Targeting Key Signalling Pathways in Leukemia: A Docking-Based
Approach for Drug Discovery
Fadilullahi Opeyemi Ibiyemi*; Ismail Kolawole Odetayo
1Department of Chemistry & Industrial Chemistry, Osun State
Water Regulatory Commission, Ministry of Water Resources , Osun State, Nigeria
2Department of Biochemistry & Chemistry Fountain University,
P.M.B. 4491 Osogbo Osun State, Nigeria
*Correspondence: ibiyemi.ademola97@gmail.com
DOI: https://doi.org/10.71431/IJRPAS.2025.4806
|
Article Information
|
|
Abstract
|
|
Review Article
Received: 14/07/2025
Accepted: 01/08/2025
Published: 31/08/2025
Keywords
phytoconstituent, FLT3 gene,
Ligands,
Docking,
Lipkins rule
|
|
Cancer may be a sort
of malady that bargains with advancement and multiplication of irregular
cell, they have inclination to devastate typical cell. The aim of this
research is to conduct a comprehensive review of key signaling pathways
implicated in leukemia progression and to identify potential molecular
targets, finally to perform molecular docking simulations to predict the
binding affinities and interactions between selected ligands and target
proteins. This investigate is centered on leukemia which is the cancer of the
blood cell, caused by protein FLT3 gene, which we have targeted the signal
pathway in leukemia using a docking based approach for drug discovery. In
this thinks about, assortments of phytoconstituent were chosen selected, to
check their liking for treating leukemia and the phytoconstituent were chosen
on the criterial of lipkins rule and preADMET for ADME and toxicology
prediction. The chosen phytoconstituent were associating with protein causing
leukemia FLT3 (1ETE) utilizing schrodinger maestro software program to
perform the docking.Result shows that resveratrol and pterostilbene shows a
better docking score after the protein-ligand interaction with a binding
score of -5.606 and -5.218 respectively, which underscores the potential of
resveratrol and pterostilbene as a good candidate for inhibiting FLT3 gene
causing leukemia compare to other selected phytoconstituent.
|
INTRODUCTION
Understanding the causes, chance components, and treatment choices for
cancer is basic in organize to successfully coordinate and anticipate the
ailment, {31}.
Cancer may be a complex and multifaceted sickness that impacts millions of
individuals around the world. It is basic to educate oneself nearly the
different sorts of cancer and their influence on the people, {44}. This data will enable individuals to create
taught choices with regard to their healthcare and conceivably reduce the rate
and mortality of cancer. Besides, remaining updated on the foremost later
headways in cancer ask almost and treatment can give trust for individuals
overseeing with a cancer assurance, {8}. Cancer may be a disease that requires a comprehensive and
multidisciplinary approach to conclusion and treatment. This consolidates
early area through standard screenings, understanding the diverse treatment
choices open such as surgery, chemotherapy, radiation treatment, centered on
medications, immunotherapy, and palliative care, and giving back for patients'
physical, psychosocial, and otherworldly well-being. Additionally, it is basic
to recognize the aberrations in cancer treatment availability between
unmistakable countries and work towards moving forward get to to comprehensive
care for all individuals, regardless of their wage level. By understanding
the causes, chance components, and treatment choices for cancer, individuals
can suitably manage and expect the ailment, {32}. Cancer could be a complex and differing malady that can influence
different organs and tissues within the body. One particular sort of cancer
that warrants dialog is leukemia, which is characterized by the abnormal
production of white blood cells, {42}. Leukemia may be a shape of blood cancer that basically impacts the
bone marrow and blood. It is classified into a couple of subtypes, checking
seriously lymphoblastic leukemia, seriously myeloid leukemia, consistent
lymphocytic leukemia, and incessant myeloid leukemia. These subtypes of leukemia contrast in terms
of their movement, treatment alternatives, and guess. Leukemia could be an
exceedingly heterogeneous illness, with different hereditary changes
contributing to its advancement and movement, {16}. Understanding the atomic and hereditary premise of leukemia has
significantly extended in later a long time. Looking at sedate advancement and
customized helpful mediations for leukemia sufferers, the examination has been
ingested with data. Through the presentation of genomic approaches, basic
information enveloping the beginning of leukemia has been collected. Within the
dominance of leukemia, the enactment of the FLT3 pathway and the JAK-STAT
signaling are basic {27},
embroiling that they are promising targets that can be practicable. There are
recommendations that the availability and handiness of medicines can change
from country to country, unexpected on certain levels of wage. Whereas
comprehensive treatment is allegedly accessible in more than 90% of high-income
nations, less than 15% of low-income nations have get to to such. In
conclusion, information and understanding are key within the fight against
