Recognition. 1996;9: 1-5.
Bernstein FC, Koetzle TF, Williams GJ, Meyer EF Jr, Brice
MD, Rodgers JR, Kennard O, Shimanouchi T, Tasumi M.
The Protein Data Bank: a computer-based archival file for
macromolecular structures. J Mol Biol. 1977;112(3):535-42.
Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW,
Klein ML. Comparison of simple potential functions for
simulating liquid water. J. Chem. Phys. 1983;79:926-935.
Jorgensen WL, Maxwell DS, Tirado-Rives J. Development
and testing of the OPLS all-tom force field on
conformational energetics and properties of organic liquids.
J. Am. Chem. Soc. 1996;118:11225–11236.
Shinoda W, Mikami M. Rigid-body dynamics in the
isothermal-isobaric ensemble: a test on the accuracy and
computational efficiency. J Comput Chem. 2003;24(8):
920-30.
Arima H., Danno G. Isolation of antimicrobial compounds
from guava (Psidium guajava L.) and their structural
elucidation. Bioscience Biotechnology and Biochemistry.
2002;66(8):1727-1730.
Begum S, Hassan SI, Siddiqui BS, Shaheen F, Ghayur MN,
Gilani AH. Triterpenoids from the leaves of Psidiumguajava.
Phytochemistry. 2002;61(4):399-403.
International Journal of Life-Sciences Scientific Research (IJLSSR)
Open Access Policy
Authors/Contributors are responsible for originality, contents, correct
references, and ethical issues.
IJLSSR publishes all articles under Creative Commons
Attribution- Non-Commercial 4.0 International License (CC BY-NC).
https://creativecommons.org/licenses/by-nc/4.0/legalcode |
How to cite this article:
Raghavendra Rao M.V., Raj BV, Acharya Y, Nayak SJK, SireeshaBala A, Pawar AC: Targeting p53-MDM2 Interaction by
Natural Plant Products: A Novel Approach for Future Cancer Therapy. Int. J. Life. Sci. Scienti. Res., 2017; 3(2): 940-950.
DOI:10.21276/ijlssr.2017.3.2.12
Source of Financial Support: Nil, Conflict of interest: Nil |