In silico Molecular Modelling of Selected Natural Ligands and their Binding Features with Estrogen Receptor Alpha
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Published:2018-12-14
Issue:1
Volume:15
Page:89-96
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ISSN:1573-4099
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Container-title:Current Computer-Aided Drug Design
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language:en
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Short-container-title:CAD
Author:
Maruthanila V.L.1, Elancheran R.2, Roy Nand Kishor3, Bhattacharya Anupam4, Kunnumakkara Ajaikumar B.3, Kabilan S.5, Kotoky Jibon2
Affiliation:
1. Department of Biotechnology, A.V.C. College, Mannampandal-609305, Tamil Nadu, India 2. Drug Discovery Lab, Life Sciences Division, Institute of Advanced Study in Science and Technology, Guwahati-781035, Assam, India 3. Department of Biosciences and Bioengineering, Indian Institute of Technology, Guwahati, Assam-781039, India 4. Bioinformatics Center, Life Sciences Division, Institute of Advanced Study in Science and Technology, Guwahati- 781035, Assam, India 5. Department of Chemistry, Annamalai University, Chidambaram- 608002, Tamil Nadu, India
Abstract
Background:
Breast cancer is one of the most common cancers diagnosed among women. It
is now recognized that two receptors mediate estrogen action and the presence of estrogen receptor alpha
(ERα) correlates with better prognosis and the likelihood of response to hormonal therapy. ERα is
an attractive target for the treatment of breast cancer. Most of the drugs currently used for the breast
cancer treatment have numerous side effects and they are often unsuccessful in removing the tumour
completely. Hence, we focused on natural compounds like flavonoids, polyphenols, etc. which do not
exhibit any high toxic effects against normal cells.
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Objectives: To identify the potential natural inhibitors for BCa through an optimised in silico approach.
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Methods: Structural modification and molecular docking-based screening approaches were imposed to
identify the novel natural compounds by using Schrödinger (Maestro 9.5). The Qikprop v3.5 was used
for the evaluation of important ADME parameters and its permissible ranges. Cytotoxicity of the
compounds was evaluated by MTT assay against MCF-7 Cell lines.
Results:
From the docking studies, we found that the compounds, Myricetin, Quercetin, Apigenin,
Luteolin and Baicalein showed the highest Glide Scores -10.78, -9.48, -8.92, -8.87 and -8.82 kcal mol-1
respectively. Of these, Luteolin and Baicalein showed the significant IC50 values (25 ± 4.0 and 58.3 ±
4.4 µM, respectively) against MCF-7 cell line. The ADME profiling of the test compounds was evaluated
to find the drug-likeness and pharmacokinetic parameters.
We mainly focused on in silico study to dock the compounds into the human estrogen receptor
ligand binding domain (hERLBD) and compare their predicted binding affinity with known antiestrogens.
Myricetin, Quercetin, Apigenin, Luteolin and Baicalein were identified as the most promising
among all. Of these, Luteolin and Baicalein showed significant anticancer activities against MCF-7 cell
line. These findings may provide basic information for the development of anti-breast cancer agents.
Publisher
Bentham Science Publishers Ltd.
Subject
Drug Discovery,Molecular Medicine,General Medicine
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