Abstract
Breast cancer is the most frequent female cancer and one of the leading causes of cancer death in women. There are many chemotherapy agents available for the treatment of breast cancer. Still, the current therapeutic options have not fulfilled the desired outcomes, especially for drug-resistant breast cancer therapy. Thus, there is an urgent need to develop novel anti-breast cancer agents. Coumarin is ubiquitous in natural and synthetic bioactive compounds, and coumarin derivatives readily interact with a variety of enzymes and receptors in breast cancer cells. Moreover, the coumarin-based irosustat as the first-generation steroid sulfatase inhibitor in breast cancer is under clinical evaluation, revealing the potential of coumarin derivatives as novel anti-breast cancer agents. This review aims to describe the recent development of natural and synthetic coumarin derivatives with anti-breast cancer potential, covering the articles published from 2015 to 2020.
Keywords: Coumarin, Natural product, Dimers, Hybrids, Breast cancer, Steroid, Cancer cells.
Graphical Abstract
Call for Papers in Thematic Issues
Adaptogens—History and Future Perspectives
Adaptogens are pharmacologically active compounds or plant extracts that are associated with the ability to enhance the body’s stability against stress. The intake of adaptogens is associated not only with a better ability to adapt to stress and maintain or normalise metabolic functions but also with better mental and physical ...read more
Addressing the Most Common Causes of Death with Niacin/NAD and Inositol Polyphosphates
The most common causes of death in the world are cardiovascular disease (CVD) and cancer. These are perhaps best addressed by reducing lipodystrophy and blockages with niacin and inositol polyphosphates (e.g., IP6+inositol) respectively when addressing CVD. Niacin serves as a vitamin by virtue of its role as a skeletal precursor ...read more
AlphaFold in Medicinal Chemistry: Opportunities and Challenges
AlphaFold, a groundbreaking AI tool for protein structure prediction, is revolutionizing drug discovery. Its near-atomic accuracy unlocks new avenues for designing targeted drugs and performing efficient virtual screening. However, AlphaFold's static predictions lack the dynamic nature of proteins, crucial for understanding drug action. This is especially true for multi-domain proteins, ...read more
Artificial intelligence for Natural Products Discovery and Development
Our approach involves using computational methods to predict the potential therapeutic benefits of natural products by considering factors such as drug structure, targets, and interactions. We also employ multitarget analysis to understand the role of drug targets in disease pathways. We advocate for the use of artificial intelligence in predicting ...read more
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