cancer. By remaining educated almost the causes, chance variables, and
treatment choices for cancer, people can make way better choices almost their
healthcare and possibly decrease the frequency and mortality of the malady.
Understanding cancer, active ongoing investment in cancer research {15}, not just of the kind going into
experimental methods and theories, the basics and descriptive aspects of cancer
research, contributes greatly into better comprehending this dreadful illness
and coming up with possibly new breakthrough remedies. In a nutshell, aiming
for a comprehensive concept of cancer matters the most when it comes to proper
managing at all the stages, trying to stop effectively its spread or
implementation of curative measures. Briefly - could be equivalent -
trying to fully explore the cancer process, a key in numerous critical aspects
involving cancer care enforcement.
Leukemia is a type of cancer that affects the
white blood cells, and it has been associated with dysregulation of key
signaling pathways {4}.
These pathways play a crucial role in the development and progression of
leukemia, making them attractive targets for therapeutic intervention. In this
study, we employed a docking-based approach to identify potential drug
candidates that can effectively target these key signaling pathways in
leukemia. By utilizing molecular docking techniques, we aimed to predict the
binding interactions between a library of compounds and the key molecules
involved in leukemia signaling pathways. Through this approach, we aimed to
prioritize compounds that have a high binding affinity and favorable in silico
ADME properties, {26}. By
targeting these key signaling pathways, we hope to discover novel drug
candidates that can effectively inhibit leukemia cell growth and improve
patient outcomes. Furthermore, this approach may provide insights into the
underlying mechanisms of leukemia pathogenesis and aid in the development of
personalized therapeutic strategies for patients with different subtypes of
leukemia. Through the utilization of a docking-based approach, this study aims
to identify potential drug candidates that can effectively target key signaling
pathways in leukemia, {25}. By understanding and targeting these
signaling pathways, we hope to improve treatment outcomes for patients with
leukemia and potentially develop more personalized therapeutic approaches.
Utilizing a docking-based approach, this study aims to identify potential drug
candidates that can effectively target key signaling pathways in leukemia, {33}. By understanding and targeting these
signaling pathways, the study aims to improve treatment outcomes for patients
with leukemia and potentially develop more personalized therapeutic approaches.
The utilization of a docking-based approach in this study aims to identify
potential drug candidates that can effectively target key signaling pathways in
leukemia, {11}. By
understanding and targeting these pathways, the study aims to improve treatment
outcomes for patients with leukemia and potentially develop more personalized
therapeutic approaches, {24}. The
FLT3 quality, moreover known as FMS-like tyrosine kinase 3, may be a
protein-coding quality that plays a significant part in hematopoiesis, the
arrangement of blood cells within the bone marrow, {21}. It is located on chromosome 13q12 and encodes a receptor tyrosine
kinase included within the control of cell survival, multiplication, and
separation. The molecular structure of the FLT3 gene consists of several
important components, {37}. The
FLT3 gene contains 24 exons that are transcribed into a primary mRNA
transcript. The primary mRNA transcript undergoes several post-transcriptional
modifications, including splicing, to remove introns and generate a mature mRNA
molecule, {17}. The
mature mRNA molecule is then translated into the FLT3 protein, which consists
of an extracellular domain, a transmembrane domain, and an intracellular
domain. The extracellular domain of the FLT3 protein is responsible for binding
to its ligand, known as FL, and initiating the signaling cascade, {30}. Upon ligand binding, the intracellular
domain of FLT3 undergoes autophosphorylation at specific tyrosine residues,
driving to actuation of downstream signaling pathways included in cell
multiplication and survival. This activation of downstream signaling pathways
is critical for normal hematopoiesis. Understanding the molecular structure of
the FLT3 gene is important for comprehending its function in hematopoiesis and
its potential role in diseases, such as acute myeloid leukemia, {13}. Discussions about the FLT3 gene's molecular
structure typically involve its role in hematopoiesis, its location on
chromosome 13q12, and the components of the gene, including its exons, mRNA
transcript, and protein structure. In expansion, it is worth noticing that
changes within the FLT3 quality have been recognized in a noteworthy number of
patients with intense myeloid leukemia, which can lead to constitutive
activation of its signaling pathways and contribute to disease progression, {15}. The FLT3 gene, also known as FMS-like tyrosine kinase 3, is an
essential gene involved in hematopoiesis. Its molecular structure consists of
24 exons that are transcribed into a primary mRNA transcript. The primary mRNA
