Molecular Docking Studies and Orbital Analysis to Identify Anti-Cancerous Potentials to Prevent Breast Cancer

Authors(2) :-V. Kavitha, Dr. N. Gunavathy

Breast cancer is the cancerous condition that develops in breast tissues, which could be invasive or non-invasive cancer. Hormonal therapy is general practice to control the estrogen level in Estrogen Receptor – positive (ER+) condition of breast cancer. Phytoestrogens that have been hypothesized to reduce risk of breast cancer and Glycine max (Soya bean) is a primary source of isoflavones, which has structure similar to estrogen receptor molecule. Glycine max intake in the diet has been associated with low risk for developing breast cancer. The aim of the study was to identify anti-cancerous potentials from Glycine max with the help of docking studies and molecular orbital analysis. Insilico docking studies were carried out using computational methods, based on Lamarckian genetic algorithm and PM7. This theoretical analysis could lead to further improvement of potent estrogen receptor antagonists for treatment of cancerous conditions.

Authors and Affiliations

V. Kavitha
Department of Chemistry, Nirmala College for Women, Coimbatore, Tamil Nadu, India
Dr. N. Gunavathy
Assistant Professor, Department of Chemistry, Nirmala College for College, Coimbatore, Tamil Nadu, India

Glycine max, Phytoestrogens, Molecular Docking, Autodock, MOPAC

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Publication Details

Published in : Volume 2 | Issue 4 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 483-488
Manuscript Number : CSEIT1724130
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

V. Kavitha, Dr. N. Gunavathy, "Molecular Docking Studies and Orbital Analysis to Identify Anti-Cancerous Potentials to Prevent Breast Cancer ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.483-488, July-August-2017.
Journal URL : http://ijsrcseit.com/CSEIT1724130

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