Rafeeq, Misbahuddin M. and Sain, Ziaullah M. and Alturki, Norah A. and Alzamami, Ahmad and Asiri, Saeed A. and Mashraqi, Mutaib M. and Alqosaibi, Amany I. and Alnamshan, Mashael M. and Almutairi, Abdulrahman and Alanazi, Abdulkhaliq Munawir and Alam, Qamre (2021) Computational Screening of Natural Compounds for the Discovery of Potential Aromatase Inhibitors: A Promising Therapy for Estrogen-Dependent Breast Cancer. Journal of Pharmaceutical Research International, 33 (32A). pp. 72-78. ISSN 2456-9119
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Abstract
Aromatase plays a significant role in the progression of estrogen receptor-positive (ER-positive) breast cancer. The adverse side effects of currently used aromatase inhibitors (AIs) necessitate the development of new AIs that are more active, selective, and less toxic. This study used a computational approach to screen 503 natural compounds ZINC database against the aromatase active site. The best scoring hits ZINC69482055, ZINC69482510, and ZINC406719 exhibited strong binding with aromatase, with binding energy values of -8.45, -10.35, and -8.75 kcal/mol, respectively, which is comparatively higher than that of the control compound Anastrozole (-6.43 kcal/mol). Docking analysis showed that the selected hits interacted with the crucial residues of the aromatase active site. This study suggested that these compounds could be used as possible AIs in the cure of breast cancer. Hands-on bench work validation is needed to optimize these compounds as AIs.
Item Type: | Article |
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Subjects: | Universal Eprints > Medical Science |
Depositing User: | Managing Editor |
Date Deposited: | 16 Feb 2023 06:41 |
Last Modified: | 26 Jun 2024 06:30 |
URI: | http://journal.article2publish.com/id/eprint/819 |