Publication: Towards understanding aromatase inhibitory activity via QSAR modeling
Issued Date
2018-07-20
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ISSN
16112156
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2-s2.0-85051467585
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Mahidol University
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SCOPUS
Bibliographic Citation
EXCLI Journal. Vol.17, (2018), 688-708
Suggested Citation
Watshara Shoombuatong, Nalini Schaduangrat, Chanin Nantasenamat Towards understanding aromatase inhibitory activity via QSAR modeling. EXCLI Journal. Vol.17, (2018), 688-708. doi:10.17179/excli2018-1417 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/44713
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Towards understanding aromatase inhibitory activity via QSAR modeling
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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.