transcript undergoes post-transcriptional modifications, including splicing, to
generate a mature mRNA molecule, {34}. This mature mRNA molecule is translated into the FLT3 protein, which
comprises of an extracellular space, a transmembrane space, and an
intracellular space. The extracellular space of the FLT3 protein is capable for
authoritative to its ligand, FL, and starting signaling pathways included in
cell multiplication and survival In outline, the FLT3 quality plays a pivotal
part in hematopoiesis and its atomic structure comprises of 24 exons, {23}. . The FLT3 gene is involved in
hematopoiesis and its molecular structure includes 24 exons that are
transcribed into a primary mRNA transcript.
ROLE of FLT3 GENE
The main functions and roles of FLT3 include:
Delving into the
therapeutic domain closely associated with cancer, particularly acute myeloid
leukemia (AML), we encounter FLT3. Explored as a target for treatment,
FLT3 inhibitors have emerged, akin to tyrosine kinase inhibitors. These
inhibitors endeavor to impede aberrant signaling emanating from the abnormal
FLT3 signaling uniformly present within cancerous cells. We discover that
such investigations and advancements originated from prior knowledge of FLT3's
correlation with the genesis and exacerbation of cancer cells. As affirmed by
{35}, diverse trials and attenuations have been attempted for FLT3 throughout
these years by various entities. Uncertain as to the precise outcomes of these
initiatives, we confront a dubious conception of definitive findings.
1. Hematopoiesis
Regulation: Differentiation and proliferation of
hematopoietic stem regulation involves FLT3. Quite vital in different
blood cell lineages development- red blood, white blood and platelets role is
played by it cells of postorative kinds hematopoiesis and differentiation into
a part of proliferation onymous is also FLT3.
2. Immune
System Function: FLT3 is particularly important for the
development and maturation of dendritic cells, which are crucial for the
initiation of immune responses, {38}. Dendritic cells process and present
antigens to T cells, initiating the adaptive immune response.
- Cell
Survival and Apoptosis: FLT3 signaling contributes to cell survival by
activating pathways that prevent apoptosis (programmed cell death). This
is important for the maintenance and expansion of hematopoietic stem and
progenitor cells.
4. Oncogenesis
in Acute Myeloid Leukemia (AML): Alterations in the FLT3
gene manifest frequently in acute myeloid leukemia (AML), a neoplasm of the
blood. These mutations encompass internal tandem duplications and point
mutations in the tyrosine kinase domain. These mutations induce constitutive
activation of FLT3 signaling, engendering uncontrolled cell proliferation and
persistence. Targeting these FLT3 mutations has evolved into a consequential
therapeutic maneuver in AML, {22}.
5. Target
for Therapy: Due to its involvement in cancer, particularly
in AML, FLT3 has been identified as a therapeutic target. Various FLT3
inhibitors, such as tyrosine kinase inhibitors, have been developed and tested
for their ability to block aberrant FLT3 signaling in cancer cells, {35}.
LITERATURE REVIEW
(Natarajan et al., 2019) displayed a
worldview move within the treatment of incessant myelogenous leukemia (CML)
with focused on treatment utilizing exceedingly particular tyrosine kinase
inhibitors (TKIs). In spite of this advance, sedate resistance caused by
changes within the kinase space presents a challenge to helpful adequacy. This
think about points to address this issue by examining elective restorative
targets other than the BCR-ABL oncoprotein. In specific, the center in BCR-ABL
is on blocking the interaction between development factor-binding protein-2
(Grb-2) and phosphorylated tyrosine (Y177), which is an vital step within the
enactment of Ras and PI3K/AKT signaling pathway (Audrito et al., 2011).
Utilizing computer based methods involving drug design researchers identified
compounds of inhibiting the binding of Grb 2, to Y177 by targeting the binding
site of the BCR domain (Xu et al., 2016). Examination of gene expressions in
the GEO dataset revealed associations with processes such as hematopoietic cell
line, NK cell mediated cytotoxicity, NF κB and chemokine signaling, cytokine
cytokine receptor interaction, histidine metabolism and transcriptional
dysregulation in cancer (Bajbouj et al., 2018). The BCR domain structure was
simulated using the SPARKS X tool resulting in a Z score of 8.21. By analyzing
gene expression profiles docked to BCR, a list of drugs was generated. Through
Schrodinger XP docking studies compounds like diphosphopyridine nucleotide,
hesperidin, butyrosine, ovoflavin and nor dihydroguaretic acid were identified
for their interaction near the active binding site containing Y177 (Barrett et
al. 2007). Validation was carried out using iGEMDOCK along, with Parallelized
Open Babel and AutoDock suit Pipeline (POAP). This study not as it were growing
the run of drugs for unused signs, but too offers the plausibility of
combination treatment with standard drugs utilized within the treatment of CML.
Be that as it may, the adequacy of these reusable drugs requires assist
considers with considers in vitro and in vivo.
