Abstract
Autophagy is an important basic metabolic mechanism by engulfing and degrading the unnecessary or dysfunctional cellular components within double-membered autolysosomes to maintain cellular homeostasis. Autophagy has sparkled great interest for its complicated functions in different stages of cancer, and is regarded as a potential target for anticancer therapy. As a suppressor pathway, autophagy prevents tumor initiation and as a survival pathway, autophagy contributes to tumor growth and progression by attenuating cellular metabolic stress and resisting therapeutic agents-induced cell death. Many autophagy regulators have been identified as potential cancer therapeutic agents and some cytotoxic anticancer drugs also induce autophagy. Combination regimen of autophagy regulators with other anticancer agent exhibits desirable efficacy and several protocols are underway in clinical trials. This review delineates the possible role of autophagy in anticancer therapy, and discusses reported potent autophagy regulators in cancer treatment.
Keywords: Autophagy, Autolysosome, Autophagy inducers, Autophagy inhibitors, Beclin1, Cancer treatment, Drug discovery.
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
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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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