Pharmacophore Modeling and Molecular Docking of Flavonoid Derivatives in Abelmoschus manihot Against Human Estrogen Receptor Alpha of Breast Cancer
by Recky Patala ★ , Viani Anggi
Academic editor: Keerthic Aswin
Sciences of Pharmacy 1(2): 1-9 (2022); https://doi.org/10.58920/sciphar01020001
This article is licensed under the Creative Commons Attribution (CC BY) 4.0 International License.
30 Aug 2022
21 Sep 2022
26 Sep 2022
03 Oct 2022
Abstract: Tamoxifen is the most commonly used anti-estrogen adjuvant therapy for estrogen receptor-positive breast cancer. However, it is associated with an increased risk of some serious side effects, such as uterine cancer, stroke, and pulmonary embolism. The flavonoid compounds in the leaves of A. manihot inhibited the growth of 4T1 breast cancer cells at a CTC50 concentration of 185.06 μg/ml. Therefore, this study aims to examine the molecular interactions and pharmacophore modeling based on the interaction of 4-OHT with human ER, followed by the molecular docking of the flavonoid derivatives with human ERα. The molecular docking simulations and 3D structure-based pharmacophore models were used to identify the molecular interactions of flavonoid derivatives in A. manihot on estrogen receptors (ERα) (PDB ID: 3ERT). The results showed that the binding energies of the flavonoid derivatives in isorhamnetin and isoquercitrin were -8.68 kcal/mol and -8.75 kcal/mol, respectively. This compound also interacted with Arg394 and Glu353 important amino acid residues in the ERα-binding pocket. Meanwhile, the pharmacophore fit scores of isorhamnetin and isoquercitrin were 82.36% and 84.91%, respectively. The flavonoid derivatives in A. manihot had pharmacophore fit resulting from the 4-OHT complex with ER, and therefore they had potential as ERα antagonists. Out of the 10 flavonoid derivatives, isorhamnetin and isoquercitrin showed the best docking scores and could be used as candidates for new anti-breast cancer drugs with antagonistic activity against ERα.
Keywords: Abelmoschus manihotEstrogen Receptor AlphaMolecular DockingPharmacophore
1. Introduction
Cancer is currently the leading cause of death worldwide. In
2020, almost 10 million deaths were registered as a result of cancer, and
according to report, breast cancer ranks first with 2.26 million cases and
685,000 deaths (1). Estrogen receptors are the human prognostic marker used to
identify tumors in breast tissue (2), and they consist of two subtypes, ERα and
ERβ, which have different affinities for estrogen. ERα is a transcription
regulator-activated ligand as a major regulator of breast differentiation and
proliferation (3). Furthermore, it plays an important role in the development
and progression of hormone-dependent breast cancer (4). Tamoxifen, as an
antiestrogen can block estrogen signaling through a mechanism of competition
with endogenous estrogens to bind to the estrogen receptor and alter its
activity as a regulator of gene transcription. Additionally, it has
antagonistic activity in the breast but is an agonist in the uterus and bone
(5). Tamoxifen and its active metabolite 4-hydroxytamoxifen (4-OHT) have
cytotoxic activity against MCF-7 breast cancer cells with an IC50 of 5 μM and 1
μM (6). However, the effectiveness of tamoxifen is limited by the presence of
intrinsic resistance. Amplification and overexpression of COPS5 (complex
subunit COP9) was a major cause of tamoxifen resistance in 86.7% of patients
with ERα-positive breast cancer. Overexpression of COPS5 through isopeptidase
activity leads to proteasome-mediated NCoR degradation, which is a major
repressor of ERCC, and therefore, alternative medicine is needed (7).
Flavonoids are one of the promising natural remedies for
breast cancer (8). One of the plants that contain active flavonoid compounds is
Abelmoschus manihot L. Medik. Most people in Palu and Manado cities, Indonesia
use the leaves as food, which were reported to have total flavonoids of 61.763%
(9). It was reported that the flavonoid compounds in the leaves of A. manihot
inhibited the growth of 4T1 breast cancer cells at a concentration of 50%
inhibitory cell growth (CTC50) of 185.06 μg/ml (10). Furthermore, flavanoid
compounds can act as selective estrogen receptor modulators (SERMs) as they are
a group of compounds with a C6-C3-C6 chemical structure. SERMs can enter the
cell and then bind to the ER, forming a complex bond. This complex binding
binds to the Estrogen Response Element (ERE), which is located near the gene
whose transcription is controlled. Additionally, the complex will activate
nuclear receptor co-repressor (NCoR) protein and suppress cancer cell
replication, therefore its proliferation can be controlled (11,12). Currently,
studies on pharmacophore and molecular docking of flavonoid derivatives in A.
manihot to ERα are very limited. Therefore, it is necessary to conduct
pharmacophore modeling tests based on the interaction of 4-OHT with human ERα
followed by molecular docking of flavonoid derivatives of A. manihot with human
ERα.
2. Experimental Section
2.1 Hardware and Software
The hardware used is a computer with Windows 10 64-bit OS,
AMD A6-7310 APU Processor with AMD Radeon R4 Graphic 2.00 GHz and 6 GB RAM. The
software is ChemDraw professional 15.0 (Academic License), LigandScout 4.4.5
Advanced (Universitas Padjadjaran License), AutoDock 4.2.6, AutoDockTools 1.5.6
(The Scripps Research Institute), and BIOVIA Discovery Studio 2021 (Academic
License).