(Yang et al., 2023) highlighted that
transformations in FLT3‐ITD and FLT3‐TKD contribute to over 30–35% of
AML cases, supporting the enactment of FLT3 protein and activating downstream
signaling proteins included in cell expansion, separation, and survival. In
spite of the accessibility of various inhibitors in clinical hone focusing on
these changes, the by and large survival rate for AML patients beneath medicine
remains at 5 years
(Singh et al., 2017). To tackle this issue researchers conducted simulations
and studies, on selected plant based compounds against the FLT3 protein
receptor in search of medications for FLT3 induced AML (American Physiological
Society, 2019). They used docking simulations with the human FLT3 protein
target (PDB ID; 6JQR). Tested 313 plant-based compounds alongside standard
anticancer drugs like Sorafenib and Gilteritinib (Choudhary et.al., 2020). The
proteins structure was obtained from the Protein Data Bank. Prepared using
Biovia Discovery Studio. The structures of the plant based compounds were
sourced from the NCBI PubChem database. Prepared using Open Babel and VConf
program. PyRx on Autodock Vina was used for docking and the ADMET properties of
the promising compounds were assessed using SwissADME and pkCMS web servers.
The findings revealed that compounds such as glabridin, ellipticine along with
its derivatives (elliptinium and 9 methoxyellipticine) mezerein, ursolic acid,
formononetin, cycloartocarpesin, hypericin, silymarin and indirubin exhibited
binding affinities compared to sorafenib and gilteritinib. These performing
compounds demonstrated binding properties as well as favorable ADMET profiles
positioning them as potential starting points or candidates for new drug
discovery, against FLT3 induced AML (Sweta et al., 2019).
(Islam et al., 2024) set up that roughly 30%
of patients with intense myeloid leukemia (AML) harbor enacting transformations
in Cat McDonough Sarcoma (FMS)-like tyrosine kinase 3 (FLT3), making it a
promising restorative target for AML treatment. Given the wide range of
tyrosine kinase inhibitors accessible, which have demonstrated compelling in
obstructing different stages of cell multiplication in cancer, our ponder is
centered on recognizing strong antileukemic specialists against the FLT3 gene.
To accomplish this objective, we at first chosen well-known antileukemic
medicate candidates to make a structure focused pharmacophore is used to
analyze 217,77093 compounds from the Zinc database, for screening (Adelusi et
al., 2022). The distinguished hit compounds experienced docking against the
target protein, and the best four compounds were at that point subjected to
ADMET examination. Utilizing thickness utilitarian hypothesis (DFT), the ponder
conducted geometry optimization, the evaluation of the frontier orbitals (FMO)
HOMO LUMO and global reactivity descriptors confirms a profile and reactivity
ranking, for the selected candidates (Chattaraj and giri 2007). In comparison
to control compounds, the docking comes about uncovered significant
authoritative energies (-11.1 to −11.5 kcal/mol) for the four compounds with
FLT3. The physicochemical and ADMET expectations adjusted with the bioactive
and secure nature of these candidates. Atomic flow (MD) examination affirmed
prevalent authoritative fondness and soundness compared to gilteritinib,
showing the potential of these compounds as FLT3 inhibitors. This computational
approach recognizes vigorous and secure antileukemic operators, justifying
advance in-vivo and in-vitro examinations for comprehensive validation.
Within the 2022 think about, (Abohassan et
al., 2022) centered on Intense Myeloid Leukemia (AML), a cancer stamped by
disturbed cell signaling. They highlighted the significance of focusing on the
PI3K/AKT pathway (Mirza & Karim, 2023) to stifle AML cell development
successfully. To move forward treatment results and decrease side impacts
(Greim et al., 2014), the analysts supported for customized drugs. They
utilized a combined approach to distinguish double inhibitors for PI3K and AKT
(Mirza & Karim, 2023), illustrating their viability in controling AML cell
proliferation. The investigate
included progressed screening methods to find little atoms within the
ChemBridge library that emphatically tie to particular targets inside the PI3K
pathway. The group chosen compounds with negligible off-target impacts for
encourage examination, (Woods and Vassiliou, 2014). Among the recognized
compounds, one named C16 showed up basic guarantee. It shown strong enjoying
for key proteins inside the PI3K pathway and outlined effective anti-cancer
impacts in AML cells.
(Helmi et al., 2024) Intense myeloid leukemia
(AML) could be a deadly shape of cancer, characterized by the visit
upregulation of B cell lymphoma 2 (BCL2), a significant player within the
survival of both AML cells and AML stem cells. This consider pointed to find
novel plant-based compounds focusing on BCL2 and evaluate their
pharmacokinetics and harmfulness through in-silico tools. The investigate
strategy included in-silico screening of phytochemicals against the BCL2
dynamic location utilizing the PyRx 0. 8 AutoDock instrument. In this way,
in silico pharmacokinetic and poisonous quality expectations were conducted,
