Please use this identifier to cite or link to this item: https://doi.org/10.6026/97320630012324
Title: Novel aromatase inhibitors selection using induced fit docking and extra precision methods: Potential clinical use in ER-alpha-positive breast cancer.
Authors: Kumavath, Ranjith
Azad, Manan
Devarapalli, Pratap
Tiwari, Sandeep
Kar, Shreya
Barh, Debmalya
Azevedo, Vasco
Kumar, Alan Prem 
Keywords: anticancer drug
aromatase inhibitors
breast cancer
molecular docking
Issue Date: 2016
Publisher: Biomedical Informatics
Citation: Kumavath, Ranjith, Azad, Manan, Devarapalli, Pratap, Tiwari, Sandeep, Kar, Shreya, Barh, Debmalya, Azevedo, Vasco, Kumar, Alan Prem (2016). Novel aromatase inhibitors selection using induced fit docking and extra precision methods: Potential clinical use in ER-alpha-positive breast cancer.. Bioinformation 12 (6) : 324-331. ScholarBank@NUS Repository. https://doi.org/10.6026/97320630012324
Abstract: Aromatase (CYP19A1) the key enzyme of estrogen biosynthesis, is often deregulated in breast cancer patients. It catalyzes the conversion of androgen to estrogen, thus responsible for production of estrogen in human body. However, it causes over-production of estrogen which eventually leads to proliferation of breast cancer cells. Identification of new small molecule inhibitors targeted against CYP19A1 therefore, facilitates to increase drug sensitivity of cancer cells. In this scenario, the present study aims to identify new molecules which could block or suppress the activity of aromatase enzyme by molecular docking studies using Schrödinger-Maestro v9.3. In this study we used in silico approach by modeling CYP19A1 protein the strcture was subjected to protein preparation wizard; to add hydrogen and optimize the protonation states of Thr310 and Ser478 and Asp309 residues. Active site of the CYP19A1 protein was identified using SiteMap tool of Scchrodinger package. We further carried out docking studies by means of Glid, with various ligands. Based on glid score, potential ligands were screeened and their interaction with CYP19A1 was identified. The best hits were further screened for Lipinski's rule for drug-likeliness and bioactivity scoring properties. Thus, we report two rubivivaxin and rhodethrin compounds that have successfully satisfied all in silico parameters, necessitating further in vitro and in vivo studies.
Source Title: Bioinformation
URI: https://scholarbank.nus.edu.sg/handle/10635/237220
ISSN: 0973-2063
DOI: 10.6026/97320630012324
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