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Multitargeted Molecular Docking Study of Natural-Derived Alkaloids on Breast Cancer Pathway Components.

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BACKGROUND Targeting of multiple sites is a pharmacologically, pharmacokinetic and dynamically more acceptable approach for complex diseases such as BC. It is recommended that the women who are at high… Click to show full abstract

BACKGROUND Targeting of multiple sites is a pharmacologically, pharmacokinetic and dynamically more acceptable approach for complex diseases such as BC. It is recommended that the women who are at high risk of developing BC might be given foods enhanced by indole alkaloids from vegetables like cabbage and broccoli. Administration of indole-3-carbinol is associated with decreased incidence of hormone-responsive BC (HRBC) which is implicated due to the induction of cytochrome P450 and glutathione-S-transferase which metabolizes chemical mutagens and by altering estrogen metabolism. OBJECTIVE To determine the molecular mechanism behind the anticancer activity of natural indole alkaloids present in various food and nutraceuticals products by utilizing Induced-fit docking (IFD) approach. METHODS Indole alkaloids were obtained from the database maintained by ChEBI (The database and ontology of Chemical Entities of Biological Interest) with ChEBI id 38958. The 3-dimentional and X-ray structure coordinates of Estrogen receptor- α (ER-α), Estrogen receptor- β (ER-β), and aromatase were obtained from protein data bank with PDB id codes 3ERT, 3OLS, and 3S7S (www.rcsb.org). The Induced fit molecular docking and ADME properties were calculated using Maestro 9.6. RESULTS IFD analysis showed that bromocriptine exhibits maximum binding affinity towards ER-α and fellutanine B towards ER-β and aromatase. CONCLUSION Present research provided in-depth analysis of molecular mechanism and helped in the future design of new pharmacophores based on natural indole alkaloids targeting BC.

Keywords: docking study; study natural; molecular docking; indole alkaloids; multitargeted molecular

Journal Title: Current computer-aided drug design
Year Published: 2017

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