(usher et al., 2017). Protein-protein interaction examination utilizing the
STRING database evaluated intelligent between BCL2 and its neighboring
proteins, (sabe et al., 2021). nA add up to of 1106 terpenoids compounds
experienced screening to assess their authoritative fondness towards BCL2, (Del
Prado-Audelo et al., 2021). Among them, five common compounds displayed strong
official to the BCL2 protein, outperforming the official energies of the
positive control (venetoclax). These compounds were distinguished through
careful screening, nitty gritty interaction examination, and visual
assessments. Critically, they illustrated higher official energies and were
found to tie to key BCL2 buildups, having favorable drug-like properties, (fan
et al., 2023). In conclusion, these recognized phytochemicals talk to a essential
starting step in cure disclosure for managing AML. In any case, exploratory
endorsement is fundamental to optimize these phytochemicals as potential BCL2
inhibitors.
Ø
Windows XP or Windows 7
Ø
Discovery Studio Visualizer
http://accelrys.com/products/discovery-studio/visualization-download.php
Docking
suits (Schrödinger Maestro, Windows-x64) employing a virtual screening
workflow. This workflow utilized XP hits for each official location. The
proteins was arranged by limited minimization utilizing drive field OPLS4e. The
network sites were created using a Float receptor grid generator with a
distance of 20 angstroms. The central points of the frameworks were identified
through observations, on the target protein. Ligands were prepared using the
force field OPLS4e. Potential states were generated within pH range of 7.0 ±
2.0. Docking scores are reported in kilocalories, per mole, where lower numbers
indicate binding affinity.
PLAN OF WORK
•
In Silico Docking
Studies
•
Ligand Preparation
•
Pharmacokinetics
Analyses: ADME/ Toxicology Properties
•
Protein Preparation
•
Molecular Docking
Using Schrödinger Maestro
Table
1: 1 ETE
Protein and its identification number
|
Protein
|
PDB
ID.
|
|
1ETE
|
P49771
|
SELECTED PHYTOCONSTITUENT USING LIPINKI’S
RULE OF FIVE
With Lipinski's Rule of Five, the
phyto-constituents were screened based on the following criteria: a molecular weight
of less than 500 Daltons, a partition coefficient (log P) of less than 5, no
more than 10 hydrogen bond acceptors, no more than 5 hydrogen bond donors, and
a polar surface area not exceeding 140 Å.
Table 2:
Selected phytoconstituent using lipkins rule of five
|
PHYTOCONSTITUENT
|
MOLECULAR WEIGHT
|
LOG P ( PARTITION COEFF)
|
HYDROGEN BOND DONOR
|
HYDROGEN BOND ACCEPTOR
|
POLAR SURFACE AREA
|
|
Curcumin
|
368.38
|
3.24
|
2
|
6
|
93.1
|
|
Resveratrol
|
228.25
|
3.1
|
3
|
3
|
60.7
|
|
Artemisinin
|
282.33
|
2.8
|
0
|
5
|
54
|
|
Berberine
|
336.4
|
3.6
|
0
|
4
|
40.8
|
|
Ellagic acid - Berries, Pomegranates
|
302.19
|
1.1
|
4
|
8
|
134
|
|
WGenistein - Soybeans
|
270.24
|
2.7
|
3
|
5
|
87
|
|
Sulforaphane - Cruciferous vegetables
|
177.3
|
1.4
|
0
|
4
|
80.7
|
|
Allicin - Garlic
|
162.3
|
1.3
|
0
|
3
|
61.6
|
|
Gingerol - Ginger
|
294.4
|
2.5
|
2
|
4
|
66.8
|
|
Capsaicin - Chili peppers
|
305.41
|
3.6
|
2
|
3
|
58.6
|
|
Withaferin A - Ashwagandha
|
470.6
|
3.8
|
2
|
6
|
96.4
|
|
Pterostilbene - Blueberries
|
256.3
|
3.8
|
1
|
3
|
38.7
|
|
Guggulsterone
|
312.4
|
3.9
|
0
|
2
|
34.1
|
|
Fisetin – Strawberries
|
286.24
|
2
|
4
|
6
|
107
|
|
Apigenin - Parsley, Chamomile
|
270.24
|
1.7
|
3
|
5
|
87
|
|
Kaempferol - Broccoli, Kale
|
286.24
|
1.9
|
4
|
6
|
107
|
|
Diallyl disulfide - Allium vegetables
|
146.3
|
2.2
|
0
|
2
|
50.6
|
|
Naringenin - Citrus fruits
|
272.26
|
2.4
|
3
|
5
|
87
|
|
Thymoquinone - Black seed (Nigella sativa)
|
164.2
|
2
|
0
|
2
|
34.1
|
|
Luteolin - Celery, Peppers
|
286.24
|
1.4
|
4
|
6
|
107
|
|
Nimbolide - Neem
|
466.5
|
2.2
|
0
|
7
|
92
|
|
Emodin - Aloe vera, Rhubarb
|
270.24
|
2.7
|
3
|
5
|
94.8
|
PREADMET FOR ADME AND TOXICOLOGY PREDICTION
The PreADMET is important in prediction of
the toxicology profile and pharmacokinetic profile e.g Absorption, distribution
Metabolism, Excretion, using parameters like, Human intestinal Absorption,
CaCO-2 permeability, Blood brain barrier
penetration, plasma protein binding, and buffer solubility.
Table 3:
PREADMET for ADME and toxicology prediction
|
Phytoconstituent
|
B.B.B
|
PPB
|
HIA
|
Caco2
|
Buffer Solubility
|
PUBCHEM. I.D
|
|
Resveratrol
|
1.73
|
100
|
88.48
|
5.19
|
33.99
|
445154
|
|
Artemisinin
|
1.30488
|
93.34
|
96.3
|
30.33
|
565.6
|
68827
|
|
Berberine
|
0.6932
|
58.54
|
97.9
|
55.58
|
8.02
|
2353
|
|
Allicin - Garlic
|
1.22
|
4.34
|
98
|
21.7
|
1139.18
|
65036
|
|
Gingerol - Ginger
|
1.474
|
100
|
98
|
24.5
|
780.2
|
442793
|
|
Capsaicin - Chili peppers
|
4.099
|
92.86
|
91.96
|
37.37
|
1546.08
|
1548943
|
|
Pterostilbene - Blueberries
|
1.3224
|
100
|
92.5
|
45.92
|
21.9
|
5281727
|
|
Guggulsterone
|
0.911
|
100
|
95.74
|
28.18
|
242.897
|
6450278
|
|
Diallyl disulfide - Allium vegetable
|
1.37
|
98.03
|
99.07
|
22.01
|
24.73
|
16590
|
|
Thymoquinone - Black seed
(Nigella sativa)
|
1.7894
|
100
|
99.29
|
23.03
|
357.209
|
10281
|
RESULTS
This chapter meticulously
examines and interprets the results obtained from the conducted experiments,
aiming to elucidate the key findings and their significance within the context
of the research objectives.

