Simple jQuery Dropdowns
Please use this identifier to cite or link to this item:
Title: Towards understanding aromatase inhibitory activity via QSAR modeling
Authors: Watshara Shoombuatong
Nalini Schaduangrat
Chanin Nantasenamat
Mahidol University
Keywords: Agricultural and Biological Sciences;Biochemistry, Genetics and Molecular Biology;Pharmacology, Toxicology and Pharmaceutics
Issue Date: 20-Jul-2018
Citation: EXCLI Journal. Vol.17, (2018), 688-708
Abstract: © 2018, Leibniz Research Centre for Working Environment and Human Factors. All rights reserved. Aromatase is a rate-limiting enzyme for estrogen biosynthesis that is overproduced in breast cancer tissue. To block the growth of breast tumors, aromatase inhibitors (AIs) are employed to bind and inhibit aromatase in order to lower the amount of estrogen produced in the body. Although a number of synthetic aromatase inhibitors have been released for clinical use in the treatment of hormone-receptor positive breast cancer, these inhibitors may lead to undesirable side effects (e.g. increased rash, diarrhea and vomiting; effects on the bone, brain and heart) and therefore, the search for novel AIs continues. Over the past decades, there has been an intense effort in employing medicinal chemistry and quantitative structure-activity relationship (QSAR) to shed light on the mechanistic basis of aromatase inhibition. To the best of our knowledge, this article constitutes the first comprehensive review of all QSAR studies of both steroidal and non-steroidal AIs that have been published in the field. Herein, we summarize the experimental setup of these studies as well as summarizing the key features that are pertinent for robust aromatase inhibition.
ISSN: 16112156
Appears in Collections:Scopus 2018

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.