2.2 Preparation of Ligands and Molecular Docking
3D X-ray crystallographic structure of ERα in complex with
4-OHT (PDB ID: 3ERT) crystallized and stored by Shiau et al., (1998) 1.90 Å
resolution downloaded from the Protein Data Bank online (https://www.rcsb.org
/structure/3ERT) (13). The ligands were separated from the receptor structure
using the BIOVIA Discovery Studio 2021 R2 client. The 3D-mangostin structure
and its derivatives as ligands were optimized by ChemOffice 2010 and ChemDraw
Ultra 12.0 (PerkinElmer Inc.) and LigandScout 4.4.5 Advanced (Inte: Ligand
GmbH). Molecular docking simulations were carried out according to previous
validation studies (14). ERα receptors and ligands were prepared for docking
simulation using AutoDockTools 1.5.6. Furthermore, receptors as macromolecules
are added with Kollman charges, while ligands are added with Gasteiger charges
(15). The grid parameter file corresponds to a grid consisting of 40×40×40
points spaced 0.375Å and centered on the active edge ERα (x = 30,010, y =
-1,913, and z = 24,207). AutoDock 4.2.6 (The Scripps Research Institute) was
used to perform molecular docking simulations. The docking parameter file
corresponds to the Lamarckian Genetic Algorithm (LGA) with 100 run counts, 150
population sizes, 2,500,000 energy evaluations, 0.02 gene mutation rate, and
0.8 crossover rate (16). The conformational results from the simulation were
grouped using the root mean square deviation (RMSD) tolerance of 1.0. The
ligand conformation with the lowest free bond energy (∆G) was selected from the
best cluster, and the best ligand conformation was used for the next analysis
stage. The receptor-ligand complex from the docking simulation was visualized
using the BIOVIA Discovery Studio Visualizer 2021. The determination of ligand
interaction features for each pose in the receptor-binding pocket was analyzed
with LigandScout 4.4.5 Advanced Inte: Ligand GmbH. Wina, Austria (8).
2.3 3D Structure-based Pharmacophore Modeling
Structure-based 3D pharmacophore modeling was derived from
an ERα X-ray structure complexed with 4-OHT (PDB ID: 3ERT) using Ligandscout
4.4.5 Advanced (17). Feature validation was performed by filtering 626 active
sets and 20,773 bait sets obtained from the Database of Useful Decoys (18). The
flavonoid derivatives in A. manihot were screened virtually using a 3D
structure-based pharmacophore model validated with the LigandScout 4.4.5
advanced algorithm. The result of this process is the adjustment value of the
pharmacophore. The pharmacophore-fit score was used to measure the feature and
geometry similarity of each achieved compound based on a 3D structure with a
feature pharmacophore model with 4 feature counts removed for the combined
pharmacophore, 10.0% optional threshold partial adaptation feature, and 1.0
feature tolerance scale factor.
3. Result and Discussion
Two hydrogen bonds were observed in the interaction between
4-OHT and human ERα. Hydrogen bonding was observed in the interaction between
4-OHT and human ERα bound to Glu353 as a hydrogen bond donor (HBD) and Arg394
as a hydrogen bond acceptor (HBA), as shown in Figure 1.
Figure 1.
Interaction of hydrogen bonds between 3D (left) and 2D (right) structure 4-OHT with
Arg394 and Glu353 in human ERα (Black dotted lines indicate hydrogen bonds,
salt bridges, and metal interactions. Solid green lines indicate hydrophobic
interactions).
The hydrophobicity of 4-OHT mostly interacts with the
aromatic ring and the butenyl group also forms positive ionized interactions
with the secondary amine nitrogen. Hydrogen bond interactions are formed with
hydroxyl oxygen and phenoxy as shown in Figure 2.
Figure 2. (left)
3D structure-based pharmacophore modeling of 4-OHT with ERα (PDB ID: 3ERT) (The
interactions of positively ionizable hydrophobic hydrogen bond donors and
acceptors are represented as blue stars, yellow balls, green and red arrows).
(right) 2D structure-based 3ERT shows the hydrophobic interactions with the binding
pocket residues.
ERα has a ligand-binding domain (LBD) that is primarily a
hydrophobic cavity composed of amino acid residues of helices 3, 6, 7, 8, 11,
and 12. The agonist and antagonist activities of the ligands are determined by
helix-12 of residue 536- 544 in its macromolecule (ERα). When a 4-OHT
antagonist of ERα binds to LBD, helix-12 will be closed and not bound to the
co-activator, and therefore it has antagonistic activity based on the absence
of hydrogen bonding interactions with His524 (14). Based on the interaction
between 4-OHT and the pharmacophore features of human ERα, two features of four
aromatic rings of HBD and one HBA were produced using LigandScout.
Molecular validation of the docking was performed by
rebinding the co-crystallized 4-OHT to its original position at the human ERα
binding site. The results show a binding mode similar to that of the original
complex. The 4-OHT molecule interacts with Arg394 and Glu353. The validity of
the docking program was confirmed by placing the 4-OHT pose, which was
re-docking with the original resulting in an RMSD value of 0.590. This value is
defined as valid as shown in figure 3.
Figure
3. Superimposition of the original and re-docking 4-OHT molecule (RMSD =
0.590).
The best docking conformation of isorhamnetin and
isokesitrin in the ERa ligand-binding domain is indicated by the presence of
hydrogen bonds with Arg394 and Glu353 important amino acid residues in the
human ERα binding pocket and with other amino acid residues as shown in Figure
4.