Figure 1: Gingerol binding with 1ete protein
(442793)

Figure 2: Allicin binding with 1ETE (65036)

Figure 3: Guggulsterone binding with 1ETE
(6450278)

Figure 4: Resveratrol binding with 1ETE
(445154)

Figure 5: capsaicin binding with 1ETE
(1548943)

Figure 6:
Berberine binding with 1ETE (2353)

Figure 7: Thymoquinone binding with 1ETE
(10281)

Figure 8: Pterostilbene binding with 1ETE
(5281727)

Figure 9: Artemisinin binding with 1ETE
(68827)

Figure 10 : Artemisinin binding with 1ETE
(68827)

Figure 11: Pterostilbene binding with 1ETE
(5281727)

Figure 12: Thymoquinone binding with 1ETE
(10281)
Figure 13:
Berberine binding with 1ETE
(2353)

Figure 14: capsaicin binding with 1ETE
(1548943)

Figure 15: Resveratrol binding with 1ETE
(445154)

Figure 16: Guggulsterone binding with 1ETE
(6450278)

Figure 17: Allicin binding with 1ETE (65036)

Figure 18: Gingerol binding with 1ete protein
(442793)
INFORMATION ON TARGET AND COMPONENTS FOR MOLECULAR DOCKING
This table presents the binding
energies (docking scores) of the selected protein in interaction with the
ligands.
Table 4:
Overall binding result/ docking score
|
Target
|
PDB ID
|
Components
|
Numerical identifier
|
Binding Energy/ Docking score
|
|
Fms-related tyrosine
kinase 3 ligand
|
1 ETE
|
Resveratrol
|
445154
|
-5.606
|
|
|
|
Artemisinin
|
68827
|
-2.820
|
|
|
|
Berberine
|
2353
|
-3.690
|
|
|
|
Allicin - Garlic
|
65036
|
-1.869
|
|
|
|
Gingerol - Ginger
|
442793
|
-1.869
|
|
|
|
Capsaicin - Chili peppers
|
1548943
|
-2.908
|
|
|
|
Guggulsterone
|
6450278
|
-3.449
|
|
|
|
Thymoquinone - Black seed (Nigella sativa)
|
10281
|
-4.453
|
|
|
|
Pterostilbene - Blueberries
|
5281727
|
-5.218
|
CONCLUSION
These studies utilized
molecular docking to explore potential medications within an approved bioactive
compound database. Various phytoconstituents were screened using Lipinski's
rule and preADMET for ADME and toxicology prediction. Specifically, we
investigated the interaction of the protein 1ETE with these phytoconstituents,
focusing on their potential to inhibit the Flt3 gene associated with leukemia.
This groundwork sets the stage for computational drug discovery aimed at
developing new compounds to target the overexpression of the Flt3 gene in
cancer. Among the compounds examined, resveratrol and pterostilbene emerged
with promising binding energies. Resveratrol exhibited a binding score of
-5.606, forming conventional hydrogen bonds with histamine (HIS A: 8) and
asparagine (ASP A: 3) within the protein. Additionally, interactions with van
der Waals forces were observed with several amino acids. Similarly,
pterostilbene exhibited a binding score of -5.218 and interacted via
conventional hydrogen bonds with HIS A: 8 and ASP A: 3, along with weak van der
Waals forces with other amino acids.
In summary, our research underscores the
potential of resveratrol and pterostilbene as candidates for inhibiting the
Flt3 gene. Both compounds exhibited favorable binding energies and shared
common amino acid interactions within the protein binding site. Further
investigations can be pursued to explore their efficacy as potential treatments
for leukemia.
REFERENCE
1. Abohassan
M, Alshahrani M, Alshahrani MY, Rajagopalan P. Insilco and Invitro approaches
identify novel dual PI3K/AKT pathway inhibitors to control acute myeloid
leukemia cell proliferations. Medical Oncology. 2022 Oct 8;39(12):249.
2. Adelusi,
T. I., Oyedele, A. K., Abdeen, I. D.B., Ogunlana, T., Adeyemi, R. O., Ukachi,
C. D., Idris, M. O., Olaoba, O. T., Adedotun, I. O., Kolawole, O. E., Xiaoxing,
Y., Abdul-Hammed, M.. (2022). Molecular modeling in drug discovery. Informatics
Medicine Unlocked, 29, 100880. https://doi.org/10.1016/J.IMU.2022.100880
3. American
Physiological Society. (2019). FMS-like tyrosine kinase 3/FLT3: From basic
science to clinical implications. https://journals.physiology.org/doi/full/10.1152/physrev.00029.2018
4. Arthur
DE, Uzairu A. Molecular docking studies on the interaction of NCI anticancer
analogues with human Phosphatidylinositol 4, 5-bisphosphate 3-kinase catalytic
subunit. Journal of King Saud University-Science. 2019 Oct 1;31(4):1151-66.
5. Audrito
V, Vaisitti T, Rossi D, et al. Nicotinamide blocks proliferation and induces
apoptosis of chronic lymphocytic leukemia cells through activation of the
p53/miR-34a/SIRT1 tumor suppressor network. Cancer Res. 2011;71:4473–83.
6. Bajbouj
K, Shafarin J, Hamad M. High-dose deferoxamine treatment disrupts intracellular
Iron homeostasis, reduces growth, and induces apoptosis in metastatic and
nonmetastatic breast cancer cell lines. Technol Cancer Res Treat.
2018;17:1533033818764470.
7. Barrett
T, Troup DB, Wilhite SE, et al. NCBI GEO: mining tens of millions of expression
profiles--database and tools update. Nucleic Acids Res. 2007;35:D760–5.
8. Becker
S. A historic and scientific review of breast cancer: The next global
healthcare challenge. International Journal of Gynecology & Obstetrics.
2015 Oct;131:S36-9.
9. Chattaraj,
P. K., & Giri, S. (2007). Stability, Reactivity, and Aromaticity of
Compounds of a Multivalent Superatom. The Journal of Physical Chemistry. A,
111(43), 11116–11121. https://doi.org/10.1021/JP0760758
10. Choudhary,
M. I., Shaikh, M., Tul-Wahab, A., & Ur-Rahman, A. (2020). In silico
identification of potential inhibitors of key SARS-CoV-2 3CL hydrolase (Mpro)
via molecular docking, MMGBSA predictive binding energy calculations, and
molecular dynamics simulation. PloS One, 15(7), e0235030. https://doi.org/10.1371/journal.pone.0235030
11. Davis
AS, Viera AJ, Mead MD. Leukemia: an overview for primary care. American family
physician. 2014 May 1;89(9):731-8.
12. Del
Prado-Audelo ML, Cortes H, Caballero-Floran IH, Gonzalez-Torres M,
Escutia-Guadarrama L, et al. Therapeutic applications of terpenes on
inflammatory diseases. Frontiers in Pharmacology, (2021); 12: 704197.
13. Egbuna
C, Patrick-Iwuanyanwu KC, Onyeike EN, Khan J, Alshehri B. FMS-like tyrosine
kinase-3 (FLT3) inhibitors with better binding affinity and ADMET properties
than sorafenib and gilteritinib against acute myeloid leukemia: in silico
studies. Journal of Biomolecular Structure and Dynamics. 2022 Dec
12;40(22):12248-59.
14. Fan M,
Yuan S, Li L, Zheng J, Zhao D, et al. Application of terpenoid compounds in
food and pharmaceutical products. Fermentation, (2023); 9(2): 119.
15. Gilliland
DG, Griffin JD. The roles of FLT3 in hematopoiesis and leukemia. Blood, The
Journal of the American Society of Hematology. 2002 Sep 1;100(5):1532-42.
16. Gilliland
DG, Jordan CT, Felix CA. The molecular basis of leukemia. ASH Education Program
Book. 2004 Jan 1;2004(1):80-97.
17. Gokhale
P, Chauhan AP, Arora A, Khandekar N, Nayarisseri A, Singh SK. FLT3 inhibitor
design using molecular docking based virtual screening for acute myeloid
leukemia. Bioinformation. 2019;15(2):104.
18. Grove
CS, Vassiliou GS. Acute myeloid leukaemia: a paradigm for the clonal evolution
of cancer? Dis Model Mech. 2014;7:941–51.
19. Helmi
N. Identification of therapeutic phytochemicals targeting B-cell lymphoma 2
(BCL2) as anti-acute myeloid leukemia agents: An in-silico approach. Advancements
in Life Sciences. 2024 Jan 8;10(4):670-4.
20. Islam
MR, Osman OI, Hassan WM. Identifying novel therapeutic inhibitors to target
FMS-like tyrosine kinase-3 (FLT3) against acute myeloid leukemia: a molecular
docking, molecular dynamics, and DFT study. Journal of Biomolecular Structure
and Dynamics. 2024 Jan 2;42(1):82-100.
21. Kampen
KR. The discovery and early understanding of leukemia. Leukemia research. 2012
Jan 1;36(1):6-13.
22. Kiyoi
H, Yanada M, Ozekia K. Clinical significance of FLT3 in leukemia. International
journal of hematology. 2005 Aug;82:85-92.
23. Kiyoi,
H. and Naoe, T., 2002. FLT3 in human hematologic malignancies. Leukemia &
lymphoma, 43(8), pp.1541-1547.
24. Kuchenbauer
F, Kern W, Schoch C, Kohlmann A, Hiddemann W, Haferlach T, Schnittger S.
Detailed analysis of FLT3 expression levels in acute myeloid leukemia.
Haematologica. 2005 Jan 1;90(12):1617-25.
25. Levis
M. FLT3 mutations in acute myeloid leukemia: what is the best approach in
2013?. Hematology 2013, the American Society of Hematology Education Program Book.
2013 Dec 6;2013(1):220-6.
26. Levis
M, Small D. FLT3: ITDoes matter in leukemia. Leukemia. 2003 Sep;17(9):1738-52.
27. Lowenberg
B, Downing JR, Burnett A. Acute myeloid leukemia. New England Journal of
Medicine. 1999 Sep 30;341(14):1051-62.
28. Mirza
Z, Karim S. Structure-Based Profiling of Potential Phytomolecules with AKT1 a
Key Cancer Drug Target. Molecules. 2023 Mar 13;28(6):2597.
29. Natarajan
A, Thangarajan R, Kesavan S. Repurposing Drugs by In Silico Methods to Target
BCR Kinase Domain in Chronic Myeloid Leukemia. Asian Pacific Journal of Cancer
Prevention: APJCP. 2019;20(11):3399.
30. Ozeki
K, Kiyoi H, Hirose Y, Iwai M, Ninomiya M, Kodera Y, Miyawaki S, Kuriyama K,
Shimazaki C, Akiyama H, Nishimura M. Biologic and clinical significance of the
FLT3 transcript level in acute myeloid leukemia. Blood. 2004 Mar
1;103(5):1901-8.
31. Parker
SK, Williams HM, Turner N. Modeling the antecedents of proactive behavior at
work. Journal of applied psychology. 2006 May;91(3):636.
32. Pei H,
Guo W, Peng Y, Xiong H, Chen Y. Targeting key proteins involved in
transcriptional regulation for cancer therapy: Current strategies and future
prospective. Medicinal Research Reviews. 2022 Jul;42(4):1607-60.
33. Primavera
E, Palazzotti D, Barreca ML, Astolfi A. Computer-Aided Identification of
Kinase-Targeted Small Molecules for Cancer: A Review on AKT Protein.
Pharmaceuticals. 2023 Jul 11;16(7):993.
34. Quentmeier
H, Reinhardt J, Zaborski M, Drexler HG. FLT3 mutations in acute myeloid
leukemia cell lines. Leukemia. 2003 Jan;17(1):120-4.
35. Rombouts
WJ, Blokland I, Löwenberg B, Ploemacher RE. Biological characteristics and
prognosis of adult acute myeloid leukemia with internal tandem duplications in
the Flt3 gene. Leukemia. 2000 Apr;14(4):675-83.
36. Singh
VK, Chang HH, Kuo CC, Shiao HY, Hsieh HP, Coumar MS. Drug repurposing for
chronic myeloid leukemia: in silico and in vitro investigation of DrugBank
database for allosteric Bcr-Abl inhibitors. Journal of Biomolecular Structure
and Dynamics. 2017 Jun 11;35(8):1833-48.
37. Small
D. FLT3 mutations: biology and treatment. ASH Education Program Book. 2006 Jan
1;2006(1):178-84.
38. Stirewalt
DL, Radich JP. The role of FLT3 in haematopoietic malignancies. Nature Reviews
Cancer. 2003 Sep 1;3(9):650-65.
39. Sabe
VT, Ntombela T, Jhamba LA, Maguire GEM, Govender T, et al. Current trends in
computer aided drug design and a highlight of drugs discovered via
computational techniques: A review. European Journal of Medicinal Chemistry,
(2021); 224: 113705.
40. Sweta
J, Khandelwal R, Srinitha S, Pancholi R, Adhikary R, Ali MA, Nayarisseri A,
Vuree S, Singh SK. Identification of high-affinity small molecule targeting
IDH2 for the clinical treatment of acute myeloid leukemia. Asian Pacific
journal of cancer prevention: APJCP. 2019;20(8):2287.
41. Usha
T, Shanmugarajan D, Goyal AK, Kumar CS, Middha SK. Recent Updates on
Computer-aided Drug Discovery: Time for a Paradigm Shift. Current Topics in
Medicinal Chemistry, (2017); 17(30): 3296-3307.
42. Wang
Y, Wu X, Ren Z, Li Y, Zou W, Chen J, Wang H. Overcoming cancer chemotherapy
resistance by the induction of ferroptosis. Drug Resistance Updates. 2023 Jan
1;66:100916.
43. Yang
Y, Yang Y, Shen Y, Liu J, Zeng Y, Wei C, Liu C, Pan Y, Guo Q, Zhong F, Guo L.
Exploring the pharmacological mechanisms of Shuanghuanglian against T-cell
acute lymphoblastic leukaemia through network pharmacology combined with
molecular docking and experimental validation. Pharmaceutical biology. 2023 Dec
31;61(1):259-70.
44. Zhang
S, Sun K, Zheng R, Zeng H, Wang S, Chen R, Wei W, He J. Cancer incidence and mortality
in China, 2015. Journal of the National Cancer Center. 2021 Mar 1;1(1):2-11.